INSERT INTO `resume` (`id`, `screeningId`, `adminId`, `candidateId`, `candidateDetailsId`, `resumeName`, `resumeOriginalName`, `resumeContent`, `isSkillScreened`, `isResumeScreened`, `isCron`, `isCandidate`, `candidateShortlist`, `enableInterviewReport`, `gptLanguageId`, `isInterviewAssign`, `interviewValidity`, `interviewAssignDate`, `isPsychoAssign`, `psychoValidity`, `psychoAssignDate`, `created`, `createdBy`) VALUES
(373, 89, 73, 34, NULL, '73_89_17437761646697641053c39_Asmiya_Begum_N-Developer-Connected_Vehicle.pdf', 'Asmiya Begum N-Developer-Connected Vehicle.pdf', 'Asm iy a  B eg u m  N\nA ndro id  D eve lo p er\n	C hen nai		+ 91 9 003606100		asm iy a b eg u m .n m r@ gm ail.c o m	\nasm iy a -b eg u m\nasm iy a -b eg u m	\nE xp erie n ce d  A ndro id  D eve lo p er w it h  3 .3  y e ars  o f e x p ertis e  i n  b u ild in g h ig h -q u ali t y  a p pli c a tio n s t h ro u gh  c le an\nco d e a n d b est p ra ctic e s. P ro fic ie n t i n  u sin g d iv e rs e  l i b ra rie s a n d f r a m ew ork s t o  a d dre ss  r e al- w orld  c h alle n ges.\nD ed ic a te d  t o  m ain ta in in g s tr u ctu re d  c o d e o rg a n iz a tio n  a n d c o n sis te n tly  i m pro vin g c o d e q u ali t y . A ctiv e ly  s e ek in g a\nn ew  r o le  t o  e x p an d k n ow le d ge o f e m erg in g t e ch n olo gie s a n d c o n tr ib u te  t o  s o lv in g u se r c h alle n ges.\nW ORK  E X PER IE N CE\nH TC G lo b al S erv ic e s\nM ob ile  A ppli c a tio n  D eve lo p er	\nS ep  2 023 -  P re se n t	\nChen nai	\n	h tt p s:// w ww.h tc in c.c o m /	\nHTC  G lo b al S erv ic e s p ro vid es I T  a n d B usin ess  P ro ce ss  S erv ic e s a n d S olu tio n s t h at h elp  b u sin ess e s m ak e d ig it a l\nch an ge h ap p en .	\nColla b ora te d  o n  f e atu re  i m ple m en ta tio n  f o r t h e H orm an n p ro je ct.\nW ork ed  f o r t h e P en sk e c li e n t o n  i m ple m en tin g s u pply  c h ain  m an agem en t f e atu re s, i n clu din g o rd er t r a ck in g\nan d w atc h li s t f u n ctio n ali t ie s.\nW ork ed  o n  t h e g o ogle  m ap s t o  t r a ck  t h e s h ip m en ts  i n  a p pli c a tio n .\nIm ple m en te d  M SA L i n  a n  A ndro id  a p p t o  f a cili t a te  s e cu re  u se r a u th en tic a tio n  v ia  A zu re  A D, h an dli n g t o k en\na cq u is it io n  a n d r e n ew al f o r a cce ss in g p ro te cte d  A PIs .	\nG ofr u gal T ech n olo gie s P vt L td\nA ndro id  D eve lo p er	\nF eb  2 021 -  J u n  2 023	\nC hen nai	\n	h tt p s:// w ww.g o fr u ga l.c o m /	\nGofr u ga l i s  a  s o ft w are  c o m pan y t h at p ro vid es r e ta il /  P O S s o lu tio n s f o r s m all a n d m ed iu m  s iz e d  b u sin ess e s a cro ss\nv a rio u s i n du str ie s.	\nD eve lo p ed  m ob ile  a p pli c a tio n  w it h  h ig h -p erfo rm an ce  b arc o d e a n d Q R c o d e s c a n nin g.\nE nab le d  o ffli n e c a p ab ili t y  a n d u tili z e d  a d va n ce d  a lg o rit h m s f o r e ffic ie n t c o m pu ta tio n .\nU pgra d ed  c a m era  s c a n nin g f r o m  G M S V is io n  t o  C am era X  f o r f a ste r b arc o d e d ete ctio n .\nExp erie n ce d  i n  A ndro id  f e atu re s l i k e R xJa va , M VVM , D ata  B in din g, B ro ad ca st R ece iv e rs , F C M , C on te n t\nPro vid ers , O kH tt p , R etr o fit ,N av ig atio n ,a n d K otli n  s p ecif ic  f e atu re s s u ch  a s C oro u tin es, K otli n  S eria li z a tio n .\nIn te g ra te d  w it h  t h e p rin te r s d k t o  s u pp ort t h e i n  a p p p rin tin g. U tili z e d  M VVM  a rc h it e ctu re  f o r m ob ile  a p p\ndeve lo p m en t a n d s e p ara te d  a p p d ata , U I, a n d a p p l o gic  f o r b ett e r c o d e o rg a n iz a tio n  a n d m ain ta in ab ili t y .\nIm ple m en te d  s h are d  v ie w  m od els  f o r i m pro ve d  s c a la b ili t y  a n d c o d e r e u sa b ili t y .\nE xp erie n ce d  w ork in g o n  i m age l o ad in g t a sk s u sin g G li d e,a n d C oil.\nE nhan ce d  m ob ile  a p p s e cu rit y  b y e n cry p tin g b oth  a p p a n d u se r d ata .\nP erfo rm ed  s e cu rit y  t e stin g i n  Z A P , M OBSF  , S Q L m ap .\nG ain ed  e x te n siv e  k n ow le d ge o f m ult it h re ad in g a n d m em ory  m an agem en t f o r o p tim iz e d  a p p p erfo rm an ce .\nA uto m ate d  r e le ase  b u ild  a n d d ep lo ym en t i n  p la ysto re  u sin g f a stla n e.	\nP ro je cts\nI n ve n to ry  C on tr o l\nM ob ile  P O S I n ve n to ry  C on tr o l A ppli c a tio n\n	h tt p s:// p la y.g o ogle .c o m /s to re /a p ps/d eta ils ?id =co m .g o fr u ga l.s to ck m an agem en t&amp; pli = 1\nG oS u re  i s  a n  i n ve n to ry  c o n tr o l a p pli c a tio n  t h at e n ab le s u se rs  t o  p erfo rm  a ll i n ve n to ry -r e la te d  o p era tio n s i n\nP O S. I t  c o n sis ts  o f f o u r m od u le s: s to ck  t a k in g, G RN  ( G ood s R ece ip t N ote ), s to ck  p ic k , a n d s to ck  r e fill . T hese\nm od u le s p ro vid e f u n ctio n ali t ie s f o r m an ag in g s to ck  c o u n ts , r e co rd in g i n co m in g g o od s, p ic k in g i t e m s f o r\nord ers , a n d r e p le n is h in g s to ck .\nIt  i s  a  s tr o n g a n d r e li a b le  a p pli c a tio n  t h at c a n  h an dle  a  l a rg e c u sto m er d ata b ase  w it h ou t s lo w in g d ow n o r\nca u sin g a n y p erfo rm an ce  i s s u es.\nIt  e ffic ie n tly  m an ages e x te n siv e  c u sto m er d ata  w hile  m ain ta in in g h ig h  p erfo rm an ce  l e ve ls .\nIt  i s  a  u se r-fr ie n dly  a p pli c a tio n  t h at w ork s o n  b oth  m ob ile  d evic e s a n d P D A  d evic e s.\nIt  a llo w s u se rs  t o  s c a n  b arc o d es u sin g e it h er t h e d evic e &#039;s  b u ilt - in  b arc o d e s c a n ner o r t h e c a m era . T his  m ak es i t\ne asy  t o  c a p tu re  i n fo rm atio n  a n d m an age i n ve n to ry  e ffe ctiv e ly .\nIt  k eep s d ata  s a fe  a n d s e cu re  i n  b oth  o ff li n e a n d o n li n e m od es, p re ve n tin g a n y l o ss  o f i n fo rm atio n .\nIt  i s  a  n ativ e  A ndro id  a p pli c a tio n  u sin g K otli n , t a rg etin g A ndro id  d evic e s	\nP ric e  C heck er ( K IO SK )\nPric e  a n d L oya lt y  P oin ts  C heck in g A ppli c a tio n\n	h tt p s:// p la y.g o ogle .c o m /s to re /a p ps/d eta ils ?id =co m .g o fr u ga l.g o ch eck .r e le a se\nG oC heck  i s  a  p ric e  t a g  c h eck in g a p pli c a tio n  d esig n ed  t o  b e p la ce d  o n  t h e r a ck s i n  r e ta il s h op s.\nIt  e q u ip p ed  w it h  a  b arc o d e s c a n ner. W hen  a  b arc o d e i s  s c a n ned , i t  d is p la ys t h e d eta ils  o f a n y o ffe rs  a va ila b le\na n d t h e c o rre sp on din g l o ya lt y  p oin ts  f o r t h e c u sto m er.\nI t  s u pp orts  b oth  b arc o d e s c a n nin g a n d c a m era  s c a n nin g f u n ctio n ali t ie s. U se rs  c a n  c h oose  t o  s c a n  b arc o d es\nu sin g a  b arc o d e s c a n ner o r u tili z e  t h e d evic e &#039;s  c a m era  t o  c a p tu re  a n d p ro ce ss  b arc o d e i n fo rm atio n  w it h in  t h e\nap pli c a tio n . T his  p ro vid es f le x ib ili t y  i n  s c a n nin g m eth od s f o r e ffic ie n t a n d c o n ve n ie n t u se .\nIt  i s  a  n ativ e  A ndro id  a p pli c a tio n  u sin g K otli n , t a rg etin g A ndro id  d evic e s.	\nH orm an n S erv ic e  S u pp ort A pp\nD oor I n sta lla tio n  S erv ic e  S u pp ort A ppli c a tio n\n	h tt p s:// p la y.g o ogle .c o m /s to re /a p ps/d eta ils ?id =co m .h orm an n .s e rv ic e su pp orta p pli c a tio n &amp; hl= en &amp; gl= U S\nThe H orm an n s e rv ic e  s u pp ort a p pli c a tio n  i s  d esig n ed  t o  a ss is t i n sta lle rs  a n d s e rv ic e  e n gin eers  b y p ro vid in g\nhelp fu l i n sta lla tio n  a n d t r o u ble sh ootin g i n fo rm atio n .\nIt  i n clu des s e arc h ab le  f a u lt  c o d es, p ara m ete r c o d es, q u ic k  s ta rt t ip s, c o m mon  i s s u es, a n d s c h em atic s.\nIt  f e atu re s m od u le s t o  d is p la y c ir c u it  i m ages, d oor i n sta lla tio n  i n str u ctio n s, a n d t r o u ble sh ootin g g u id es w it h in\nt h e a p p i n te rfa ce .\nA  m od u le  a llo w in g t h e p la yb ack  o f i n str u ctio n al v id eo s d ir e ctly  f r o m  Y ou T ube U RLs w it h in  t h e a p pli c a tio n .	\nSu pply  C hain  I n sig h t\nO rd ers  t r a ck in g a p pli c a tio n  f o r s u ppli e r\n	h tt p s:// w ww.p en sk e.c o m /\nSu pply  C hain  I n sig h t i s  a n  a p pli c a tio n  t h at a llo w s u se rs  t o  t r a ck  l o ad s, o rd ers , v ie w  d eta ile d  o rd er i n fo rm atio n\nalo n g w it h  t im eli n es.\nIt  f e atu re s a n  i n fo rm ativ e  d ash board  w here  u se rs  c a n  v ie w  c o m pan y-s p ecif ic  i n sig h ts  o n  l o ad s, o rd ers ,\nw atc h li s ts , a n d l a te  o rd ers .\nIt  i s  i n te g ra te d  w it h  G oogle  M ap s t o  t r a ck  o rd ers  i n  r e al- tim e.\nT he a p p&#039;s  n etw ork  c a lls  a re  s e cu re d  u sin g t h e M ic ro so ft  A uth en tic a tio n  L ib ra ry  ( M SA L), w hic h  p erio d ic a lly\nr e fr e sh es t o k en s t o  p re ve n t v u ln era b ili t ie s.	\nP ers o n al P ro je cts\nS tr e am Vers e\nM ovie  S tr e am in g A ppli c a tio n\n	h tt p s:// g it h ub.c o m /A sm iy a B eg u m /S tr e am Vers e\nS tr e am Vers e  i s  a  m ovie  s tr e am in g p la tfo rm  t h at h as b een  d eve lo p ed  u tili z in g t h e e x o p la ye r f r a m ew ork .\nIt  f e atu re s a  u se r-fr ie n dly  h om e s c re en  w here  u se rs  c a n  e x p lo re  a  c a ro u se l s h ow ca sin g t h e l a te st a n d m ost\np op u la r m ovie s, a s w ell a s b ro w se  m ovie s c a te g o riz e d  a cco rd in g t o  d if fe re n t g en re s.\nIt  f e atu re s a  d ed ic a te d  v id eo  s tr e am in g i n te rfa ce  b u ilt  o n  t h e p ow erfu l e x o p la ye r f r a m ew ork . T his  i n te rfa ce\nb oasts  a  c u sto m  p la ye r l a yo u t t h at g re atly  e n han ce s t h e u se r e x p erie n ce . U se rs  c a n  e asily  a d ju st m ed ia  v o lu m e,\nsc re en  b rig h tn ess, s e ek  f o rw ard  o r b ack w ard  i n  t h e v id eo, c h an ge t h e s c re en  o rie n ta tio n , a n d e ve n  l o ck  t h e\nsc re en  t o  p re ve n t a cc id en ta l t o u ch es, e n su rin g a  s e am le ss  a n d e n jo ya b le  s tr e am in g e x p erie n ce .	\nS ketc h Flo w\nD ra w in g A ppli c a tio n\n	h tt p s:// g it h ub.c o m /A sm iy a B eg u m /S ketc h F lo w\nS ketc h F lo w  i s  a  m ob ile  a p p t h at l e ts  y o u  c re ate  a rt u sin g v a rio u s b ru sh es a n d c o lo rs . Y o u  c a n  c h an ge\nb ack gro u n ds, u n do, r e d o, a n d c le ar. I t  a llo w s s a v in g d ra ft s  f o r l a te r a n d e x p ortin g a rt t o  s p ecif ic  f o ld ers  a n d\nfo rm ats . Y ou  c a n  a ls o  s h are  y o u r c re atio n s w it h  o th er a p ps s e am le ss ly .	\nW eath erF ore ca st\nW eath er F ore ca stin g A ppli c a tio n\n	h tt p s:// g it h ub.c o m /A sm iy a B eg u m /W eath erF ore ca st\nIt &#039;s  a  w eath er f o re ca stin g a p pli c a tio n  t h at a llo w s u se rs  t o  s e arc h  f o r l o ca tio n s o r p in  t h em  o n  a  m ap  t o  r e tr ie ve\nth e w eath er s u m mary  f o r t h ose  a re as.\nIt  i n clu des a  f e atu re  f o r b ook m ark in g l o ca tio n s, a llo w in g u se rs  t o  e asily  a cce ss  b ook m ark ed  l o ca tio n s\nw hen eve r n ee d ed .\nT he a p pli c a tio n  i s  d eve lo p ed  u sin g J e tp ack  C om pose , p ro vid in g s u pp ort f o r b oth  l i g h t a n d d ark  m od es.	\nA ch ie ve m en ts\n-  D eve lo p ed  a  u se r-fr ie n dly  a p p i n te rfa ce  t h at r e su lt e d  i n  i n cre asin g u se r e n gagem en t.\n-  S u cce ss fu lly  i n tr o d u ce d  r o b u st s e cu rit y  m ea su re s, s e tt in g a  h ig h er s ta n dard  f o r d ata  p ro te ctio n .\n- E xce lle d  i n  m an ag in g a n d c o n tr ib u tin g t o  p ro je cts  i n  a  r e m ote  w ork  e n vir o n m en t, w hile  s e am le ss ly  o p tim iz in g\npro je ct e ffic ie n cy  t h ro u gh  e ffe ctiv e  c o lla b ora tio n  w it h  i n te rn al a n d i n te g ra tio n  t e am s.\nS tr e n gth\n-  P ro b le m  s o lv in g\nSu cce ss fu lly  a d dre ss e d  i n tr ic a te  t e ch n ic a l c h alle n ges t h ro u gh ou t t h e d eve lo p m en t o f t h e i n ve n to ry  c o n tr o l\nap pli c a tio n , l e ad in g t o  a  s ig n if ic a n t i m pro ve m en t i n  a p p p erfo rm an ce .\n- C olla b ora tio n\nC olla b ora te d  w it h  t e am  m em bers  t o  s u cc e ss fu lly  c o m ple te  p ro je cts  o n  t im e a n d w it h in  t im eli n e. A ctiv e ly  l i s te n ed  t o\nfe e d back  a n d i n co rp ora te d  c o n str u ctiv e  c rit ic is m  i n to  m y w ork .\n- A dap ta b ili t y\nP ro ve n  a b ili t y  t o  a d ap t q u ic k ly  t o  c h an gin g p rio rit ie s a n d t ig h t d ea d li n es, s u cce ss fu lly  c o m ple tin g a  h ig h pre ss u re\np ro je ct t h at r e q u ir e d  l e arn in g n ew  l i b ra ry  a n d c o lla b ora tin g w it h  t e am .\nSkills\nP ro gra m min g L an gu age s\n- K otli n  -  J a va  -  X M L	\nAndro id  D eve lo p m en t\n- A ndro id  S D K  -  J e tp ack  C om pose  -\nJ e tp ack  L ib ra rie s -  T hir d  P arty\nL ib ra rie s	\nD ata  P ers is te n ce\n- S h are d P re fe re n ce s -  E ncry p te d\nS h are d P re fe re n ce s -  D ata sto re  -\nP ro to D ata sto re  -  A ndro id  K ey S to re  -\nI n te rn al S to ra ge -  E xte rn al S to ra ge	\nD ata b ase s\n- R oom  -  R ealm  -  S Q Lit e  -  O bje ctB ox	\nD ep en den cy  I n je ctio n\n- H ilt  -  K oin	\nU I a n d D esig n  P att e rn s\n- T ra d it io n al D esig n  ( X M L) -  M od ern\nD ecla ra tiv e  ( J e tp ack  C om pose ) -\nD esig n  P att e rn s (  M VVM  ,  M VP )	\nN etw ork in g a n d A PIs\n-  R etr o fit  - O kH tt p  -  R estfu l A PI&#039;s  -\nW eb Sock et S erv ic e s	\nM ult it h re ad in g a n d C on cu rre n cy\n- C oro u tin es -  R X Ja va  -  L iv e D ata  -\nK otli n  F lo w s	\nM ed ia  a n d M ult im ed ia\n-  E xo p la ye r -  C am era  A PI&#039;s  (  G M S\nCam era  V is io n , C am era X ) -  I m age\nL oad in g ( G li d e, P ic a ss o , C oil)  -\nG oogle  C od e S ca n ners	\nD eve lo p m en t T ools  a n d V ers io n\nC on tr o l\n- G it H ub -  G ra d le  -  C I/ C D  (  J e n kin s,\nF astla n e )  -  G oogle  P la y C on so le  -\nA pp C en te r	\nD eb u ggin g T ools\n-  A ndro id  D eb u gger -  E m ula to rs  -\nA ndro id  P ro file r -  N etw ork\nIn sp ecto r -  C ra sh  L og -  F ir e b ase\nC ra sh ly tic s	\nA naly tic s\n- F ir e b ase  A naly tic s -  Z oh o A pptic s	\nT estin g\n- E sp re ss o  -  M ock it o  -  U I T estin g -\nU nit  T estin g	\nE ve n t H an dli n g a n d N av ig atio n\n- N av ig atio n  C on tr o lle r	\nA pp C om pon en ts\n-  B ro ad ca st R ece iv e rs  -  F C M\n(F ir e b ase  C lo u d M ess a g in g) -  W ork\nM an ager -  C on te n t P ro vid ers	\nS ecu rit y  T ools\n-  S on arQ ube -  Z A P -  M OBSF  -  S Q L\nM ap\nE du ca tio n\nA la g ap p a C hett ia r G ove rn m en t C olle ge  o f E n gin eerin g a n d T ech n olo g y\nE le ctr o n ic s a n d C om mun ic a tio n  E ngin eerin g\n8.5	\n2 017 -  2 021	\n	h tt p :// a cce te d u .i n /	\nLan gu age s\nE n gli s h\nP ro fe ss io n al\nT am il\nN ativ e', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-20 11:06:38', '2024-07-17 11:06:38', 0, NULL, NULL, '2024-07-17 06:26:24', 0),
(374, 90, 73, NULL, NULL, '73_90_1488666637669766d93dd45_Bhushan_Bende_Developer_Connected_Platform_(1).pdf', 'Bhushan Bende_Developer_Connected Platform (1).pdf', 'Bhushan	Bende	\nSoftware	Engineer	\nRoles	:Senior	Software	Engineer	\nE-mail:	bhushanyahoo@gmail.com	\nMobile:	9405708908	\nProfessional	Synopsis:	\n	Experience	inPython	Developer	,Building	APIand	Data	Pipeline	,with	PRDomain	\n	Experience	onworking/building	Python-Fast	API	hosted	onLambda	connected	with	Elastic	Search	\n	Building	ETL	&amp;ELT	Data	Pipeline	inPython	with	AWS	Managed	Streaming	Application	Flink,	Self	Managed	Flink	and	AWS	Lambda	\n	5years	ofFunctional	and	Automation	Testing	experience	inInvestment	Banking	Domain	,Payment	Domain	and	Media	Monitoring.	\n	Keen	understanding	onCapital	Market	and	Money	Market.	\n	Well	versed	knowledge	ofPayments	system	and	Gateway	transaction	\n	Well	versed	inallphases	ofSoftware	Development	Life	Cycle	(SDLC)	and	Software	Testing	Life	Cycle	(STLC).	\n	Experience	inTesting	Web	Based	Application,	Windows	Based	Application	,Web-Service	and	Database	.	\n	Extensive	Knowledge	inwriting	Functional	and	Regression	Test-cases	,maintaining	and	modifying	test	cases.	\n	Proficient	inautomation	using	Selenium	Web-driver	with	Java	programming	language	.	\n	Extensive	knowledge	ofwriting	scripts	using	Element	locators	,Web-driver	methods	and	Java	Programming	.	\n	Generating	defect	report	and	interacting	with	developers	toresolve	the	defects.	\n	Having	good	exposure	todefect	management,	raising	defect/bugs.	\n	Having	good	time	management	towork	ondifferent	types	ofreleases	simultaneously	(BAU/OOC/Strategic).	\n	Has	rigorously	worked	onAPI	Testing	and	API	Test	Automation	with	JavaScript	-Mocha	Framework	\n	Extensive	knowledge	onvarious	testing	methodologies	like	UAT,	SIT,	Regression	testing,	Sanity	testing,	Smoke	testing,	and	\nFunctional	testing	.	\n	Experience	inusing	Test	Management	tool	HP-ALM,	JIRA	,Rally	.	\n	Great	exposure	toMS-OFFICE	suite	,Google	Suite	.	\n	Worked	extensively	onautomating	BFS	applications	from	enhancing	the	Automation	framework	inEclipse	using	Maven	tocommitting	\nthe	code	toBitBucket	/GITHUB	and	storing	test	artefacts	inJIRA	after	every	sprint	completion	.	\n	Have	working	experience	inCI/CD	model.	\n	Has	Good	Understanding	onEvent	Driven	System,	that	takes	data	asevent	process	it.	\n	Worked	onsetting	upKAFKA	and	KINESIS	for	Data	Stream	Processing	\n	Worked	onBuilding	Data	Pipeline	inPython	and	Deploying	itonAWS	Lambda	\n	Has	good	interpersonal,	communication	and	organizational	skill	with	ability	tointeract	effectively	with	colleagues	atalllevel.	\nTech	Stack:\nLanguages:	Python,	Core	Java,	SQL	,Javascript-NodeJS	\nOperating	System:	Windows,	Linux	,MacOS	\nTest	Management	Tool:	HP-ALM,	JIRA	,Rally	\nData	Base	Tools:	DBeaver,	MySQL,	Microsoft	SQL	Server	.,Google	Big	Query,	ElasticSearch	\nKnowledge	And	Worked	On:	API	Testing	with	POSTMAN,	API	Performance	Testing	with	JMeter	,ETL	Testing,	GCP,	AWS	EC2,	AWS	Lambda,	\nAWS	KINESIS,	Kafka,	Data	Streaming	Project,	API	Contract	Testing,	Docker	\nVersioning	Tool:	GIT	\nCertification:	GIT	(Udemy)	,AWS	API	GATEWAY(AWS),	GCP	KAFKA(GOOGLE),	Streaming	Pipeline	Using	Pyspark	and	Kakfa	\nAutomation	Framework	:BDD	-Cucumber,	TDD-	TestNG,	JavaScript	Mocha	\nAPI	Development	Framework	:Fast	API	Python	\nDeployment	Framework	:Zappa	\nAutomation	Tools:	Selenium	Web-driver,	Jenkins	,TestNG,	Cucumber	\nDeployment	Stack:	Kubernetes,	AWS	EKS	\nEmployment	Detail:	\nName	OfCompany	:Onclusive,	Mumbai	\nDesignation	:Senior	Software	Engineer	(Data	Engineer)	\nDuration	:19Oct	2022	ToCurrent	\nName	OfCompany	:TSYS	,Pune	\nDesignation	:Automation	Developer	\nDuration	:17May	2021	To	18Oct	2022	\nName	OfCompany	:Altimetrik,	Pune	\nDesignation	:Automation	Quality	Engineer	\nDuration	:18Jan	2021	To15May	2021	\nName	ofCompany	:Cognizant	Technology,	Pune	\nDesignation	:Test	Professional	\nDuration	:26June	2018	TO	15Jan	2021\n\nOnclusive	\nProject	1:	\nName	:Data	Platform	\nDesignation	:Senior	Software	Engineer	\nProject	Description	:Onclusive	isaMedia	Monitoring	Company.	Which,	monitors	the	Articles	,Content,	News,	Radio,	Youtube	and	also	TV	\nChannel.	Tofind	out	the	sentiment	for	the	particular	product	inmarket.	\nWhere	we	have	multiple	sources	who	pushes	Petabyte	ofdata	into	our	system	we	stream	that	into	MSK	Kafka	and	then	into	AWS	Kinesis	,using	\nData	Pipeline	asaconsumer	we	fetch	itand	process	ittoElastic	Search.(Elastic	stack)	\nAfterwards	this	used	for	sentiment	analysis	ofmarket	and	further,	using	API	this	Data	isfetch	and	given	toDown-Stream	Application	for	ML/AI	\npipeline.\nRole/Responsibility:	\n	ToDevelop	API	that	connects	with	Elastic-Search	and	fetch	out	data	with	relevant	query	that	we	build	run	time	.	\n	We	dohave	lots	ofAPI	that	exports	the	for	articles	based	onuser-query,	Iworked	onDeveloping	and	maintaining	API	\n	Todevelop	Data	Pipeline	Fetching	data	from	Apache	Kafka	and	AWS	Kinesis	then	transforming	and	Pushing	ittoStorage.(with	hosted	\nservice	onAWS	Lambda)	\n	Interm	tomodernize	these	pipeline	and	improving	the	performance	we	have	shifted	toApache	Flink	and	Apache	Beam	Pipeline	\no	Where	itfetch	data	from	Kafka,	using	UDF	we	modify	and	transform	this	data	and	push	itback	toElastic	Sink.	\no	Elastic	Sink	isself	managed	service	that	push	data	toElastic	Search	\n	Responsible	for	developing	and	deploying	the	API-P	oller	onAWS	ECS	tofetch	data	from	various	API	sources,	transform	it,and	store	it	\ninto	S3before	pushing	ittoKinesis	for	further	processing.	\nOther	Responsibilites	:	\n	Taking	part	inDesigning	Data	Pipeline	\n	Modernizing	Data	Pipelines	\no	Earlier	we	were	using	AWS	Kinesis	for	our	Data	Streaming,	now	we	have	designed	the	pipeline	touse	Kafka	which	has	good	\nRetention	period	and	also	tomaintain	the	AWS	Cost	itwill	becheaper	than	Kinesis.	\n	Adding	Layer	for	Open-Telemetry	intoServerless	AWS	Lambda	tocapture	telemetry	data	for	Failure	Analysis	\n	Deploying	StateFullset	ElasticSearch	InKubernetes	\n	Streaming	Data	Processing	On	Apache	Beam	Pipeline	\nProject	2:	\nName	:Data	Platform	\nDesignation	:Automation	Developer	\nProject	Description	:Onclusive	isaMedia	Monitoring	Company.	Which,	monitors	the	Articles	,Content,	News,	Radio,	Youtube	and	also	TV	\nChannel.	Tofind	out	the	sentiment	for	the	particular	product	inmarket.	\nWhere	we	have	multiple	sources	who	pushes	Petabyte	ofdata	into	our	system	we	stream	that	into	MSK	Kafka	and	then	into	AWS	Kinesis	,using	\nBroadcast	pipeline	asaconsumer	we	fetch	itand	process	ittoElasticSearch.	\nAfterwards	this	used	for	sentiment	analysis	ofmarket	and	further,	using	API	this	Data	isfetch	and	given	toDown-Stream	Application	for	ML/AI	\npipeline.\nRole/Responsibility:	Worked	asaAutomation	Architect	\n	ToDevelop	API	Automation	Framework	based	onNodeJS-JavaScript.	\n	Inclusion	ofBDD	inNode-JS	Framework.	\n	Maintaining	Automation	Framework	asaQA	Engineer	for	allthe	In-scope	API	\n	Completing	Testing	using	Manual	Testcases	and	Automation	\nOther	Responsibilites	:	\n	Taking	part	inDesigning	Data	Pipeline	\n	Modernizing	Data	Pipelines	\no	Earlier	we	were	using	AWS	Kinesis	for	our	Data	Streaming,	now	we	have	designed	the	pipeline	touse	Kafka	which	has	good	\nRetention	period	and	also	tomaintain	the	AWS	Cost	itwill	becheaper	than	Kinesis.	\n	Adding	Layer	for	Open-Telemetry	intoServerless	AWS	Lambda	tocapture	telemetry	data	for	Failure	Analysis\n\nTSYS	:Project	Worked	On	\nProject	1:	\nName	:UCP	-Global	Payments	\nDesignation	:Automation	Developer	\nProject	Description	:	\nAsaglobal	payments	we	wants	our	Merchants	has	full	capabilities	toselect	their	transaction	gateway	asper	their	own	\nconvenience	sothat	they	can	decide	their	security	level	and	transaction	changes	asper	area	they	are	serving	.Asaresult	we	have	created	aGlobal	\nPlatform	when	Global	Payment	will	board	Merchants	onUnified	Platform	(Unified	Commerce	Platform)	that	itwill	gives	right	toMerchants	toselect	\ngateway	without	any	code	changes.	\nHere	we	asaGlobal	Payments	will	take	care	ofinternal	transformation	and	Merchant	just	need	toplug	out	APIs	and	start	\nplaying	the	business	without	worrying	about	their	internal	transaction	transformation.	\nProject	2:	\nName	:Propay	Enterprise	Integration	\nDesignation	:Automation	Developer	\nProject	Description	:	\nAsTSYS,	AGlobal	Payments	Company,	we	act	asamediator	between	payment	gateways,	platform	and	Merchant.	\nMindBody	asaclient	comes	toGlobal	Payments	with	ask	that	they	want	tomigrate	their	allMerchant	toPROPAY	platform.	We	GPAPI	handles	their	\nTransaction,	Merchant	Boarding	Requirement	and	other	POS	devices	requirement	within	Single	Request.	\nArchitecture	works	like	take	abase	request	from	Merchant(Mindbody	Merchant)	segregate	and	convert	that	request	into	required	request	form	\nDownstream	I.ePROPAY,	TransIT,	SoundPayment,	PAX	Portal,	Express.	Receive	the	response	and	send	ittomerchant.	\nAsnumber	ofFinancial	entities	comes	into	picture	with	this	project,	ithas	avery	huge	scope.	Itincludes	payment	processing	and	merchant	\nprocessing.\nRole/Responsibility:	\n	Asbeing	aintegral	part	ofEnterprise	Integration	Team	my	responsibilities	were	related	togather	and	understand	the	latest	\nchanges/requirements	for	the	Gateway	Release	.	\n	Write	functional	and	regression	test	cases.	Used	POSTMAN	for	API	Testing	\n	Execute	manually	functional	and	regression	pack,	manage	test	cases	inRally	\n	Raise	defect	and	communicate	with	developers	toresolve	it.	\n	Reporting	Bugs,	verifying	logs,	verifying	server-side	services,	verifying	data,	generating	SQL	scripts	for	Database	changes.	\n	Verify	other	dependent	systems	are	receiving	proper	transaction	message	and	help	them	for	payments	booking	scenarios.	\n	Create	and	Execute	Automat	ion	Test	Scripts,	inNodeJS	based	framework	inJavaScript	.	\n	Verify	API-Integration	working	asexpected	\n	API	Performance	testing	with	JMete	r	\n	Generating	Sign-off	report	with	notifying	that	everything	isworking	fine	with	allnew	changes,	sothat	allnew	requirements	should	be	\nlive	inproduction	inupcoming	bi-weekly	release.	\n	Handling	multiple	developers	overseas.	\n	Communicating	with	Dev-ops	team	tocheck	new	build-changes,	DB-changes,	services	side	changes.	\n	Experience	inworking	with	Agile	and	CI/CD	testing	Models	.	\nAltimetrik	:Projet	Worked	On	:	\nProject	:	\nName	:CitiBank	-High	Value	Payments	\nDesignation	:Quality	Engineer	\nProject	Description	:	\nFew	High	Valued	Customers	are	tied	up	with	CitiBank,	they	transact	huge	amount	ofmoney	per	Business	Day.	We	have	\ncreated	DashBoards	tokeep	atrack	ontheir	transactions	and	check	and	observe	what	isthe	status	for	that	payment	and	transactions,	Inthe	form	\nonGraphs	and	Tabular	Data	we	are	displaying	data	.	\nRoles/Responsibility	:	\n	Write	Test	Cases	For	various	Dash-Board	showing	different	Types	ofData	Analysis	for	Payments.	\n	Analyse	Requirement	From	JIRA/BRD/FRD	\n	DB	Testing	with	high	number	ofHigh	Valued	Payment	with	Different	Types	OfMOP	(Mode	OfPayments)	\n	UITesting	-Verify	Data	Calculation	and	computation	for	the	Data	from	DB	iscorrect.	\n	Functional	And	Regression	Testing.	\n	Create	UIAutomation	Framework	Based	onJava	Selenium	BDD	-Cucumber.\n\nCognizant	:Project	Worked	On:	\nProject	1:	\nName	:Global	Markets	(Global	Securities	Lending)-	Trade	Execution	and	Management	(Short	&ndash;Selling)	\nClient:	Credit	Suisse	\nProject	Type	:Functional	And	Automation	Testing	\nDuration:	24Sept	2018	toJan	2021	\nProject	Description:	\nCredit	Suisse	uses	anapplication	toBook	trades	for	Short	Selling.	Where	Borrow,	Loan	and	Collateral	Trades	were	booked	\nevery	day,	this	isavery	heavy	application	asitisused	bynumber	ofusers	allover	the	Globe.	\nRole/Responsibility:	\n	Togather	and	understand	the	latest	changes/requirements	for	the	release	from	Business	Requirement	Documents.	\n	Write	functional	and	regression	test	cases.	\n	Execute	manually	functional	and	regression	pack,	manage	test	cases	inQuality	Centre	-HP	ALM	\n	Raise	defect	and	communicate	with	developers	toresolve	it.	\n	Reporting	Bugs,	verifying	logs,	verifying	server-side	services,	verifying	data,	generating	SQL	scripts	for	Database	changes.	\n	Verify	other	dependent	systems	are	receiving	proper	trade	message	and	help	them	for	trade	booking	scenarios.	\n	Create	and	Execute	Automated	Test	Scripts,	and	verifying	results.	\n	Verify	API-Integration	working	asexpected	\n	API	Performance	testing	with	JMete	r	\n	Generating	Sign-off	report	with	notifying	that	everything	isworking	fine	with	allnew	changes,	sothat	allnew	requirements	should	be	\nlive	inproduction	inupcoming	bi-weekly	release.	\n	Taken	initiative	toenhance	automation	ofWeb	Based	Application	using	Selenium	WebDriver	with	IDE	Eclipse	.		Handling	multiple	developers	overseas.	\n	Communicating	with	Dev-ops	team	tocheck	new	build-changes,	DB-changes,	services	side	changes.	\n	Experience	inworking	with	Agile	and	CI/CD	testing	Models	.	\nProject	2:	\nName	:Security	Financing	Transaction	Regulation	\nClient:	Credit	Suisse	\nProject	Type	:Functional	Testing	\nDuration:	Jan	2020	toJan	2021	\nProject	Description:	\nThis	isaglobal	change	where	every	Investment	Bank,	needs	toreport	their	allEurope	based	transaction,	tothe	certain	\nReporting	Entity.	\nRole/Responsibility:	\n	Togather	and	understand	the	change	from	Business	Requirement	Documents.	\n	Write	functional	and	regression	test	cases.	\n	Execute	manually	functional	and	regression	pack.	\n	Raise	defect	and	communicate	with	developers	toresolve	it.	\n	Verifying	logs,	verifying	server-side	services,	verifying	data,	generating	SQL	scripts	for	Database	testing.	\n	Verify	other	dependent	systems	are	receiving	proper	trade	message	and	help	them	for	trade	booking	scenarios.	\nProject	3:	\nName:	Fixed	Income	Securities	\nClient:	Credit	Suisse	\nProject	Type:	Functional	Testing/API	Testing	\nDuration:	March	2020	toMay	2020	\nProject	Description:	\nFixed	Income	securities	tobeimplemented	for	certain	Client/Counterparties	with	specified	entity	directions,	\nFor	that	combination	ofClient	and	Fixed	Income	Securities	system	calculating	rate	and	fetching	them	from	API	end	point.\n\nRole/Responsibility:	\n	Togather	and	understand	the	changes.	\n	Verify	API-Integration	working	asexpected.	\n	Write	and	execute	manual	and	regression	pack.	\n	Verify	logs,	DB	testing	reporting	defect	\n	Performance	testing	for	API	with	JMeter	.	\nAcademic	Details:	\nSr.No	Qualification	University/Board	Passing	Year	Percentage	\n1.	Executive	PDGM	MIT	SDE	2022	Grade	A	\n2.	Bachelor	inComputer	Application	Amravati	University	2017	68%	\n3.	HSC	Maharashtra	State	Board	2014	62.46%	\n4.	SSC	Maharashtra	State	Board	2012	82.55%	\nOther	Qualification	Details:	\nSerialNo.	Qualification	University	/Board	Passing	Year	Percentage	\n1.	Eng-Typing	30	Maharashtra	State	Council	ofExamination,	Pune	Dec-2012	65%	\n2.	Eng-Typing	40	Maharashtra	State	Council	ofExamination,	Pune	Dec-2012	51%	\n3.	MS-CIT	Maharashtra	State	Board	OfTechnical	Education,Mumbai	July-2010	92%	\nSelf-Learning	Project:\n	Project	1:Text	files	reader.	(Text	tospeech).	(Using	python	and	GTTS	library)		Project	2:QR	code	generator	(Using	Python)		Project	3:Speech	totext	(Using	Python	and	Google	Speech	Recognition	Library)	\nAchievement:	\n	Awarded	as&ldquo;Pillar	OfThe	Month	&ldquo;(Cognizant	May	2019)		Best	&ldquo;Student	ofYear	&rdquo;(CMCS	2017)	\nPersonal	Details:	\nName:	Bhushan	Ashokrao	Bende	Dob:	18/01/1996	Permanent	Address:	Old	Gilani	Nagar,	Yavatmal	445001	Maharashtra	Current	Address:	Venkat-Padmavati	PGbehind	Persistent,	Hinjewadi	,411057	Pune	Strength:	Good	Communication,	Quick	learner	Hobby:	Cooking,	Gardening	Languages	known:	English,	Marathi,	Hindi	\nMobile	+91	9405708908	\nEmail:	Primary:	bhushanyahoo@gmail.com	\nDeclaration:	Ihereby	declare	that	the	above	information	istrue	tothe	best	ofmy	knowledge	and	allnecessary	documents	will	beprovided	as&amp;	\nwhen	required.	\nSignature:	Bhushan	Ashokrao	Bende	\nDate:	Place:	Pune', 2, 2, 1, 'Recruiter', NULL, 'N', NULL, 0, NULL, NULL, 0, NULL, NULL, '2024-07-17 06:38:17', 0),
(375, 91, 73, 42, NULL, '73_91_177430066066976972d99cf_Ajay_Chaudhari_-_HMI_Developer.pdf', 'Ajay Chaudhari - HMI Developer.pdf', '/  	\nA JAY  C H AU DH ARI\nSoft w are  D eve lo p er	\narc h au d hari1 4 0 2@ gm ail. c o m	h ttp s:/ /w ww.lin ke d in .c o m /in /a ja y -\nc h au d hari- 0 15 6 ba16 9/	\nK an ag aw a, J a p an	\nS U M MARY\nExp erie n ce d  S oft w are  D eve lo p er w it h  o ve r 4 .3  y e ars  s p ecia liz in g  in  A nd ro id -\nbase d  A uto m otiv e  In fo ta in m en t s y ste m s 	 \n 	\nP ostg re S Q L,  a n d  O doo.  I  a m  e ag er t o  c o lla b ora te  o n a d va n cin g  c u ttin g -e d ge	 	\nte ch no lo g y a n d  d eliv e rin g  e xc e p tio nal  r e su lt s .\nE X PER IE N CE\nOnsit e  D eve lo p m en t E ngin eer\nTata  C on su lt a n cy S erv ic e s L td	\n0 5/2 0 24	&nbsp;	K an ag aw a,  J a p an	\nA ssig ned  F e atu re :  R ad io  	 	\nR ad io ,  P od ca st)\nO nsit e  S PO C f o r R ad io  f e atu re ,  C lie n t c o m mun ic a tio n,  M an ag e S O P /  Q LU	 	\n/ M ain lin e d eliv e rie s f o r N is sa n  V eh ic le s,  B ug  t r ia g in g  a n d  f ix in g\nW ork in g  w it h  c ro ss-fu n ctio nal  t e am s s u ch  a s X peri,   L G ,  G oog le ,  B osc h ,	 	\netc .\nT e ch S ta ck:  A nd ro id ,  K otlin ,  J a va ,  A O SP,  A ASP	\nS yste m s E ngin eer\nTata  C on su lt a n cy S erv ic e s L td	\n0 1/2 0 22 	&nbsp;	G an d hin ag ar,  In d ia	\nN is sa n  IV I  f e atu re s:  T e le m atic s 	 	\nC onnm an  \nF i,   a n d  H ots p ot).\nH M I  d eve lo p m en t t h at w ork s w it h  A O SP a n d  H AL p ro vid ed  b y L G  a n d	 	\nB osc h ,  f e atu rin g  1 0 0\nB uilt  p yth o n s c rip t t h at r e d uce d  S ST R g en era tio n t im e b y 8 0 %\nTe ch S ta ck:  A nd ro id ,  K otlin ,  J a va	\nJ r. A pplic atio n  E ngin eer\nTin yE R P P vt. L td	\n1 0 /2 0 20  	&nbsp;	A hm ed ab ad ,  In d ia	\nO doo:  E R P B usin ess S uit e  o f o p en -s o urc e  b usin ess a p ps c o ve rin g  C RM ,	 	\neC om merc e ,  A cco un tin g ,  In ve n to ry ,  P O S e tc\nD eve lo p m en t o f c u sto m  m od ule s a s p er c lie n ts &#039;  n eed s.  A ddre sse d  m ain ly	 	\ng en eric  &amp;  s p ecif ic  is su e s d urin g  d ata b ase  u p gra d es.  1  g en eric  f ix  c a n	 	\nre so lv e  r o ug hly  1 0  C lie n ts  d ata b ase  u p gra d e is su e s\nTe ch S ta ck:  P yth o n,  P ostg re sq l,   J S ,  U bun tu	\nP yth on /O doo D eve lo p er\nBro w se ln fo  P vt. L td	\n0 3 /2 0 20  	&nbsp;	A hm ed ab ad ,  In d ia	\nD eve lo p ed  C usto m  L ib ra ry  m an ag em en t O doo A pp,  P ro d uct Q ualit y	 	\nA ssu ra n ce  A pp u sin g  g en eric  m od ule s\nC ontr ib ute d  t o  e xis tin g  O doo A pps lik e  B atc h  P ay m en t d urin g  in vo ic in g\nTe ch S ta ck:  P yth o n,  J S ,  O doo	\nE D U CATIO N\nBach elo r o f E ngin eerin g\nSA L E n g in eerin g  A nd  T e ch nic al I n stit u te , G TU	\n04 /2 0 17  	&nbsp;	A hm ed ab ad ,  In d ia	\nGP A	\n8.2 7	10	\nC om pute r E ng in eerin g  M ajo r	\nS KIL LS\nTe ch S ta ck\nA nd ro id	J av a	K otlin	P yth on	\nO doo	P ostg re sq l	M atp lo tL ib	\nN um py	O pen C V	Pan d as	S eab orn	\nS kle arn	G it	\nT e ch nic al  E xp ert is e\nA uto m otiv e  I n fo ta in m en t f o r C CS\nER P S oft w are  	M ac h in e L e arn in g	\nP R O JEC TS\nAuto m atic  A tte n dan ce  S yste m	\nhttp s:/ /g it h ub .c o m /A jja rv is /A uto m atic _A tte n d an ce _S\ny ste m	\nF ace  R eco g nit io n-b ase d  A uto m atic  A tte n d an ce	 	\nS yste m  u sin g  C CTV  f o r r e al- tim e s tu d en t	 	\natte n d an ce .	\nTe ch S ta ck:  P yth o n,  T kin te r,  X lr d ,  X ls x w rit e r,	 	\nO pen C v	\nIn diM on ey : A n E xp en se  T ra cke r A pp	\nhttp s:/ /g it h ub .c o m /A jja rv is /In d iM oney	\nA nd ro id  E xp en se  T ra cke r A pp f o r e ffic ie n tly	 	\nm onit o rin g  o f e xp en se  a n d  in co m e w it h  le ss e ffo rts	\nT e ch S ta ck:  A nd ro id ,  S Q Lit e ,  G oog le  M L k it	\nA C H IE V EM EN TS	\nPala d in  o f t h e I V IT  C ham pio n s\nRece iv e d  b eca u se  o f h ig h p erfo rm an ce  o n	 	\ncrit ic a l  p hase  o f t h e p ro je ct\nD ig it a l M ile sto n e a t T C S\nCle are d  c o d in g  c h alle n g es in  P yth o n a n d	 	\nd em onstr a te d  c o m pete n cie s in  A gile	 	\nm eth o d olo g y.\nIn nova to r M ile sto n e a t T C S\nCle are d  c o d in g  c h alle n g e o n M ach in e	 	\nLe arn in g	\nwww .enhancv .com	\n	\nPow er ed b y	\nE		q	\n\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;	\n&bull;\n&bull;\n&amp;\n\n', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-21 14:32:36', '2024-07-18 14:32:36', 0, NULL, NULL, '2024-07-17 06:49:22', 0),
(376, 91, 73, 36, NULL, '73_91_135311370066976972d9bda_Arjun_V_Menon_-_HMI_Developer.pdf', 'Arjun V Menon - HMI Developer.pdf', '. \n. \n 	 	\nARJUN V MENON	 	\nSoftware Engineer 	 	\n +91 9744816460	  	\n\ncom	 	 	\n https://www.linkedin.co\nm/in/arjun	-menon	-	\n937159141/	 	 	\n 	\n 	\nAn  inspired  android  developer  dedicated  to  continuously  developing, \nimplementing,  and  adopting  new  technologies  to  maximize  development \nefficiency  and  produce  innovative  applications.  I  have  a  total  technical \nexperience of more than 4 years &amp; passionate to	wards solving problems. 	 	\n \n 	Skills	 	\n Native Android Development ( Java , Kotlin) 	 	 \n JSON, RESTful web services. 	 	 \n Retrofit, Volley, Coroutines. 	 	 \n SQL Lite, Room DB, MySql, Shared Preferences. 	 	 \n Markup language (XML). 	 	 \n Version Control (Git, Bitbuket, SVN, Gerrit). 	 	 \n Project Management (Jira, Jenkins, Polarion, Confluence). 	 	 \n AOSP 	 	 \n Android HMI 	 	 	 	\n 	\nWork History	 	\n Senior Software Enginner	 	\nTata Elxsi, Bangalore	 	\n Worked on Android Map application using Mapbox for automotive 	 	\n Worked on Telematics CV2X project, In Android Telematics Service \nApplication. 	 	\n Testing and Debugging on Hardware for Android Telematics. 	 	\n Worked on Android HMI for Launcher App. 	 	\n Skills: Jira 	- Confluence 	- Polarion 	- Gerrit 	- AOSP 	- BinderIPC 	- Android 	\nFramework 	- Java 	- Mqtt 	- AIDL 	 	\n Programmer Analyst	 	\nCognizant, Bangalore	 	\n Worked on Google Play Protect Project. 	 	\n Worked on android security and android reverse engineering. 	 	\n Worked on Identifying security threats and malware in Playstore. 	 	\n Worked Android Malware analysis. 	 	\n Skills: Jira 	- Android Studio 	- Reverse Engineering 	- Java 	- Kotlin 	 	\n 	\n2022	-11 	- Current	 	\n2021	-09 	- 2022	-11	 	\narjunvenumenon@gmail.\n\n. \n. 	\n Software Engineer	 	\nQuest Global, Trivandrum	 	\n Software development in Android Automotive HMI 	 	\n Worked on Phonebook team of HMI, Version control using SVN. 	 	\n Developed features for Phonebook and Contacts of HMI. 	 	\n Testing and debugging of Build in Hardware. 	 	\n Skills: Jira 	- Gerrit 	- AOSP 	- BinderIPC 	- Android Studio 	- AIDL 	 	\n Software Engineer	 	\nAutocon India Pvt. Ltd, Kochi	 	\n Developed new features for proprietary Android applications used on \nphones and tablets; worked with developers to develop toptier solutions \nfor restaurant and retail customers 	 	\n Uses Coroutines for long	-running tasks (database and network access) 	 	\n Maintaine	d long and short	-range deliverables with product 	\nmanagement team according to product roadmaps 	 	\n Created custom mobile applications using native technologies 	 	\n Database access through Room persistence library. 	 	\n Android Developer	 	\nTradeasy Technologies, Kannur	 	\n Created custom mobile applications for retail customers 	 	\n Documented architecture and implementation for internal and external \nconsumption 	 	\n Applied various techniques to locate bugs and errors in applications 	 	\n Designed and built sales applications for Android platform 	 	\n Provided dedicated support and timely issue resolution to clients \nfollowing successful app launch. 	 	 	\n 	\nEducation	 	\n B-tech: 	Electronics And Communication Engineering	 	\nKannur 	University 	- Kannur	 	\nPercentage: 63 	 	\n 12th: 	Science	 	\nChapparapadava HSS 	- Kannur	 	\nPercentage: 70% 	 	\n 10th Std	 	\nChapparapadava HSS 	- Kannur	 	\nPercentage: 85% 	 	 	\n 	\nAccomplishments	 	\n  Conducted Android App Development workshops in various colleges 	 	\n Participated in workshop on Internet of Things by Innovians Technologies 	 	\n Participated in Cannovation 2018 startup exhibition of Kannur University 	 	\n 	 	 	\n. 	\n2021	-04 	- 2021	-09	 	\n2020	-08 	- 2021	-04	 	\n2019	-03 	- 2020	-08	 	\n2014	-07 	- 2018	-05	 	\n2011	-06 	- 2013	-03	 	\n2010	-06 	- 2011	-03', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-08-07 17:14:06', '2024-08-04 17:14:06', 0, NULL, NULL, '2024-07-17 06:49:22', 0),
(377, 91, 73, 40, NULL, '73_91_89661268866976972d9da4_Gowtham_Mohanraj_HMI_Developer_Resume_1_(1).pdf', 'Gowtham    Mohanraj HMI Developer Resume 1 (1).pdf', 'ED U C ATIO N\nG OW TH AM  SA SSIS TA N T M AN AG ER	 	C O NTA C T+91 6 383311446go w tth am s6 @ gm ail.c o m ch en naiS K IL LS	Pro je ct M an ag e m en t	 	\nT eam work\nT im e M an ag e m en t\nLe ad ers h ip\nE ffe ctiv e  C om mun ic a tio n\nC rit ic a l  T hin kin g	\nV ELA LA R C O LLE G E O F\nEN GIN EER IN G A N D T EC H NO LO GY\nEle ctr o nic s &amp;  C om mun ic a tio n -  7 5%2 010  -  2 01 32009PO NNU M ATR IC U LA TIO N H R S E C\nSC H O OL\nHig h er s e co nd ary  e d uca tio n -  8 5%W ORK  E X PER IE N CEPR O JE C TS	 	P R O FIL EDyn am ic   an d  in no vativ e   in fo ta in m en t  sy ste m  exp ert  w it h  o ve r  4  ye ars   o f\nexp erie n ce   in   deve lo pin g  an d   im ple m en tin g  cu ttin g-e d ge   in   au to m otiv e\nin d ustr y  a n d  in fo rm atio n s y ste m s.  O ve r a ll  1 0 y e ars  o f e xp erie n ce  in  S o ft w are\nin d ustr y .  P ro ve n  a b ili t y  to  le ad  c ro ss-fu n ctio nal  te am s  a n d  m an ag e  p ro je cts\nfr o m  co nce p t  to   co m ple tio n,  en su rin g  se am le ss  in te gra tio n  of  m ult im ed ia ,\nn av ig atio n,  an d   co nnectiv it y   fe atu re s.  Adep t  at  le ve ra g in g  ad van ce d\nte ch no lo gie s t o  e n han ce  u se r e xp erie n ce  a n d  d riv e  m ark e t c o m petit iv e n ess.\n2 023 -  P R ESE N TM on tr a  - T I c le an  m ob il it y  p riv ate  l im it e dA ssis ta n t m an ag er	 	\nP ro d uct d eve lo p m en t &amp;  R eq uir e m en ts  h an d lin g	  -  C en tr a l R &amp; D	The  cre atio n   an d   exe cu tio n   of  m an ual  te st  ca se s  fo r  all  m od ule s  an d\nap plic a tio n s o f v e h ic le  t e le m atic s.\nT he c re atio n  o f  v e h ic le  a le rts  a n d  in fo rm atio n  th ro u g h th e te le m atic s c lo u d\nfo r m ob il e  a p plic a tio n s a n d  O EM .\nFu n ctio n al  a n d  in te g ra tio n  te stin g  o f  a p plic a tio n  fe atu re s a t  b oth  th e te st\nb en ch  a n d  v e h ic le  l e ve ls  u sin g  a  C AN  A naly ze r.\nC usto m iz in g  th e te le m atic s d ash b oard  a n d  m an ag in g  it   a cco rd in g  to  re al-\nt im e f ie ld  i s su es a n d  s e rv ic e  r e q uir e m en ts .\nD eve lo p m en t  te stin g  o f  v e h ic le  fe atu re s s u ch  a s g eo fe n cin g ,  liv e  tr a ckin g ,\nan d  v e h ic le  a le rts  a n d  A nd ro id  d eve lo p m en t i n  i n fo ta in m en t s y ste m .\nTele m atic s p erfo rm an ce  a n aly sis  t h ro u g h v a rio u s c o m petit iv e  b en ch m ark in g .\nSu p port t h e v e n d or s e le ctio n  p ro ce ss a n d  m an ag e v e n d ors  t o  e n su re  t im ely\nd eliv e ry  a n d  t h e r e q uir e d  q ualit y .\nG ood  k n ow le d ge a n d  u n d ers ta n d in g  o f  E V  a rc h it e ctu re  w it h  m ult ip le  C AN\nnetw ork s i n  t h e v e h ic le .\nP re p ara tio n   of  8D  re p orts   in   co ord in atio n   w it h   pro d uctio n   an d   cro ss-\nfu n ctio n al t e am s t o  s o lv e  c rit ic a l q ualit y  i s su es.\nE xp ertis e  i n  p re p arin g  S co p e o f R eq uir e m en ts  d ocu m en ts .\nT eam  s iz e  :  2\nI n it ia tin g  a n d  im ple m en tin g  U D S p ro to co l  a cro ss  a ll  ve h ic le  d ow nstr e am\nE C Us, c o n sid erin g  a ll a sp ects  a n d  v e rtic e s.\nS u p portin g  t h e d eve lo p m en t o f a  s in g le  c lo u d  p la tfo rm  f o r v a rio u s t e le m atic s\nu n it s .\nA ctiv e ly  in vo lv e d  in  t h e im ple m en ta tio n  a n d  v a lid atio n  o f	  t e le m atic s f e atu re s	\nsu ch  a s :\n D eep  l o g ger -	  V erif ic a tio n  a n d  v a lid atio n  o f e ach  v e h ic le  d ata  p oin t.	1.\n D eep  u p d ate r -	  D eve lo p m en t o f U D S p ro to co l i n  a ll E C Us t o  s u p port	\nF ir m ware  O ve r-T he-A ir  	(F O TA	) u p d ate s.	\n2.\nD eep  c o m man d er -  D eve lo p m en t o f v e h ic le  I m m ob il iz a tio n  s y ste m s.	3.	\nT O OLS	 	CA N oe\nC A N an aly ze r\nB us M aste r\nP -C A N\nJT A G\n\nDoco m o I n te rto u ch  I n d ia  L td  ,  B an g alo re , I n d ia	 	IT  S u p port E n g in eer	M S O utlo ok c o n fig ura tio n , b acku p  ,  r e sto re  a n d  t r o u b le sh ootin g .\nM an ag e D om ain  e n vir o n m en t f o r t w o s it e s t h ro u g h r e m ote  s u p port.\nW ir e le ss n etw ork in g  i n  D om ain  e n vir o n m en t.\nA sse m blin g , h ard w are  u p  g ra d atio n  a n d  t r o u b le sh ootin g .\nPro vid in g  s u p port t o  i n sta llin g  O S f o r t h e u se r m ach in es a n d  s e rv e rs .	\n G em alt o  M id dle  E ast F Z  L LC , D ub ai, U .A .E	                              	2 016 - 2 020	 	 2013- 2 016	 	IS S/N etw ork  a n d  S u p port E n g in eer	R esp on sib le   fo r	   	LA N  an d  W AN  n etw ork   op era tio n s,  sy ste m  d is a ste r	\nre co ve ry ,  data b ase   an d   sy ste m  backu p ,  Pla ye d   ke y  ro le   in   backu p\nm an ag em en t o f I T  d ep artm en t.\nC IS C O   :  Rou te rs ,  Sw it c h es,  Serv e r,  wir e le ss  devic e s,  an d   Acce ss\nte ch nolo g ie s.\nS tr o n g  t r o u b le sh ootin g  s k il ls  o n  L A N , W AN  a n d  W ir e le ss t e ch nolo g ie s.\nM an ag ed  u se r a cco u n ts  w it h  ( A D ) A ctiv e  D ir e cto ry  f o r t h e u se rs  t o  p ro vid e\ncre atio n ,  d ele tio n ,  u se r p erm is sio n  a n d  m an ag ed  u se r s e cu rit y  w it h  g ro u p\np olic ie s\nG ood  e xp erie n ce  i n  i n sta llin g  a n d  m ain ta in in g  t h e v ir tu al w ork sta tio n s	\n        	( E 2C )\nH an d lin g  P K I a n d  V PN  b ase d  s e cu rit y  i s su es.  p erfo rm  t r o u b le sh ootin g  e n d -\nto -e n d  b etw een  t h e s it e s.  P ro vid in g  t r a in in g  fo r t h e u se rs  t o  c o n fig ure  t h e\nce rtif ic a te  a n d  s e cu re  d om ain  w it h  t w o f a cto r a u th en tic a tio n .\nP erfo rm in g   Reg is tr a tio n   an d   Auth orit y   dutie s  to   in clu d e  ce rtif ic a te\ne n ro lm en t a n d  r e vo ca tio n .\nM an ag ed  A cce ss C on tr o l  S yste m  to  m ain ta in  a ll  th e b ad ges o f  u se rs  a n d\nvis it o rs .  T o p ro vid e p erm is sio n s fo r  th e re co m men d ed  d ep ortm en t  a n d\nse cu re d  a re a.\nIn sta llin g  G em alt o  B om gar  a p plic a tio n  fo r  a ll  th e m ach in es in  p ro d uctio n\nare a.	\nK in g sto n  I n fo  s o lu tio n s,B an g alo re .	                                       	2 020 -	  2 023	            	\n        \n       	 T est E n g in eer	\n 	\nperfo rm in g  v a lid atio n  o n  i n fo ta in m en t f e atu re s i n  a ll p ossib le  c o n d it io n s.\nV alid atin g  d if fe re n t m od ule s l ik e  U SB ,F M ,H M I a n d  P hon e	 	\nP erfo rm in g  th e ra p id  v a lid atio n  te sts   fo r  a ll  te st  c o n d it io n s  a n d  in va lid\nc a se s	 	\nP re p arin g  s o ft w are  v a lid atio n  s ta tu s r e p ort .\nD eve lo p m en t a n d  v a lid atio n  o f i n te g ra te d  T ele m atic s a n d  C lu ste r.	\n 	\nI h ave  a ctiv e ly  in it ia te d  a n d  d eve lo p ed  F O TA  im ple m en ta tio n  in  3 W  ( L 5 M ,\nL5 N ),  T ra cto r,  S C V,  a n d  H CV.  S u cce ssfu lly ,  I  h ave  g iv e n  a  d em o w it h  t w o\nve rtic e s.	 	\nI p ro p ose d  F O TA  e n tr y -le ve l c o n d it io n s a n d  c h ecklis ts  b ase d  o n  i n d iv id ual\nE C U a n d  v e h ic le  b eh avio u r,  e n su rin g  n o im pact o n  t h e e n d  c u sto m er a n d\nm ain ta in in g  v e h ic le  p erfo rm an ce .	\nL A N G UAG ES	Engli s h	 	\nIE LT S w it h  b an d  6\nT am il	 	\nS TA C K H O LD ER S	Sib ro s ,  N esh  ,  C onnectm  ,\nP ric o l  ,  E le ctr o nik a ,  A W EV ,\nSo na C om sta r ,E xid e	 	\n      \nO TH ER  I N FO	Passp o rt n o  - K 2849988	 	\nH obbie s - S ke tc h in g &amp;\nG ard en in g	 	\nT han ks	 	G O W TH AM  S A KTH IV EL	,  C hen nai,  2 4 J u n e 2 024', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, '2024-07-21 09:14:48', '2024-07-18 09:14:48', 0, NULL, NULL, '2024-07-17 06:49:22', 0);
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(378, 91, 73, 33, NULL, '73_91_161939989266976972da127_HMI_Developer-Shailendra_Semwal.docx', 'HMI Developer-Shailendra Semwal.docx', '\r\nShailendra Semwal\r\n# 3047 Janapriya Havens\r\nYalanka, Bangalore-560065)\r\n✉E-mail Id  shailendarsemwal@gmail.com☎Contact No +91-8548074898\r\n  LinkedIn: https://www.linkedin.com/in/shailendrasemwalCareer Objective:\r\nTo work with maximum potential in a challenging and dynamic environment, with an opportunity of working with diverse group of people and enhancing my professional skills with learning and experience for career growth.\r\nExperience Summary:\r\nWith 8 years of experience in Android Application Development, Android Automotive, and AMS Engineering Application Support, I bring a wealth of expertise to my roles. I have working navigation systems for Scania trucks, kitchen management apps for restaurant chains, and provided critical support for engineering applications at Black &amp;amp; Veatch.\r\nTechnical Skills:\r\nTools &ndash; Git SVN, ADB tools, QFIL Tools, AOSP\r\nLanguage &ndash;  JAVA, Kotlin, Java(Android SDK)\r\nDatabase &ndash; SQLite, MySQL.\r\nTechnology &ndash; Android,AOSPOperating System &ndash; Windows, Mac,LinexIDE &ndash;Android Studio, Eclipse,Microsoft PowerBITicketing Tools- ServiceNow, Jira, Conference, Figma\r\nAreas Of Expertise:\r\n&bull;    Familiar with the Android SDK, Eclipse, Google services and APIs.\r\n&bull;    Knowledge of SQLite, MySQL or Oracle database management system.\r\n&bull;    Proficient in design, problem-solving, and debugging.\r\n&bull;    Proficient with Developer Console in publishing and managing the application.\r\n&bull;    Knowledge in integrating web services, TCP and UDP socket programming.\r\n&bull;    Familiarity with HERE SDK Navigation. \r\n&bull;    Knowledge of Android AOSP Automotive ROM  Development.\r\n&bull;    Knowledge of Android build system.\r\n&bull;    Knowledge of Android boot process Deep Analysis.\r\n&bull;    Knowledge of Car Api, Car Services, VHAL.\r\n&bull;    Knowledge of Car Launcher.\r\n&bull;    Knowledge of Boot Animation.\r\n&bull;    Knowledge of SELinux.\r\n&bull;    Knowledge of Car Settings.\r\n&bull;    Knowledge of System UI.\r\n&bull;    Knowledge of Mobile Penetration Testing of Android Application.\r\nOrganization Experience\r\nEmployer :  L&amp;amp;T Technology Services Ltd\r\nDuration : March 2021 &ndash; Till now\r\nDesignation : Senior Engineer(Android  Developer)\r\n Project Name: -Navigation\r\nClient: Scania \r\nAs part of our Android automotive project, we are developing a navigation app specifically tailored for Scania trucks. This app aims to provide Scania truck drivers with reliable and efficient navigation assistance to optimize their driving experience. Our focus is on creating a user-friendly interface that takes into account the unique requirements of truck drivers, such as vehicle dimensions, weight restrictions, and specific road regulations. The navigation features will include truck-specific routing options, real-time traffic updates, and points of interest relevant to truck drivers, such as rest areas and truck stops. To ensure seamless integration with Scania trucks, we are collaborating closely with the client to understand their specific needs and requirements. Our development process involves leveraging the latest technologies and best practices in Android automotive development to deliver a high-quality and robust navigation solution. By working closely with Scania and leveraging our expertise in Android development, we aim to create a navigation app that enhances the driving experience for Scania truck drivers, improving efficiency and safety on the road. \r\nDDU,RIG,QFIL Tools, AOSP, Gadget Testing, HERE SDK, JIRA, Figma, Coverity static analysis.\r\nEmployer :  Barbeque Nation Hospitality Ltd\r\nDuration : August2020 &ndash; Till now\r\nDesignation : Assistant Manager(Android  Developer)\r\nProject Name:-KDS:( Hospitality Management)\r\nhttps://play.google.com/store/apps/details?id=com.bbqn.relayProject based on Hospitality Management.\r\nProject Name:- Samiksha:( ERP)\r\nhttps://play.google.com/store/apps/details?id=com.app.bbqn.samikshaEmployer :  DFoE (Digital Future of Education Pvt. Ltd.)\r\nDuration : February 2020 &ndash; August2020\r\nDesignation : Android  Research Engineer\r\nProject Name:-FRI:( Hospitality Management)\r\nhttps://play.google.com/store/apps/details?id=com.dfoe.friclienthttps://play.google.com/store/apps/details?id=com.dfoe.frimasterhttps://play.google.com/store/apps/details?id=com.dfoe.frikitchenTechnologies used:&nbsp; JSON, REST, TCP and UDP Socket Programming, SQLite Db.\r\nProject based on Hospitality Management.\r\nPayment Gateway integration using Stripe Payment, PayU.\r\ncommunication protocols Socket.\r\nOrganization Experience\r\nEmployer : Ayshwarya syndicate LLP, Bangalore\r\nDuration :August 2019 &ndash; November 2019\r\nDesignation :Software Developer\r\nProject Name:-Spark IN:\r\nhttps://play.google.com/store/apps/details?id=com.assccl.spark.coopProject based on Banking Consumer Account.\r\nPush notification is implemented using Google Firebase.\r\nPayment Gateway integration using Paytm, Razor pay;\r\nImplemented finger print access security and Device lock security.\r\nHere customer can create Health Insurance, Debit and Credit Cards, Bill Payment.\r\nEmployer :  Technoforte Software (p) Ltd\r\nDuration :  August  2018 &ndash; August  2019\r\nDesignation : Associate Engineer -Software. \r\nClient: Toyota\r\nProject Name:- Polygon:\r\nManufacturer of inventory management &amp;amp; parts tracking systems for real-time inventory control    &amp;amp; tracking serial number, date tracking, trace the movement of materials.\r\nAn Integrated ZebraBarCode scanner, library to scan the barcode.\r\nDesigned the database, UI pattern, data-flow between different modules.\r\nTesting the end to end app, database &amp;amp; web-services.\r\nEmployer : Pronto Software Solutions (p) Ltd, Bangalore\r\nDuration :  November 2016 &ndash; August 2018\r\nDesignation : Associate Software Engineer\r\nProject Name:- Sangama:\r\nClient: Karnataka Forest Department - Belagavi Circle.\r\nhttps://play.google.com/store/apps/details?id=com.pronto.sangamaSangama is an application which is designed to help the officers monitor and Update their work status online/offline.Key Features of the app are as follows: \r\nProject Name:- Cricket Score Pad:\r\nhttps://play.google.com/store/apps/details?id=com.pronto.scorepadCricket Score Pad comes closest to the cricket score card you have filled manually all this years. A scorer&rsquo;s delight, Cricket Score Pad&#039;s neat, clean and intuitive design ensures the cricket score book stays upto-the-ball without you breaking a sweat. Use Cricket Score Pad to score multiple match formats (T20 or ODI) or even custom make your own match.\r\nDesign UI pattern &amp;amp; database.\r\nIdentify and correct fix bugs\r\nEmployer : SPH Vibhava Private (p) Ltd, Bangalore\r\nDuration :  April 2016 &ndash; October 2016\r\nDesignation : Software  Developer\r\nProject Name:- SmartPropertyHunt:\r\nCertified Course\r\n4  month Java &amp;amp; Testing Training In &ldquo;ABC For java &amp;amp; Testing&rdquo; in Bangalore\r\n4 month .Net Technology Training in DUCAT Gwalior.\r\n5 month  C,C++,Core Java Training In GLOBAL ICS Delhi\r\n2 Month  Android Training in Falgee Software Development Pvt Ltd Bangalore.\r\nAcademic Background\r\nYear(s) Qualification  Board/University College/ Institute Percentage\r\n2015  Bachelor of Engineering \r\n(Information Technology) Rajiv Gandhi Proudyogiki   Vishwavidyalaya Bhopal\r\n(Madhya Pradesh)\r\nRustamji Institute of  Technology  BSF Academy Tekanpur Gwalior \r\n(Madhya Pradesh)\r\n 7.75 CGPA \r\n2012           Diploma\r\n(Computer Engineering)\r\nBoard Of Technical Education Delhi(B.T.E) BSF Polytechnic STS \r\nTigri Camp, New Delhi    68.00%\r\nPersonal Details Name : Shailendra Semwal\r\nFather&rsquo;s Name : Prakash Chandra Semwal\r\nMother&rsquo;s Name : Prabha Devi Semwal\r\nDate of birth : 06/11/1992\r\nNationality : Indian\r\nLanguages known : English, Hindi (read, write and speak)\r\nPermanent Address : Tehri Garhwal Uttarakhand \r\nDeclaration I do hereby confirm that the details furnished above are true to the best of my knowledge. I bear the responsibility for the correctness of the above-mentioned particulars.\r\nPlace: Bengaluru\r\nDate: (Shailendra Semwal)\r\n', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, '2024-07-20 07:24:54', '2024-07-17 07:24:54', 0, NULL, NULL, '2024-07-17 06:49:22', 0),
(379, 91, 73, 38, NULL, '73_91_208471020366976972da32d_HMI_Developer-Swapnil_Thamake.pdf', 'HMI Developer-Swapnil_Thamake.pdf', 'Sw ap nil  T h am ake  \nTe am  L e ad  \n                                             \nap plic a tio n i m pro ve m en ts . C urre n t p ro je ct w ork in g  o n F o rd  C re d it  ( ﬁ nte ch ) a n d  L a st p ro je ct w as w ork e d\n                                       \nsw ap 3848@ gm ail .c o m  \n\nPune, I n d ia  \nlin ke d in .c o m /in /s w ap nil - t h am ake -2 14314a0  \nWORK  E X PER IE N CE \nTe am  L e ad  \nTe ch  M ah in d ra  \n04/2 022 -  P re se n t\n, \n  Pun e \nFo rd  C re d it  A pplic a tio n : ( F in te ch ) \nLe ad in g  t o  m y 2  b ud dy&#039;s  a n d  d eve lo pin g  M obil e  A pplic a tio n\nis  b ase d  o n ﬁ nan cia l a n d  a cco unt m an ag em en t s e rv ic e s \nUse  s k il ls  C ode o ptim iz a tio n, A pplic a tio n s e cu rit y , d esig n\npatte rn s a n d  r e so lv e  l o w  p erfo rm an ce  i s su es. \n                 \n           \nAsso cia te  C onsu lt a n t \nCap gem in i I n d ia  \n02/2 020 -  0 4/2 022\n, \n  Pun e \nHSB C B an k I n dia  \nWork e d  o n F in an ce  D om ain  &amp;  B an kin g  d o m ain  a p plic a tio n.\nIm ple m en te d  s o rt in g , s e arc h in g  a lg o rit h m s a n d  d esig n\npatte rn s. \n                         \nQR c o de, T ra n sa ctio n h is to ry , R ais e  d is p ute . \nAnd ro id , K otlin , R xJav a , D ag ger 2 ,M VP, R etro ﬁ t, J e n kin s,\n                    \nConte xt, H ooks. \nApplic a tio n E ng in eer -  M obil e  A pplic a tio n\nDeve lo per \nRaw  E n g in eerin g  I n d . P vt. L td . \n08/2 018 -  0 1/2 020\n, \n  Vir a r -  M um bai \nIn  R aw  E ngin eerin g i  h ave  w ork e d  o n s p o rt s  d o m ain  p ro je cts  \n                   \n                             \nso rt in g  a n d  s e arc h in g  a lg o rit h m s. \n                 \nRetro ﬁ t, J e n kin s, G it , A W S, X M PP,F ir e b ase , C ra sh ly tic s \nMobil e  A pplic a tio n D eve lo per \nG.N .R eatil  S e rv ic e s P vt. L td .( Z ap m art .c o m ) \n05/2 016 -  0 7/2 018\n, \n  Mum bai \nZa p m art  i s  O nlin e G ro ce ry  P ro du ct B ase d  C om pan y \nReq uir e m en t &amp;  A naly sis , D esig n a n d  D eve lo p A pplic a tio ns,\nWrit e  A PI&#039;s , W ork  o n B ack -e n d  a n d  D B. \nWork e d  o n z a p m art  a p plic a tio n w hic h  b ase d  o n o nlin e\ngro ce ry  s to re . D eve lo ped  o rd er t ra ck in g  f u nctio nalit y  u sin g\nGoogle  M ap . \nAnd ro id , j a v a , V olle y, G it , B it b uck e t, S Q LLit e , F ir e b ase ,\nCra sh ly tic s. \nSK IL L S  \nAnd ro id  S D K \nJav a  \nGit h u b  \nSQ Lit e  \nRest A PI \nMyS Q L \nFir e b ase  \nRxJav a  \nSo narQ  \nAW S \nMVC \nMVVM  \nRO OM  \nJIR A  \nMock it o  \nSyste m  D esig n \nKotlin  \nMult iT h re ad in g  \nJe tp ack  \n \n    \nAlg o rit h m s \nRetro ﬁ t \nData  s tru ctu re  \nFir e b ase  \nRxJav a  \nLiv e d ata  \nReact N ativ e  \nTyp esc rip t \n    \n \n \n  \nPR O FE SSIO NAL P R O JE C TS \nFo rd  C re d it\n ( 0 4/2 022 -  P re se n t)\n \nHSB C b an kin g\n ( 0 3/2 020 -  0 4/2 022)\n \nHaw ks A re n a F a rm  S ta te  &amp;  S acra m en to  K in g &#039;s\n ( 0 1/2 019 -  0 1/2 020)\n \nJD  P ow er\n ( 0 8/2 018 -  1 2/2 018)\n \nMed ic a lw ale  D octo r A pp\n ( 0 3/2 018 -  0 7/2 018)\n \nza p m art .c o m\n ( 0 8/2 016 -  0 1/2 018)\n \nED UCATIO N \nMCA  ( M aste r i n  C om pute r A pplic a tio n) \nKIT &#039;S  I M ER  K olh ap ur \n07/2 013 -  0 6/2 016\n, \n  Kolh ap u r,M ah ara sh tra , I n dia  \nBCA  \nGopal K ris h n a G okh ale  C olle g e K olh ap ur \n06/2 009 -  0 4/2 012\n, \n  Kolh ap u r ,  M ah ara sh tra  ,  I n dia  \n12th  \nS.M .L o hia  C olle g e, K olh ap ur \n06/2 007 -  0 2/2 009\n, \n  Kolh ap u r \n10th  \nJyo tir lin g  v id ya m an d ir  V ad an ag e \n06/2 002 -  0 3/2 007\n, \n  Kolh ap u r \nIN TER EST S \nPho to gra p hy \nSin g in g  \nCric k e t \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s 	\nUnitTest	\nMVP\nAOSP	\nSplunk	CSS	  Jacoco	\n8369096660	\nMobile Application Developer with 8 years of experience in coding, team lead, architecture design and\non HSBC Bank on financial domain . I have also worked on Sports, Health Care, Automative and E-Commerce.	\nReact Native, Typescript, Android, Kotlin, MVVM,\nJWT, Jetpack, Coroutine, Git, Splunk\nDeveloped application with key features like money transfer,\nNexus, SonarQ, Git, SSL pinning, React Native,\nDeveloped application for NBA teams and Automative App\nLive score update with xmpp protocol. Used multithreading,\nAndroid, Java, Kotlin, RxJava, Dagger2, MVP, AOSP,', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, '2024-07-21 04:51:19', '2024-07-18 04:51:19', 0, NULL, NULL, '2024-07-17 06:49:22', 0),
(380, 91, 73, 37, NULL, '73_91_151717347666976972da4c3_Muhammed_Shihab_HMI_Developer.pdf', 'Muhammed Shihab_HMI Developer.pdf', 'MUHAMMED SHIHAB V K	 	\nSenior Engineer Android	 HMI	 	\nThrissur, Kerala, India	 	\n+91	-9526199466	 	\nShihabvk99@gmail.com	 	\nlinkedin.com	/muhammedshihabvk	 	\ngithub.com/muhammedshihabvk	 	\nhackerrank	.com/muhammedshihabvk	 	\nProfile	 	\nEnergetic, Creative, and 	curiosity	-driven Android/Mobile	/HMI 	Developer with 4+ years of experience, I have a deep understanding 	\nof the Android ecosystem	 with 	different	 domain	s like 	Retail	(Leading brands)	 and 	Automotive	(OEM	), including the latest tools and 	\ntechnologies.  I  specialize  in  building  robust  and  efficient  Android  applications  that  provide  seamless  user  experiences.  I  ha	ve 	\nextensive knowledge in various mobile development languages, including Java, Kotlin, and Dart. 	I have experience in working with 	\nAndroid Studio, the Android SDK, and popular libraries.	 	\n \nCore Qualifications	 	\n▪ 	Native 	Android development	 	\n▪ 	Quality assurance	 	\n▪ 	App	 development life cycle	 	\n▪ 	User experience design	 	\n▪ 	Information architecture	 	\n▪ 	Agile software development methodologies	 	\nSkills	 \n▪ 	Programming Languages: Java, Kotlin, Dart	 	\n▪ 	Android Development: Android SDK, Android Studio, \nGradle, Retrofit, RxJava,	 Coroutine,	 Picasso, Glide. 	 	\n▪ 	Tools and Technologies: Git, GitHub, Bitbucket, JIRA, \nFirebase, RESTful APIs, JSON, Google Maps API.	 	\nProfessional experience	 	\nMahindra	 &amp; Mahindra	, Automotive, 	Coi	mbatore,	 Tamil Nadu	              	         	        	Sep 20	23-Present	 	Senior Engineer 	&ndash; Android HMI	 	\nI work	 as an Android Developer, focusing on creating user interfaces and functionality like battery 	\nmanagement, vehicle 	drive mode	, and gallery	, using	 structured	 MVVM architecture	 for Mahindra 	\nBorn 	Ele	ctric Vehicles	. I also worked on connecting our app with car systems using CAN signals. In 	\nteam  meetings,  I  shared  ideas  and  kept  everyone  updated  on  our  progress  and  any  new \ndevelopments. 	Working closely with the product team, I made sure our technical solutions aligned 	\nwith business needs. Even with tight deadlines, I successfully delivered results. I&#039;m known for being \nfriendly,  respectful,  and  always  ready  to  lend  a  hand.  When  faced  with 	challenges,  I&#039;m  good  at 	\nbreaking them down, finding solutions, and making decisions. Whether I&#039;m working independently \nor with a team, I&#039;m effective and adaptable.	 	\n \nSkills	:  Java,  Kotlin,  Android,	 Service,	 Content 	Provider,	 Broadcast	 Receivers	, Retrofit,  M	QTT	, 	\nMVVM,  ViewModel,  LiveData,	 Coroutine,	 Flow,	 Datastore,  Hilt, 	Car	 &amp; CarPropertyManager	 Libs	, 	\nCAN/Ethernet  Signals,	 Glide,  Git	, GitHub	, Canoe	 17,  QFIL  &amp;  Ren	esas(	Device  Flashing)	, Tera  Term, 	\nLottie Animation, Adobe After Effect for Lottie Json with Bodymovin	, Figma, Visure	, LeapX	. 	\nLitmus	7 Systems Consulting,	 Retail, Kochi	,Kerala	                                  	       	            	 Jul 2019	-Sep 2023	 	\nSenior Engineer 	&ndash; Android	 	\nI  made  a 	user	-friendly  e	-commerce  app  for  Android  that  makes  shopping  easy.  I  worked  with 	\ndifferent teams to make sure the app met all the needs and worked well. We added features like \nproduct listings, search, and payment. I also helped junior developers learn and	 grow. I&#039;m good at 	\nall parts of making an app, like testing and putting it on the app store.	 	\n \nSkills: 	Java,Kotlin,Dart,Android,Flutter,	MVVM,  MVP,  ViewModel,  LiveData,  REST  APIs,  Postman, 	\nRecyclerView,  Glide,  WebView  Retrofit/Fast	-Android	-Networking,    Gson/Jackson  Serialization, 	\nRxJava,  Moengage(Analytics,  geofence,  Notification  center),    Chucker(API  logger),Auth  Token \nHandling  with  OkHttp	 Authenticator,  Firebase(Auth,  Crashlytics)  Zendesk  (Chat),  Google  Maps, 	\nCheckout.com  (Payment),  Ticketing  Systems  (Jira/ServiceNow),  and  Git  VCS  (Bitbucket/GitHub \nRemote).	 	\nL3 Associate POS Engineer	 	\nI managed store software like Oracle Micros Point of Sale for retail shops. Every day, I did \nmaintenance for these systems. I worked with different teams to fix any problems, like POS \ndevelopers and database admins. I managed tickets and solved issues, eve	n outside of regular 	\nhours. I also made sure updates were done smoothly and used PowerShell to automate tasks for \nstores in the US and Canada.	 	\n 	\nEducation	 	\nBachelor of Technology (7.07cgpa) \nComputer science and Engineering \nKMEA Engineering College, IN APJ Abdul \nKalam Technological University 	2019	 	\n \nHobbies	 	\nPhotography, Badminton, Listening \nMusic	, Travelling,	 	\n \nLanguage	 	\nEnglish, Malayalam	 	\n \nPersonal Data	 	\n28yrs, DOB 28 March 1996 	S/O Kadher	 	\n9383	-9181	-5394(Aadhaar IN)', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-21 04:21:20', '2024-07-18 04:21:20', 0, NULL, NULL, '2024-07-17 06:49:22', 0),
(381, 91, 73, 60, NULL, '73_91_129574815666976972da797_Rajat_Dogra-HMI_Developer_2.pdf', 'Rajat Dogra-HMI Developer 2.pdf', 'RA JA T D O GRA\nAndro id  A pplic a tio n  D eve lo p er	\n8329268366 / 9545898398	kakar ajat10@gmail.com	\nhttps://www .linkedin.com/in/r ajat-dogra-a24409105	Bangalore, White	\nSU M MARY\nEnthusiastic Andr oid Developer with a pr oven tr ack record in leading Andr oid IVI	 	\nsolutions and enhancing user e xperience. Skilled in Core Java, Kotlin, Android	 	\nSDK, and Android Application De velopment. Recognized for boosting customer	 	\nsatisfaction through innovative Andr oid Automotive solutions and str eamlining	 	\ndevelopment pr ocesses. Exceptional pr oblem-solving abilities and a passion for	 	\ndeveloping cutting-edge applications. Eager to contribute to impactful pr ojects	 	\nin line with the company&#039;s mission and vision.\nE X PER IE N CE\nIT  A naly st\nTata Consultancy Services	\n01/2019 - Pr esent	&nbsp;	Bangalore	\nBoosted customer satisfaction b y	 20%	 by leading the tr ansition to Andr oid	 	\nAutomotive for IVI solutions thr ough developing POCs.\nDeveloped multiple Andr oid IVI applications enhancing vehicle inter activity	 	\nand user experience.\nLed 	requir ement analysis	 for (5+ years) major pr ojects, streamlining	 	\ndevelopment and documentation pr ocesses.\nIncreased code performance b y 	20%	 by addr essing pr oduction defects using	 	\nJIRA and GitLab CI/CD .\nExperience of agile methodology such as 	SCRUM 	and 	KANBAN	.	\nDeveloped 	5+	 Andr oid applications, o verseeing full lifecycle de velopment	 	\nfrom 	concept	 to 	deplo yment	.	\nOversaw a team of 	7 developers ensuring timely and quality deliver able.	\nSK IL LS\nCor e Java	Kotlin	Andr oid Application De velopment	\nAndroid SDK	Android Jetpack	Android Testing	MVVM	\nUI/UX Design	RESTful APIs	XML	JSON	UML Diagr ams	\nGitlab CI/CD	GIT	Problem-Solving	Debugging	\nBug T racking	Requir ement Analysis	Softwar e Design	\nST R EN GTH S	\nIn nova tiv e  A ndro id  S o lu tio n s\nPr oven tr ack record in leading Andr oid IVI solutions and enhancing user	 	\nexperience.\nE ffe ctiv e  P ro b le m -S o lv in g S kil ls\nEx ceptional pr oblem-solving abilities in identifying and addr essing	 	\nproduction defects e\nStr e a m lin in g D eve lo p m en t P ro ce sse s\nRecognized for str eamlining development and documentation pr ocesses	 	\nfor major projects.\nPassio n  f o r C u ttin g-E d ge A pplic a tio n s\nEager to contribute to impactful pr ojects and develop cutting-edge	 	\napplications in line with company &#039;s vision.	\nE D UCA T IO N\nBach elo r o f E n gin eerin g i n  C om pute r	 	\nS cie n ce\nUniversity of Mumbai	\n2014 - 2018	&nbsp;	\nA CH IE V EM EN TS	\nEmplo yee of the Month\nRecognized as &#039;Emplo yee of the Month&#039; 5 times	 	\nover a span of 5+ years, sho wcasing	 	\nexceptional performance and contribution to	 	\nthe pr oject.\nHigh Performance Ratings\nReceived the highest performance r ating	 	\nconsistently over a period of 5+ years for	 	\noutstanding skill, work quality , deliverables,	 	\nownership and dedication.\nNominated for Ex cellent Work Award\nNominated for an e xcellent work awar d by TCS	 	\nJapan pr esident in r ecognition of e xceptional	 	\ncontributions.\nIVI Solution Pioneer\nLed Andr oid Automotive tr ansition, developed	 	\ncritical POCs\nAndroid IVI De velopment\nCreated andr oid IVI apps for cars lik e 	Nissan	 	\nAriya	, Nissan Rogue	, enhancing user	 	\nexperience\nE\nOptimized memory usage, impr oved	 	\napplication performance signi\nInno vative Publication\nPublished on auto colorization of gr ayscale	 	\nimages and videos using deep learning in	 	\nICSCET	\nPU BLIC A T IO N S\nAuto m atic  I m ag e a n d V id eo  C olo riz a tio n	 	\nu sin g D eep  L e a rn in g\n2018 International Confer ence on Smart City	 	\nand Emerging Technology(ICSCET)\nRaja t D ogra	\n2018	&nbsp;	\nhttps://ieee xplore.ieee.or g/document/8537308	\n10.1109/ICSCET .2018.8537308	\nE		\nq		\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n\n\n\n	\n)\n)\n)\n)\n)\n)\n)', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-08-07 17:14:37', '2024-08-04 17:14:37', 0, NULL, NULL, '2024-07-17 06:49:22', 0),
(382, 91, 73, 39, NULL, '73_91_72373439366976972dabf1_Suresh_HMI_Developer.pdf', 'Suresh_HMI Developer.pdf', 'Suresh_Android Developer	 	\n \n \n \nSuresh Reddy B	 	 	 	 	 	 	 	 	 	Mobile	                     	 	\n 	 	 	 	 	 	 	 	 	 	    	+91 8309076590	                     	\nAndroid Developer	 	\nsuresh.bhumireddy94@gmail.com	                                                                               	 	\n \nProfessional Summary:	 	\n	 		 	\nas a 	Android	 Developer 	for	 Sasken Technologies P	vt Ltd	, Banglore	  . 	\n	 Worked as a 	Android Developer	 from 	 CssCorp	 Pvt	 Ltd	  from 	August	,20	20	 to 	25 Oct,	20	21.	 	\n	  Worked as a 	Android Developer	 from 	 Nextbrain Technologies 	Pvt	 Ltd	  from June,201	8 	\nto Ju	ly,20	20	. 	\n	 Worked as a 	Android Developer	 from 	 KRYPTOBLOCKS 	from June,2017 to 	June,2018.	 	\n	 Significant experience in Developing Mobile (Android) Application and Designing.	 	\n	 An effective communicator with excellent relationship building &amp; interpersonal skills. \nPossess a flexible &amp; detail oriented attitude.	 	\n \n \nMajor Strengths:	 	\n➢ 	Designing a	nd programming 	Android	 apps	 using with UI Components and CoreJava	. 	 	\n➢ 	End to end application development including requirement study and designing.	 	\n➢ 	Implement effective customer satisfaction strategies by identifying the root causes of \ncustomer problems.	 	\n➢ 	Clie	nts management	 	\n➢ 	Adapt in defect analysis and time managed work.	 	\n➢ 	Excellent analytic, design and problem solving skills.	 	\n➢ 	Ability to do disciplined and time managed work.	 	\n➢ 	Strictly adhere to the quality standards, following 	Android	 development guidelines and 	\nQuality system.	 	\n 	\n \nTechnical Background:	 	\n 	\n✓ 	Languages	: CoreJava, Android	,Kotlin	 	\n✓ 	Platform	: Windows,	 Linux	 	\n✓ 	Database	: Sqlite,Room.	 	\n✓ 	Framework	: Android 	SDK	 	\n✓ 	IDE:	 Android Studio	 	\nHaving 6.5 years of experience in Android Application development and currently working	\n,AOSP and Android Framework\n\n✓ 	Tools:	 Bug Tracker ,Active Collab,Gitlab	,Mantis Tracker.	 	\n✓ 	Architecture:	 MVVM, MVP, Clean Architecture.	 	\n \n \nEducational Qualification:	 	 	\n 	Completed B.Tech(E.C.E) from Madanapalle institute of Technolgy and Science 	(JNTU) 	\n,Madanapalle 	in the year 2016.	 	\n 	Completed +2  from	Sri Siddartha Junior College(A.P. board), Andhra 	Pradesh in year	2012.	 	\n 	Completed 10	thwith SathyaSai High School	 (A.P. board), Andhra Pradesh in 	year 2010.	 	\nProfessional Experience	: 	\nProject 1: 	OLA HMI ( Human Machine 	- Interface)	 	\nClient	: OLA Electric 	 	\nRole : Android Firmware Developer	 	\nProject Details:	 	\n OLA 	Electric is a electric scooter which is already available in the market and upgrowing scooter. 	\nEvery part of the scooter is controlled by CAN IDs and it includes sensors for all parts of the \nscooter.	 	\n \nRole: 	worked on HMI and display of the 	scooter,indicators,start buttons ,brakes and side stand 	\n.we used Kanzi UI for display and code base is Android and services.Worked on Wifi feature and \nbluetooth functionality.	 	\n \nProject 	2: SHIKHAR	 	\nClient	: Hindustan Unilever Ltd.	 	\nRole : Android Developer	 	\nPro	ject Details:	 	\nThis  is  a 	Business  to  Business  Android  application  by  Hindustan  Unilever  Ltd.  The  base 	\nfunctionality  of  this  app  is  to  deliver  the  parcels  to  local  stores  or  local  outlets  which  are  tied  up \nto  Unilever.  The  customer  can  order  products  and  do 	payments  in  installment  method  .This  is  a 	\nbig  program  run  by  HUL  where  the  billing  of  ordered  products  will  be  done  by  IKEA.Based  on \ncustomer  purchase  he  can  get  reward  points  and  can  utilise  those  points  while  ordering  the \nproduct.We have integrated you p	ayment and SBI banking process to this application.\n\nProject 	3: Thobey Driver	 	\nRole: 	Developer	 	\nProject Details:	 	\nThis is a laundry service app which includes three panels as they are customer, driver and vendor. \nDriver  can  receive  orders  from  customer  and  a	ssigned  by  vendor,where  thi	s  app  includes 	\nhardware 	printer  integration	 using  AIDL	 and  Google  directions  and  tracking  facility  of 	\ncustomer.  Once  an  order  is  assigned  by  vendor  then  this  driver  will  go  to  customer  location  and \nhe will collect cloths and gene	rate one QRcode for that pickup bag. Then he will deliver the cloths 	\nto same location after laundry.	 	\n \nProject 	4:  DROPR: Delivery and Transportation Service	 	\nRole: 	Developer	 	\nDescription:	 	\nThis is Indian parcel Delivery Appication with 100km Range.By using th	is app customer can assign 	\norder to driver by giving pickup and Drop locations using Google maps Drag and Drop methods as \nwell as Auto Complete address. We can deliver up to 20 Delivery Locations with parcel images \nupload option. While Driver is on Deliver	y ,Customer can able to track the Driver and can able to 	\ncontact via phone. Implemented Offline payment and Online payment (Razorpay payment \ngateway)	 	\nPlaystore Link: 	https://play.google.com/store/apps/details?id=com.app.dropr	 	\n \nProject 	5: DROPR Delivery 	Partner	 	\nRole: 	Developer	 	\nDescription:	 	\nThis app mainly used for track order status,parcel delivery app, can get order from the \ncustomer.By using change order status, He can able to change status also.View order information \nof particular order and should comp	lete order with Digital signature for verification purpose. We 	\ncan view order information of particular order and Notifies order status using push notification.	 	\n \nPlaystore Link: 	 https://play.google.com/store/apps/details?id=com.app.droprdriver	 	\n \nProject 	6: Laparalah Rider	 	\nRole: 	Developer	 	\nDescription:	 	\nAfter payments are made by our customers online, digital delivery orders with details such as\n\norder ID, order items, vendors, customer delivery addresses are generated through our \nmainframe and distributed to o	ur delivery teams so that they can pick up the orders and make 	\ndelivery to our customers. Driver can track customer location also.	 	\nDriver will get orders in two ways ,Manually assign ( admin or vendor can assign order manually \nby using assign to option) an	d Automation (order will assign automatically to the nearest 	\ndriver).Both cases driver will notified using push notification.	 	\n 	 	\nPlaystore Link: 	https://play.google.com/store/apps/details?id=com.app.laparlahdriver	   	\n \nProject 	7: Dumbo Delivery 	- cambodia	 	\nRol	e: 	Developer	 	\nDescription:	 	\nThis is Cambodia parcel Delivery Appication.By using this app customer can assign order to driver \nby giving pickup and Drop locations using Google maps Drag and Drop methods as well as \nAutocomplete address. We can deliver up to 20	 Delivery Locations with parcel images upload 	\noption. While Driver is on Delivery ,Customer can able to track the Driver and can able to contact \nvia phone. Implemented Offline payment and Online payment (Paypal payment gateway).	 	\n 	 	\nPlaystore Link: 	https://play.google.com/store/apps/details?id=com.app.dumbodelivery	 	\n \nProject 	8: Antflip Customer	 	\nRole: 	Developer	 	\nDescription:	 	\nThis is Indian parcel Delivery Appication with 100km Range.By using this app customer can assign \norder to driver by giving pickup 	and Drop locations using Google maps Drag and Drop methods as 	\nwell as Auto Complete address. We can deliver up to 20 Delivery Locations with parcel images \nupload option. While Driver is on Delivery ,Customer can able to track the Driver and can able to \ncon	tact via phone. Implemented Offline payment and Online payment (Razorpay payment 	\ngateway)	 	\nPlaystore Link: 	https://play.google.com/store/apps/details?id=com.app.antflip	 	\n \nProject 	9: Antflip 	- Driver\n\nRole: 	Developer	 	\nDescription:	 	\nThis app mainly used for track	 order status,parcel delivery app, can get order from the 	\ncustomer.By using change order status, He can able to change status also.View order information \nof particular order and should complete order with Digital signature for verification purpose. We \ncan 	view order information of particular order and Notifies order status using push notification.	 	\n 	 	\nPlaystore Link: 	 https://play.google.com/store/apps/details?id=com.app.antflip_driver 	 	\n  \n 	 	 	 	 	 	 	 	 	 	 	 	\n                                                                                                                             	                   	 	\n \n \n \n \n \n \n \n \n \n \n                                                                                                     	                                                 	Signature', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-31 09:21:42', '2024-07-28 09:21:42', 0, NULL, NULL, '2024-07-17 06:49:22', 0),
(383, 91, 73, 46, NULL, '73_91_177508792766976972daed9_Tabassum_Sayyad-HMI_Developer.docx', 'Tabassum Sayyad-HMI Developer.docx', '\r\nTABASSUM\r\nRESUME\r\n617855199279617855319294Experience Summary and Skill Set\r\nExperience Summary and Skill Set\r\ntabassum.sayyad1@gmail.comContact No: +91-9834112268\r\nResult oriented professional with 8.6 years of versatile experience in Android, Kotlin and Java technology.\r\nCurrently functioning as a Lead product Engineer with Harman.\r\nWorking on Android Automotive domain HMI, DCSM, Android Auto, CarPlay.\r\nWorked on AOSP code.\r\nInvolved pro-actively in various phases of Software Development Life Cycle in terms Analysis, Design, Development, Testing, Implementation, and Maintenance &amp;amp; Support.\r\nProficient experience in developing applications using Android using Java, Kotlin, React Native.\r\nHighly dedicated to produce professional work with highest quality and creativity.\r\nCommitment, hardworking, can grasp things quickly and think strategically.\r\nSUMMARY:\r\nGood knowledge of Android Framework API and Core Java and Kotlin.\r\nKnowledge of Design Patterns(MVP,MVVM), UI Material design(Recycler View, Coordinate layout and Constraint layout)\r\nExperience on remote data via REST and SOAP\r\nUnderstanding of JSON,XML parsing\r\nExperience in payment gateway\r\nExperience in third party libraries Retrofit, Volley, Picasso and Glide\r\nExcellent analytical and logical programming skills with a good understanding at the conceptual level\r\nGood in problem solving, communication skills and good team player\r\nAbility to learn new technologies and work in a dynamic environment and under pressure situations.\r\nHave working experience in agile and waterfall development process.\r\nExperience in Git and have basic knowledge of Jenkins configuration management tools.\r\nExperience to publish Apk on Google play store.\r\nComprehensive knowledge of React Native platform and core principle\r\nCommand over Kotlin.\r\nUsed Live Data\r\nImplemented Kotlin Coroutines for Thread Management.\r\nWorked using Room DB\r\nUsed data classes, Extension function\r\nWorked on RxjavaWorked on Jetpack component\r\nCOMPUTER SKILLS:\r\nLanguage/Platform: Kotlin, Core Java, Android, React Native, JavaScript, Apex\r\nDatabase: SQLite, Room Database, MySQL.\r\nOperating System: Win 10, Microsoft Win 7, Win 8, Ubuntu, Harmony OS\r\nEnvironment /Tools: Eclipse, Android Studio,STS, Android SDK, Git,Gerrit, BitBucketGitLab(Github),BugZilla, JIRA, Jenkins, SonarQube,VS code\r\n\r\nHarman. &ndash; BangaloreMay 2023 &ndash; Present\r\n    Project: PSA \r\n Client: Stellantis Description: The Android Automotive application for car brand called Peugeot, where car driver can   control climate, connect to mirroring projection like Android Auto or Car Play via Bluetooth or USB, able to play music by connecting to USB or Bluetooth, by projection user can connect voice call like incoming or outgoing call.\r\nTechnology: Android SDK, Java\r\n    Role:\r\n  Some of the key responsibilities while executing this project are as listed below -\r\nImplementation of features.\r\nFixing Framework Defects.\r\nWipro Ltd. &ndash; Pune, MHOCT 2020 &ndash; May 2023\r\nProject: ZRPL\r\nDescription: This application provides Wipro employees with substantial savings on ecommerce products. Employees can use this app to log in using their Wipro credentials and buy the product. This app provides a variety of brands, many of which provide substantial discounts on premium brands.\r\nTechnology: Android SDK, Kotlin, React Native\r\n    Role:\r\nPrepare solution based on understanding of the challenges.\r\nImplementation of the solution\r\nWorked in different module such as the product management, Address management and the Cart Module\r\n    Project: HR Direct\r\nDescription: The employee HR capabilities are accessed using this application. Once logged in, the user has access to timesheet, last six months&#039; worth of salary slips, and leave management. Here, employees can use the app to access their leaves and request leaves. Additionally, this application allows you to view and download an employee&#039;s pay slip.\r\nTechnology: Android SDK, Kotlin, React native\r\n    Role:\r\nUnderstand the various challenges faced by employee, management and HR and document the challenges in detail.\r\nDesign and development of the solution\r\nImplementation of the solution\r\nDelivered the project with 0 post-delivery defect\r\nTech Mahindra &ndash; Pune, MHAug 2019 &ndash; Oct 2020\r\n    Project: Messaging App\r\n   Client: HMD Global\r\nDescription: This application offers its users chat (RCS) and texting (MMS, SMS). Everyone has access to group texts and the ability to share images, GIFs, Emojis, videos, and voice communications.\r\nTechnology: Android SDK, Java\r\n     Role:\r\nDesign and development of the solution.\r\nImplementation of the solution.\r\nDevelopment of user friendly UI/UX added additional features like auto deletion of messages, auto texting at scheduled time and other features.\r\nBlue Planet Info Solutions (India) Pvt. LtdJan 2016 &ndash; Aug 2019\r\n \r\nWorked on various products across multiple domains. Product were developed using Android, React native and Java. Below is the list of products developed.\r\nSmartCookie Application which is a student teacher reward system\r\nOne Bay TouchPill Box\r\nTravel PillBoxVirtual PillBoxiTake-med\r\nSafety on Wheels\r\nKnow Your Medi\r\nEducation\r\nAmrutvahini College of Engineering, SangamnerBE in Information Technology | 2012-2015 | Percentage : 60%\r\nPVVP College of Engineering, LoniDiploma in Information Technology | 2009-2012 | Percentage : 67.25%\r\nSharda Kanya Vidya Mandir, RahataSecondary (12th Standard) | 2002-2003 | Percentage : 45.00%\r\nChandak Kanya Vidya Mandir, SinnarSecondary (10th Standard) | 2000-2001 | Percentage : 54.00%\r\nPersonal Details\r\nFull Name:Tabassum Abdul Latif Sayyad\r\nDate Of Birth:22nd May 1986\r\nGender:Female\r\nNationality:Indian\r\nLanguages Known:English, Hindi and Marathi\r\nAddress:Rabiya Nagar, behind Shri Hari hospital, Rahata 423107, Maharashtra.\r\nDeclaration\r\nI hereby declare that above mentioned information is genuine and true to the best of my knowledge.\r\nDate:/  / 2024Sincerely\r\nPlace:  Rahata(Tabassum Sayyad)\r\n', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-22 10:40:37', '2024-07-19 10:40:37', 0, NULL, NULL, '2024-07-17 06:49:22', 0),
(384, 91, 73, 36, NULL, '73_91_30871182466976972db136_Vishwas_HMI_Developer.pdf', 'Vishwas HMI Developer.pdf', 'Pag e 1  o f 2  \nWORK  E X PER IE N CE :  \nMah in d ra  &amp;  M ah in d ra  L td  (  M ah in d ra  S o ft w are  D efin ed\nVeh ic le  C en te r )  \nSen io r S o ft w are  E n g in eer (  L 7-O pera tio nal  )  \n10 /2 0 23 -  P re se n t\n, \n  Coim bato re  \nFu ll  T im e \nWork e d  a s H M I  D eve lo p er  fo r  M ah in d ra  V eh ic le s a t M SD VC b y E le vatin g  c lu ste r\nfe atu re s w it h  k o tlin  &amp;  J a v a. \nEn han ce d  IV I  M ed ia   ap plic a tio n  b y  im ple m en tin g   ad van ce d  so urc e   se le ctio n\nfe atu re s a n d  f u lf illin g  n ew  r e q uir e m en ts ,  o p tim iz in g  f u nctio nalit y  t o  m eet s p ecif ic\npro je ct o b je ctiv e s. \nSp earh ead ed  th e d eve lo p m en t  o f  S en try  M od e,  P ark  A pp,  M yV eh ic le ,  A m bie n t\nLig hts   IV I \nApplic a tio ns,  in co rp ora tin g   esse n tia l  fe atu re s  to   en han ce   use r\nexp erie n ce  a n d  S ecu rit y . \nSu cce ssfu lly   in te g ra te d   Vid eo   Pla y e r,  Exo   Pla y e r  &amp;  sc re en sh o t  fu nctio n\nim ple m en ta tio ns,  e n ric h in g  th e a p plic a tio n w it h  se am le ss  m ult im ed ia  p la y b ack\nca p ab ilit ie s. \nIm ple m en te d  s e ekb ar f u nctio nalit y  w it h in  t h e a p plic a tio n,  e n han cin g  u se r c o ntro l\nan d  n av ig atio n t h ro ug h v id eo  p la y b ack . \nLe ve ra g ed   JIR A  to   cre ate   co m pre h en siv e   te st  se ts ,  stre am lin in g   th e  te stin g\npro ce ss a n d  e n su rin g  t h o ro ug h c o ve ra g e o f U I e le m en ts  a n d  f u nctio nalit ie s. \nCond ucte d  U I  t e stin g  a n d  in stru m en ta tio n t e stin g  t o  id en tif y  a n d  re ctif y  is su es,\nth ere b y e n han cin g  t h e o ve ra ll  u sa b ilit y  a n d  p erf o rm an ce  o f t h e a p plic a tio n. \nExp ert  in  a ctiv e ly  re so lv in g  B ug s fo r  a  w id e a rra y  o f  a p plic a tio ns,  s p ecia liz in g  in\nboth   se lf - d eve lo p ed   ap plic a tio ns  an d   fo r  In -V eh ic le   In fo ta in m en t  (  IV I  )\nap plic a tio ns. \nUtiliz e d  C A N oe a n d  V eh ic le  S p y s o ft w are  to  p erf o rm  c o m pre h en siv e  h ard w are\nte stin g  o f (C A N )  a n d  (E C U )  s ig nals  f o r V eh ic le  T e stin g ,  e n su rin g  s y ste m  r e lia b ilit y\nan d  f u nctio nalit y  t h ro ug h d eta ile d  s ig nal  a n aly sis  a n d  t ro ub le sh o otin g . \nCap gem in i  En g in eerin g   (  R &amp; D Su b sid ia ry   of \nCap gem in i\nGro u p  )  \nSo ft w are  E n g in eerin g  L e ad  (  P ro fe ssio nal  I / B 1 )  \n04/2 0 23 -  1 0 /2 0 23\n, \n  Ban g alo re  \nFu ll  T im e \nSp ecia liz e d   in   co nnectiv it y   wit h   Apple   devic e s  an d   work e d   on  Apple &#039;s\nte ch no lo gie s s u ch  a s iA P1,  iA P2 a n d  A pple  C ar P la y . \nMan ag ed   a  te am  fo r  deve lo p m en t  of  Apple   co nnectiv it y   fo r  Auto m otiv e\nin fo ta in m en t a n d  m an ag in g  A pple &#039;s  c e rt if ic a tio n p ro ce ss g lo b ally . \nSp earh ead ed   th e  Connectiv it y   dom ain   fo r  sm art   pho ne  in te g ra tio n  w it h\nau to m otiv e  in fo ta in m en t a n d  p ro je ctio n t e ch no lo gie s. \nSp earh ead ed  th e  In fo ta in m en t  sy ste m  an d  re sp onsib le   fo r  han d lin g   m ult ip le\nap plic a tio ns  a n d  re sp onsib le  fo r  d eve lo p m en t  o f  A nd ro id  In fo ta in m en t  S yste m\nwhic h  in clu d es w ork in g  w it h  w ir e le ss p ro to co ls . \nHan d le d  a  t e am  fo r  d esig n a n d  d eve lo p m en t fo r  S m art  P ho ne C onnectiv it y  a n d\nPro je ctio n t e ch no lo gie s in  C onnecte d  C ars . \nHav e  g o od  u nd ers ta n d in g  o f  iA P1,  IA P2,  A O SP  A nd ro id  C ar  P la y  C ontro l  B onjo ur\nse rv ic e  a n d  p erf o rm an ce  t u nin g  o f A pple  C ar P la y  s o lu tio n f o r M Fi  c e rt if ic a tio n. \nSK IL LS  /  T O OLS  :  \nAnd ro id  A pplic a tio n D eve lo p m en t \nCore  J a v a \nGen eric  F ra m ew ork  \nHA L L a y e r \nJa v a 8  \nC P ro gra m min g  L a n g uag e \nC++ \nAnd ro id  T e le p ho ny \nAUTO SA R \nIn fo ta in m en t H ard w are  T e stin g  \nSo narc u b e \nJIR A  \nMVVM  \nIn stru m en ta tio n T e stin g  (  U I T e stin g  )  \nRo om  D ata b ase  \nPerf o rm an ce  T e stin g  \nAD AS \nJIR A  X -R ay  \nGIT H U B \nKotlin  \nKotlin  C oro utin es \nLIN UX \nAnd ro id  S D K \nNav ig atio n C om ponen t \nAuto m otiv e  I n fo ta in m en t \nAO SP  \nAnd ro id  A uto  P ro je ctio n \nApple  C ar P la y  \nTh ir d  P art y  L ib ra rie s &amp;  A PI&#039;s  \nMult im ed ia  I n fo ta in m en t \nFig m a(U I/ U X) \nFlu tte r \nGoogle  P la y  S to re  \nDart  P ro gra m min g  \nBin d er I P C  \nApplic a tio n S ecu rit y  \nSA ST /  D AST \nAnd ro id  F ra m ew ork  \nAnd ro id  A pp D eve lo p m en t \nAID L /  H ID L \nUnit  T e stin g  \nPen etra tio n T e stin g  \nTe le m atic s \nPro je ctio n T e ch no lo gy \nConnectiv it y  \nGIT  \nGIT H U B \nCA N oe \nVeh ic le  S p y \nRA D -G ig asta r \nPR O JE C TS :  \nCogniz a n t :  G oogle  P la y  P ro te ct (  G .P .P  )\n ( 1 2 /2 0 20  -  0 4/2 0 20 )\n \nCap gem in i  :  H A RM AN  (  T o yo ta  T A S70 0 )\n ( 0 4/2 0 23 -  1 0 /2 0 23)\n \nMah in d ra  &amp;  M ah in d ra  :  M ah in d ra  E le ctric  S U Vs H M I I V I\nApplic a tio ns (  B E.0 5,  B E.0 7,  B E.R A LL-E ,  X U V.e 8 ,  X U V.e 9\n ( 1 0 /2 0 23 -  P re se n t)\n Ach ie ve m en ts /T a sk s \nTa sk s \nhk.v is h w as2 0 23@ gm ail.c o m  \n+91 :  7 9 75 35 0 95 8  \nBan g alo re ,  I N DIA  \nlin ke d in .c o m /in /v is h w as-h -k -0 610 4616 6 \nVIS H W AS H  K  \nAnd ro id  A uto m otiv e  H M I / F ra m ew ork / I n fo ta in m en t\nDeve lo p er \nAn e n th usia stic  M ob ile  A pplic a tio n D eve lo p er  (  S o ft w are  E n g in eer  L e ad  )  w it h  a\nro b ust  A nd ro id  Secu rit y   &amp;  p ro gra m min g  exp osu re   h av in g  clo se   to  4  ye ars   o f\nexp erie n ce  in  A nd ro id  H M I/ S D K,  R eve rs e  e n g in eerin g  w it h  h an d s o n e xp ert is e  in\nko tlin ,  J a v a,  F lu tte r,  A nd ro id  S tu d io ,  G IT ,  J IR A  a n d  A uto m otiv e  P ro je ctio n D om ain\nConnectiv it y .  C urre n tly  w ork in g  a s a  S en io r E n g in eer in  M ah in d ra  &amp;  M ah in d ra  \nin  t h e\nAuto m otiv e  so ft w are  la n e a s  a  d ed ic a te d  a n d  fo cu se d  H M I  e n g in eer  p rim arily\nfo cu sin g  o n d eve lo p in g  I V I a p plic a tio ns f o r N ext-G en  M ah in d ra  E V  V eh ic le s.\n\nPag e 2  o f 2  \nWORK  E X PER IE N CE :  \nCog niz a n t T ech nolo g y S o lu tio n s (  C TS )  \nTe ch nic a l  L e ad  (  A pplic a tio n D eve lo p m en t &amp;  A nd ro id  S ecu rit y\nLe ad  )  \n12 /2 0 20  -  0 4/2 0 23\n, \n  Ban g alo re  \nFu ll  T im e \nExp ert is e   in   re ve rs e -e n g in eerin g   an d  co d e-le ve l  se cu rit y   au d it in g ,  as  w ell  as\nexp erie n ce  in  h an d lin g  o b fu sc a te d  c o d es o f a n d ro id  a p plic a tio ns. \nGood  E xp osu re  in  c o nd uctin g  S ecu rit y  T e stin g  o f  b oth  S A ST a n d  D AST a n d  to\nsa fe g uard  a p plic a tio n c o d e f ro m  m alw are  s u ch  a s s p yw are ,  p his h in g ,  r a n so m ware ,\ntro ja n s,  b ack d oor,  r o otin g  a n d  o th er c y b er t h re ats . \nPerf o rm in g  in te rn al  a n d  e xte rn al  v u ln era b ilit y  a sse ssm en ts  a n d  p erf o rm in g  d ata\nan aly sis  a n d  c re atin g  d ete ctio n r o utin es f o r d if fe re n t in te rn al  p ip elin es. \nExp erie n ce  in  M alw are  a n aly sis  o n A nd ro id  M ob ile  p la tfo rm ,  id en tif y  t h re ats  a n d\ncla ssif y  t h em  a cco rd in g  t o  t h eir  f a m ily . \nCond ucte d  M alw are  A ud it in g  o f c lo se  t o  1 0 ,0 00 A nd ro id  A pplic a tio ns in  t h e\nMuW S,  P SL t ra ck s a s a  S M E. \nED UCA TIO N :  \nM.T ech  (  U niv ers it y  V is v esv ara y a C olle g e o f E n g in eerin g  )  \nCom pute r S cie n ce  &amp;  E n g in eerin g  \n10 /2 0 18  -  1 2 /2 0 20\n, \n  Ban g alo re  \n8.9 3 C G PA\n  PU BLIC A TIO NS :  \nTru st M an ag em en t f o r S erv ic e -O rie n te d  S Io T S yste m s \nPub lis h er :  A CM  D ig it a l  L ib ra ry  \nhttp s:/ /d oi.o rg /10 .1 14 5/3 4 46999.3 4 476 35  \nTa sk s \nGra d e', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-08-07 17:13:13', '2024-08-04 17:13:13', 0, NULL, NULL, '2024-07-17 06:49:22', 0);
INSERT INTO `resume` (`id`, `screeningId`, `adminId`, `candidateId`, `candidateDetailsId`, `resumeName`, `resumeOriginalName`, `resumeContent`, `isSkillScreened`, `isResumeScreened`, `isCron`, `isCandidate`, `candidateShortlist`, `enableInterviewReport`, `gptLanguageId`, `isInterviewAssign`, `interviewValidity`, `interviewAssignDate`, `isPsychoAssign`, `psychoValidity`, `psychoAssignDate`, `created`, `createdBy`) VALUES
(385, 92, 73, NULL, NULL, '73_92_184436324966993a392e20c_Ajay_Chaudhari_-_HMI_Developer.pdf', 'Ajay Chaudhari - HMI Developer.pdf', '/  	\nA JAY  C H AU DH ARI\nSoft w are  D eve lo p er	\narc h au d hari1 4 0 2@ gm ail. c o m	h ttp s:/ /w ww.lin ke d in .c o m /in /a ja y -\nc h au d hari- 0 15 6 ba16 9/	\nK an ag aw a, J a p an	\nS U M MARY\nExp erie n ce d  S oft w are  D eve lo p er w it h  o ve r 4 .3  y e ars  s p ecia liz in g  in  A nd ro id -\nbase d  A uto m otiv e  In fo ta in m en t s y ste m s 	 \n 	\nP ostg re S Q L,  a n d  O doo.  I  a m  e ag er t o  c o lla b ora te  o n a d va n cin g  c u ttin g -e d ge	 	\nte ch no lo g y a n d  d eliv e rin g  e xc e p tio nal  r e su lt s .\nE X PER IE N CE\nOnsit e  D eve lo p m en t E ngin eer\nTata  C on su lt a n cy S erv ic e s L td	\n0 5/2 0 24	&nbsp;	K an ag aw a,  J a p an	\nA ssig ned  F e atu re :  R ad io  	 	\nR ad io ,  P od ca st)\nO nsit e  S PO C f o r R ad io  f e atu re ,  C lie n t c o m mun ic a tio n,  M an ag e S O P /  Q LU	 	\n/ M ain lin e d eliv e rie s f o r N is sa n  V eh ic le s,  B ug  t r ia g in g  a n d  f ix in g\nW ork in g  w it h  c ro ss-fu n ctio nal  t e am s s u ch  a s X peri,   L G ,  G oog le ,  B osc h ,	 	\netc .\nT e ch S ta ck:  A nd ro id ,  K otlin ,  J a va ,  A O SP,  A ASP	\nS yste m s E ngin eer\nTata  C on su lt a n cy S erv ic e s L td	\n0 1/2 0 22 	&nbsp;	G an d hin ag ar,  In d ia	\nN is sa n  IV I  f e atu re s:  T e le m atic s 	 	\nC onnm an  \nF i,   a n d  H ots p ot).\nH M I  d eve lo p m en t t h at w ork s w it h  A O SP a n d  H AL p ro vid ed  b y L G  a n d	 	\nB osc h ,  f e atu rin g  1 0 0\nB uilt  p yth o n s c rip t t h at r e d uce d  S ST R g en era tio n t im e b y 8 0 %\nTe ch S ta ck:  A nd ro id ,  K otlin ,  J a va	\nJ r. A pplic atio n  E ngin eer\nTin yE R P P vt. L td	\n1 0 /2 0 20  	&nbsp;	A hm ed ab ad ,  In d ia	\nO doo:  E R P B usin ess S uit e  o f o p en -s o urc e  b usin ess a p ps c o ve rin g  C RM ,	 	\neC om merc e ,  A cco un tin g ,  In ve n to ry ,  P O S e tc\nD eve lo p m en t o f c u sto m  m od ule s a s p er c lie n ts &#039;  n eed s.  A ddre sse d  m ain ly	 	\ng en eric  &amp;  s p ecif ic  is su e s d urin g  d ata b ase  u p gra d es.  1  g en eric  f ix  c a n	 	\nre so lv e  r o ug hly  1 0  C lie n ts  d ata b ase  u p gra d e is su e s\nTe ch S ta ck:  P yth o n,  P ostg re sq l,   J S ,  U bun tu	\nP yth on /O doo D eve lo p er\nBro w se ln fo  P vt. L td	\n0 3 /2 0 20  	&nbsp;	A hm ed ab ad ,  In d ia	\nD eve lo p ed  C usto m  L ib ra ry  m an ag em en t O doo A pp,  P ro d uct Q ualit y	 	\nA ssu ra n ce  A pp u sin g  g en eric  m od ule s\nC ontr ib ute d  t o  e xis tin g  O doo A pps lik e  B atc h  P ay m en t d urin g  in vo ic in g\nTe ch S ta ck:  P yth o n,  J S ,  O doo	\nE D U CATIO N\nBach elo r o f E ngin eerin g\nSA L E n g in eerin g  A nd  T e ch nic al I n stit u te , G TU	\n04 /2 0 17  	&nbsp;	A hm ed ab ad ,  In d ia	\nGP A	\n8.2 7	10	\nC om pute r E ng in eerin g  M ajo r	\nS KIL LS\nTe ch S ta ck\nA nd ro id	J av a	K otlin	P yth on	\nO doo	P ostg re sq l	M atp lo tL ib	\nN um py	O pen C V	Pan d as	S eab orn	\nS kle arn	G it	\nT e ch nic al  E xp ert is e\nA uto m otiv e  I n fo ta in m en t f o r C CS\nER P S oft w are  	M ac h in e L e arn in g	\nP R O JEC TS\nAuto m atic  A tte n dan ce  S yste m	\nhttp s:/ /g it h ub .c o m /A jja rv is /A uto m atic _A tte n d an ce _S\ny ste m	\nF ace  R eco g nit io n-b ase d  A uto m atic  A tte n d an ce	 	\nS yste m  u sin g  C CTV  f o r r e al- tim e s tu d en t	 	\natte n d an ce .	\nTe ch S ta ck:  P yth o n,  T kin te r,  X lr d ,  X ls x w rit e r,	 	\nO pen C v	\nIn diM on ey : A n E xp en se  T ra cke r A pp	\nhttp s:/ /g it h ub .c o m /A jja rv is /In d iM oney	\nA nd ro id  E xp en se  T ra cke r A pp f o r e ffic ie n tly	 	\nm onit o rin g  o f e xp en se  a n d  in co m e w it h  le ss e ffo rts	\nT e ch S ta ck:  A nd ro id ,  S Q Lit e ,  G oog le  M L k it	\nA C H IE V EM EN TS	\nPala d in  o f t h e I V IT  C ham pio n s\nRece iv e d  b eca u se  o f h ig h p erfo rm an ce  o n	 	\ncrit ic a l  p hase  o f t h e p ro je ct\nD ig it a l M ile sto n e a t T C S\nCle are d  c o d in g  c h alle n g es in  P yth o n a n d	 	\nd em onstr a te d  c o m pete n cie s in  A gile	 	\nm eth o d olo g y.\nIn nova to r M ile sto n e a t T C S\nCle are d  c o d in g  c h alle n g e o n M ach in e	 	\nLe arn in g	\nwww .enhancv .com	\n	\nPow er ed b y	\nE		q	\n\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;	\n&bull;\n&bull;\n&amp;\n\n', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 15:52:25', 0),
(386, 92, 73, NULL, NULL, '73_92_17343925666993a392e3e8_Arjun_V_Menon_-_HMI_Developer.pdf', 'Arjun V Menon - HMI Developer.pdf', '. \n. \n 	 	\nARJUN V MENON	 	\nSoftware Engineer 	 	\n +91 9744816460	  	\n\ncom	 	 	\n https://www.linkedin.co\nm/in/arjun	-menon	-	\n937159141/	 	 	\n 	\n 	\nAn  inspired  android  developer  dedicated  to  continuously  developing, \nimplementing,  and  adopting  new  technologies  to  maximize  development \nefficiency  and  produce  innovative  applications.  I  have  a  total  technical \nexperience of more than 4 years &amp; passionate to	wards solving problems. 	 	\n \n 	Skills	 	\n Native Android Development ( Java , Kotlin) 	 	 \n JSON, RESTful web services. 	 	 \n Retrofit, Volley, Coroutines. 	 	 \n SQL Lite, Room DB, MySql, Shared Preferences. 	 	 \n Markup language (XML). 	 	 \n Version Control (Git, Bitbuket, SVN, Gerrit). 	 	 \n Project Management (Jira, Jenkins, Polarion, Confluence). 	 	 \n AOSP 	 	 \n Android HMI 	 	 	 	\n 	\nWork History	 	\n Senior Software Enginner	 	\nTata Elxsi, Bangalore	 	\n Worked on Android Map application using Mapbox for automotive 	 	\n Worked on Telematics CV2X project, In Android Telematics Service \nApplication. 	 	\n Testing and Debugging on Hardware for Android Telematics. 	 	\n Worked on Android HMI for Launcher App. 	 	\n Skills: Jira 	- Confluence 	- Polarion 	- Gerrit 	- AOSP 	- BinderIPC 	- Android 	\nFramework 	- Java 	- Mqtt 	- AIDL 	 	\n Programmer Analyst	 	\nCognizant, Bangalore	 	\n Worked on Google Play Protect Project. 	 	\n Worked on android security and android reverse engineering. 	 	\n Worked on Identifying security threats and malware in Playstore. 	 	\n Worked Android Malware analysis. 	 	\n Skills: Jira 	- Android Studio 	- Reverse Engineering 	- Java 	- Kotlin 	 	\n 	\n2022	-11 	- Current	 	\n2021	-09 	- 2022	-11	 	\narjunvenumenon@gmail.\n\n. \n. 	\n Software Engineer	 	\nQuest Global, Trivandrum	 	\n Software development in Android Automotive HMI 	 	\n Worked on Phonebook team of HMI, Version control using SVN. 	 	\n Developed features for Phonebook and Contacts of HMI. 	 	\n Testing and debugging of Build in Hardware. 	 	\n Skills: Jira 	- Gerrit 	- AOSP 	- BinderIPC 	- Android Studio 	- AIDL 	 	\n Software Engineer	 	\nAutocon India Pvt. Ltd, Kochi	 	\n Developed new features for proprietary Android applications used on \nphones and tablets; worked with developers to develop toptier solutions \nfor restaurant and retail customers 	 	\n Uses Coroutines for long	-running tasks (database and network access) 	 	\n Maintaine	d long and short	-range deliverables with product 	\nmanagement team according to product roadmaps 	 	\n Created custom mobile applications using native technologies 	 	\n Database access through Room persistence library. 	 	\n Android Developer	 	\nTradeasy Technologies, Kannur	 	\n Created custom mobile applications for retail customers 	 	\n Documented architecture and implementation for internal and external \nconsumption 	 	\n Applied various techniques to locate bugs and errors in applications 	 	\n Designed and built sales applications for Android platform 	 	\n Provided dedicated support and timely issue resolution to clients \nfollowing successful app launch. 	 	 	\n 	\nEducation	 	\n B-tech: 	Electronics And Communication Engineering	 	\nKannur 	University 	- Kannur	 	\nPercentage: 63 	 	\n 12th: 	Science	 	\nChapparapadava HSS 	- Kannur	 	\nPercentage: 70% 	 	\n 10th Std	 	\nChapparapadava HSS 	- Kannur	 	\nPercentage: 85% 	 	 	\n 	\nAccomplishments	 	\n  Conducted Android App Development workshops in various colleges 	 	\n Participated in workshop on Internet of Things by Innovians Technologies 	 	\n Participated in Cannovation 2018 startup exhibition of Kannur University 	 	\n 	 	 	\n. 	\n2021	-04 	- 2021	-09	 	\n2020	-08 	- 2021	-04	 	\n2019	-03 	- 2020	-08	 	\n2014	-07 	- 2018	-05	 	\n2011	-06 	- 2013	-03	 	\n2010	-06 	- 2011	-03', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 15:52:25', 0),
(387, 92, 73, 40, NULL, '73_92_8687292666993a392e59c_Gowtham_Mohanraj_HMI_Developer_Resume_1_(1).pdf', 'Gowtham    Mohanraj HMI Developer Resume 1 (1).pdf', 'ED U C ATIO N\nG OW TH AM  SA SSIS TA N T M AN AG ER	 	C O NTA C T+91 6 383311446go w tth am s6 @ gm ail.c o m ch en naiS K IL LS	Pro je ct M an ag e m en t	 	\nT eam work\nT im e M an ag e m en t\nLe ad ers h ip\nE ffe ctiv e  C om mun ic a tio n\nC rit ic a l  T hin kin g	\nV ELA LA R C O LLE G E O F\nEN GIN EER IN G A N D T EC H NO LO GY\nEle ctr o nic s &amp;  C om mun ic a tio n -  7 5%2 010  -  2 01 32009PO NNU M ATR IC U LA TIO N H R S E C\nSC H O OL\nHig h er s e co nd ary  e d uca tio n -  8 5%W ORK  E X PER IE N CEPR O JE C TS	 	P R O FIL EDyn am ic   an d  in no vativ e   in fo ta in m en t  sy ste m  exp ert  w it h  o ve r  4  ye ars   o f\nexp erie n ce   in   deve lo pin g  an d   im ple m en tin g  cu ttin g-e d ge   in   au to m otiv e\nin d ustr y  a n d  in fo rm atio n s y ste m s.  O ve r a ll  1 0 y e ars  o f e xp erie n ce  in  S o ft w are\nin d ustr y .  P ro ve n  a b ili t y  to  le ad  c ro ss-fu n ctio nal  te am s  a n d  m an ag e  p ro je cts\nfr o m  co nce p t  to   co m ple tio n,  en su rin g  se am le ss  in te gra tio n  of  m ult im ed ia ,\nn av ig atio n,  an d   co nnectiv it y   fe atu re s.  Adep t  at  le ve ra g in g  ad van ce d\nte ch no lo gie s t o  e n han ce  u se r e xp erie n ce  a n d  d riv e  m ark e t c o m petit iv e n ess.\n2 023 -  P R ESE N TM on tr a  - T I c le an  m ob il it y  p riv ate  l im it e dA ssis ta n t m an ag er	 	\nP ro d uct d eve lo p m en t &amp;  R eq uir e m en ts  h an d lin g	  -  C en tr a l R &amp; D	The  cre atio n   an d   exe cu tio n   of  m an ual  te st  ca se s  fo r  all  m od ule s  an d\nap plic a tio n s o f v e h ic le  t e le m atic s.\nT he c re atio n  o f  v e h ic le  a le rts  a n d  in fo rm atio n  th ro u g h th e te le m atic s c lo u d\nfo r m ob il e  a p plic a tio n s a n d  O EM .\nFu n ctio n al  a n d  in te g ra tio n  te stin g  o f  a p plic a tio n  fe atu re s a t  b oth  th e te st\nb en ch  a n d  v e h ic le  l e ve ls  u sin g  a  C AN  A naly ze r.\nC usto m iz in g  th e te le m atic s d ash b oard  a n d  m an ag in g  it   a cco rd in g  to  re al-\nt im e f ie ld  i s su es a n d  s e rv ic e  r e q uir e m en ts .\nD eve lo p m en t  te stin g  o f  v e h ic le  fe atu re s s u ch  a s g eo fe n cin g ,  liv e  tr a ckin g ,\nan d  v e h ic le  a le rts  a n d  A nd ro id  d eve lo p m en t i n  i n fo ta in m en t s y ste m .\nTele m atic s p erfo rm an ce  a n aly sis  t h ro u g h v a rio u s c o m petit iv e  b en ch m ark in g .\nSu p port t h e v e n d or s e le ctio n  p ro ce ss a n d  m an ag e v e n d ors  t o  e n su re  t im ely\nd eliv e ry  a n d  t h e r e q uir e d  q ualit y .\nG ood  k n ow le d ge a n d  u n d ers ta n d in g  o f  E V  a rc h it e ctu re  w it h  m ult ip le  C AN\nnetw ork s i n  t h e v e h ic le .\nP re p ara tio n   of  8D  re p orts   in   co ord in atio n   w it h   pro d uctio n   an d   cro ss-\nfu n ctio n al t e am s t o  s o lv e  c rit ic a l q ualit y  i s su es.\nE xp ertis e  i n  p re p arin g  S co p e o f R eq uir e m en ts  d ocu m en ts .\nT eam  s iz e  :  2\nI n it ia tin g  a n d  im ple m en tin g  U D S p ro to co l  a cro ss  a ll  ve h ic le  d ow nstr e am\nE C Us, c o n sid erin g  a ll a sp ects  a n d  v e rtic e s.\nS u p portin g  t h e d eve lo p m en t o f a  s in g le  c lo u d  p la tfo rm  f o r v a rio u s t e le m atic s\nu n it s .\nA ctiv e ly  in vo lv e d  in  t h e im ple m en ta tio n  a n d  v a lid atio n  o f	  t e le m atic s f e atu re s	\nsu ch  a s :\n D eep  l o g ger -	  V erif ic a tio n  a n d  v a lid atio n  o f e ach  v e h ic le  d ata  p oin t.	1.\n D eep  u p d ate r -	  D eve lo p m en t o f U D S p ro to co l i n  a ll E C Us t o  s u p port	\nF ir m ware  O ve r-T he-A ir  	(F O TA	) u p d ate s.	\n2.\nD eep  c o m man d er -  D eve lo p m en t o f v e h ic le  I m m ob il iz a tio n  s y ste m s.	3.	\nT O OLS	 	CA N oe\nC A N an aly ze r\nB us M aste r\nP -C A N\nJT A G\n\nDoco m o I n te rto u ch  I n d ia  L td  ,  B an g alo re , I n d ia	 	IT  S u p port E n g in eer	M S O utlo ok c o n fig ura tio n , b acku p  ,  r e sto re  a n d  t r o u b le sh ootin g .\nM an ag e D om ain  e n vir o n m en t f o r t w o s it e s t h ro u g h r e m ote  s u p port.\nW ir e le ss n etw ork in g  i n  D om ain  e n vir o n m en t.\nA sse m blin g , h ard w are  u p  g ra d atio n  a n d  t r o u b le sh ootin g .\nPro vid in g  s u p port t o  i n sta llin g  O S f o r t h e u se r m ach in es a n d  s e rv e rs .	\n G em alt o  M id dle  E ast F Z  L LC , D ub ai, U .A .E	                              	2 016 - 2 020	 	 2013- 2 016	 	IS S/N etw ork  a n d  S u p port E n g in eer	R esp on sib le   fo r	   	LA N  an d  W AN  n etw ork   op era tio n s,  sy ste m  d is a ste r	\nre co ve ry ,  data b ase   an d   sy ste m  backu p ,  Pla ye d   ke y  ro le   in   backu p\nm an ag em en t o f I T  d ep artm en t.\nC IS C O   :  Rou te rs ,  Sw it c h es,  Serv e r,  wir e le ss  devic e s,  an d   Acce ss\nte ch nolo g ie s.\nS tr o n g  t r o u b le sh ootin g  s k il ls  o n  L A N , W AN  a n d  W ir e le ss t e ch nolo g ie s.\nM an ag ed  u se r a cco u n ts  w it h  ( A D ) A ctiv e  D ir e cto ry  f o r t h e u se rs  t o  p ro vid e\ncre atio n ,  d ele tio n ,  u se r p erm is sio n  a n d  m an ag ed  u se r s e cu rit y  w it h  g ro u p\np olic ie s\nG ood  e xp erie n ce  i n  i n sta llin g  a n d  m ain ta in in g  t h e v ir tu al w ork sta tio n s	\n        	( E 2C )\nH an d lin g  P K I a n d  V PN  b ase d  s e cu rit y  i s su es.  p erfo rm  t r o u b le sh ootin g  e n d -\nto -e n d  b etw een  t h e s it e s.  P ro vid in g  t r a in in g  fo r t h e u se rs  t o  c o n fig ure  t h e\nce rtif ic a te  a n d  s e cu re  d om ain  w it h  t w o f a cto r a u th en tic a tio n .\nP erfo rm in g   Reg is tr a tio n   an d   Auth orit y   dutie s  to   in clu d e  ce rtif ic a te\ne n ro lm en t a n d  r e vo ca tio n .\nM an ag ed  A cce ss C on tr o l  S yste m  to  m ain ta in  a ll  th e b ad ges o f  u se rs  a n d\nvis it o rs .  T o p ro vid e p erm is sio n s fo r  th e re co m men d ed  d ep ortm en t  a n d\nse cu re d  a re a.\nIn sta llin g  G em alt o  B om gar  a p plic a tio n  fo r  a ll  th e m ach in es in  p ro d uctio n\nare a.	\nK in g sto n  I n fo  s o lu tio n s,B an g alo re .	                                       	2 020 -	  2 023	            	\n        \n       	 T est E n g in eer	\n 	\nperfo rm in g  v a lid atio n  o n  i n fo ta in m en t f e atu re s i n  a ll p ossib le  c o n d it io n s.\nV alid atin g  d if fe re n t m od ule s l ik e  U SB ,F M ,H M I a n d  P hon e	 	\nP erfo rm in g  th e ra p id  v a lid atio n  te sts   fo r  a ll  te st  c o n d it io n s  a n d  in va lid\nc a se s	 	\nP re p arin g  s o ft w are  v a lid atio n  s ta tu s r e p ort .\nD eve lo p m en t a n d  v a lid atio n  o f i n te g ra te d  T ele m atic s a n d  C lu ste r.	\n 	\nI h ave  a ctiv e ly  in it ia te d  a n d  d eve lo p ed  F O TA  im ple m en ta tio n  in  3 W  ( L 5 M ,\nL5 N ),  T ra cto r,  S C V,  a n d  H CV.  S u cce ssfu lly ,  I  h ave  g iv e n  a  d em o w it h  t w o\nve rtic e s.	 	\nI p ro p ose d  F O TA  e n tr y -le ve l c o n d it io n s a n d  c h ecklis ts  b ase d  o n  i n d iv id ual\nE C U a n d  v e h ic le  b eh avio u r,  e n su rin g  n o im pact o n  t h e e n d  c u sto m er a n d\nm ain ta in in g  v e h ic le  p erfo rm an ce .	\nL A N G UAG ES	Engli s h	 	\nIE LT S w it h  b an d  6\nT am il	 	\nS TA C K H O LD ER S	Sib ro s ,  N esh  ,  C onnectm  ,\nP ric o l  ,  E le ctr o nik a ,  A W EV ,\nSo na C om sta r ,E xid e	 	\n      \nO TH ER  I N FO	Passp o rt n o  - K 2849988	 	\nH obbie s - S ke tc h in g &amp;\nG ard en in g	 	\nT han ks	 	G O W TH AM  S A KTH IV EL	,  C hen nai,  2 4 J u n e 2 024', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-21 16:09:48', '2024-07-18 16:09:48', 0, NULL, NULL, '2024-07-18 15:52:25', 0),
(388, 92, 73, 33, NULL, '73_92_132113408266993a392e8f2_HMI_Developer-Shailendra_Semwal.docx', 'HMI Developer-Shailendra Semwal.docx', '\r\nShailendra Semwal\r\n# 3047 Janapriya Havens\r\nYalanka, Bangalore-560065)\r\n✉E-mail Id  shailendarsemwal@gmail.com☎Contact No +91-8548074898\r\n  LinkedIn: https://www.linkedin.com/in/shailendrasemwalCareer Objective:\r\nTo work with maximum potential in a challenging and dynamic environment, with an opportunity of working with diverse group of people and enhancing my professional skills with learning and experience for career growth.\r\nExperience Summary:\r\nWith 8 years of experience in Android Application Development, Android Automotive, and AMS Engineering Application Support, I bring a wealth of expertise to my roles. I have working navigation systems for Scania trucks, kitchen management apps for restaurant chains, and provided critical support for engineering applications at Black &amp;amp; Veatch.\r\nTechnical Skills:\r\nTools &ndash; Git SVN, ADB tools, QFIL Tools, AOSP\r\nLanguage &ndash;  JAVA, Kotlin, Java(Android SDK)\r\nDatabase &ndash; SQLite, MySQL.\r\nTechnology &ndash; Android,AOSPOperating System &ndash; Windows, Mac,LinexIDE &ndash;Android Studio, Eclipse,Microsoft PowerBITicketing Tools- ServiceNow, Jira, Conference, Figma\r\nAreas Of Expertise:\r\n&bull;    Familiar with the Android SDK, Eclipse, Google services and APIs.\r\n&bull;    Knowledge of SQLite, MySQL or Oracle database management system.\r\n&bull;    Proficient in design, problem-solving, and debugging.\r\n&bull;    Proficient with Developer Console in publishing and managing the application.\r\n&bull;    Knowledge in integrating web services, TCP and UDP socket programming.\r\n&bull;    Familiarity with HERE SDK Navigation. \r\n&bull;    Knowledge of Android AOSP Automotive ROM  Development.\r\n&bull;    Knowledge of Android build system.\r\n&bull;    Knowledge of Android boot process Deep Analysis.\r\n&bull;    Knowledge of Car Api, Car Services, VHAL.\r\n&bull;    Knowledge of Car Launcher.\r\n&bull;    Knowledge of Boot Animation.\r\n&bull;    Knowledge of SELinux.\r\n&bull;    Knowledge of Car Settings.\r\n&bull;    Knowledge of System UI.\r\n&bull;    Knowledge of Mobile Penetration Testing of Android Application.\r\nOrganization Experience\r\nEmployer :  L&amp;amp;T Technology Services Ltd\r\nDuration : March 2021 &ndash; Till now\r\nDesignation : Senior Engineer(Android  Developer)\r\n Project Name: -Navigation\r\nClient: Scania \r\nAs part of our Android automotive project, we are developing a navigation app specifically tailored for Scania trucks. This app aims to provide Scania truck drivers with reliable and efficient navigation assistance to optimize their driving experience. Our focus is on creating a user-friendly interface that takes into account the unique requirements of truck drivers, such as vehicle dimensions, weight restrictions, and specific road regulations. The navigation features will include truck-specific routing options, real-time traffic updates, and points of interest relevant to truck drivers, such as rest areas and truck stops. To ensure seamless integration with Scania trucks, we are collaborating closely with the client to understand their specific needs and requirements. Our development process involves leveraging the latest technologies and best practices in Android automotive development to deliver a high-quality and robust navigation solution. By working closely with Scania and leveraging our expertise in Android development, we aim to create a navigation app that enhances the driving experience for Scania truck drivers, improving efficiency and safety on the road. \r\nDDU,RIG,QFIL Tools, AOSP, Gadget Testing, HERE SDK, JIRA, Figma, Coverity static analysis.\r\nEmployer :  Barbeque Nation Hospitality Ltd\r\nDuration : August2020 &ndash; Till now\r\nDesignation : Assistant Manager(Android  Developer)\r\nProject Name:-KDS:( Hospitality Management)\r\nhttps://play.google.com/store/apps/details?id=com.bbqn.relayProject based on Hospitality Management.\r\nProject Name:- Samiksha:( ERP)\r\nhttps://play.google.com/store/apps/details?id=com.app.bbqn.samikshaEmployer :  DFoE (Digital Future of Education Pvt. Ltd.)\r\nDuration : February 2020 &ndash; August2020\r\nDesignation : Android  Research Engineer\r\nProject Name:-FRI:( Hospitality Management)\r\nhttps://play.google.com/store/apps/details?id=com.dfoe.friclienthttps://play.google.com/store/apps/details?id=com.dfoe.frimasterhttps://play.google.com/store/apps/details?id=com.dfoe.frikitchenTechnologies used:&nbsp; JSON, REST, TCP and UDP Socket Programming, SQLite Db.\r\nProject based on Hospitality Management.\r\nPayment Gateway integration using Stripe Payment, PayU.\r\ncommunication protocols Socket.\r\nOrganization Experience\r\nEmployer : Ayshwarya syndicate LLP, Bangalore\r\nDuration :August 2019 &ndash; November 2019\r\nDesignation :Software Developer\r\nProject Name:-Spark IN:\r\nhttps://play.google.com/store/apps/details?id=com.assccl.spark.coopProject based on Banking Consumer Account.\r\nPush notification is implemented using Google Firebase.\r\nPayment Gateway integration using Paytm, Razor pay;\r\nImplemented finger print access security and Device lock security.\r\nHere customer can create Health Insurance, Debit and Credit Cards, Bill Payment.\r\nEmployer :  Technoforte Software (p) Ltd\r\nDuration :  August  2018 &ndash; August  2019\r\nDesignation : Associate Engineer -Software. \r\nClient: Toyota\r\nProject Name:- Polygon:\r\nManufacturer of inventory management &amp;amp; parts tracking systems for real-time inventory control    &amp;amp; tracking serial number, date tracking, trace the movement of materials.\r\nAn Integrated ZebraBarCode scanner, library to scan the barcode.\r\nDesigned the database, UI pattern, data-flow between different modules.\r\nTesting the end to end app, database &amp;amp; web-services.\r\nEmployer : Pronto Software Solutions (p) Ltd, Bangalore\r\nDuration :  November 2016 &ndash; August 2018\r\nDesignation : Associate Software Engineer\r\nProject Name:- Sangama:\r\nClient: Karnataka Forest Department - Belagavi Circle.\r\nhttps://play.google.com/store/apps/details?id=com.pronto.sangamaSangama is an application which is designed to help the officers monitor and Update their work status online/offline.Key Features of the app are as follows: \r\nProject Name:- Cricket Score Pad:\r\nhttps://play.google.com/store/apps/details?id=com.pronto.scorepadCricket Score Pad comes closest to the cricket score card you have filled manually all this years. A scorer&rsquo;s delight, Cricket Score Pad&#039;s neat, clean and intuitive design ensures the cricket score book stays upto-the-ball without you breaking a sweat. Use Cricket Score Pad to score multiple match formats (T20 or ODI) or even custom make your own match.\r\nDesign UI pattern &amp;amp; database.\r\nIdentify and correct fix bugs\r\nEmployer : SPH Vibhava Private (p) Ltd, Bangalore\r\nDuration :  April 2016 &ndash; October 2016\r\nDesignation : Software  Developer\r\nProject Name:- SmartPropertyHunt:\r\nCertified Course\r\n4  month Java &amp;amp; Testing Training In &ldquo;ABC For java &amp;amp; Testing&rdquo; in Bangalore\r\n4 month .Net Technology Training in DUCAT Gwalior.\r\n5 month  C,C++,Core Java Training In GLOBAL ICS Delhi\r\n2 Month  Android Training in Falgee Software Development Pvt Ltd Bangalore.\r\nAcademic Background\r\nYear(s) Qualification  Board/University College/ Institute Percentage\r\n2015  Bachelor of Engineering \r\n(Information Technology) Rajiv Gandhi Proudyogiki   Vishwavidyalaya Bhopal\r\n(Madhya Pradesh)\r\nRustamji Institute of  Technology  BSF Academy Tekanpur Gwalior \r\n(Madhya Pradesh)\r\n 7.75 CGPA \r\n2012           Diploma\r\n(Computer Engineering)\r\nBoard Of Technical Education Delhi(B.T.E) BSF Polytechnic STS \r\nTigri Camp, New Delhi    68.00%\r\nPersonal Details Name : Shailendra Semwal\r\nFather&rsquo;s Name : Prakash Chandra Semwal\r\nMother&rsquo;s Name : Prabha Devi Semwal\r\nDate of birth : 06/11/1992\r\nNationality : Indian\r\nLanguages known : English, Hindi (read, write and speak)\r\nPermanent Address : Tehri Garhwal Uttarakhand \r\nDeclaration I do hereby confirm that the details furnished above are true to the best of my knowledge. I bear the responsibility for the correctness of the above-mentioned particulars.\r\nPlace: Bengaluru\r\nDate: (Shailendra Semwal)\r\n', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-22 03:52:19', '2024-07-19 03:52:19', 0, NULL, NULL, '2024-07-18 15:52:25', 0),
(389, 92, 73, NULL, NULL, '73_92_184596073466993a392ead7_HMI_Developer-Swapnil_Thamake.pdf', 'HMI Developer-Swapnil_Thamake.pdf', 'Sw ap nil  T h am ake  \nTe am  L e ad  \n                                             \nap plic a tio n i m pro ve m en ts . C urre n t p ro je ct w ork in g  o n F o rd  C re d it  ( ﬁ nte ch ) a n d  L a st p ro je ct w as w ork e d\n                                       \nsw ap 3848@ gm ail .c o m  \n\nPune, I n d ia  \nlin ke d in .c o m /in /s w ap nil - t h am ake -2 14314a0  \nWORK  E X PER IE N CE \nTe am  L e ad  \nTe ch  M ah in d ra  \n04/2 022 -  P re se n t\n, \n  Pun e \nFo rd  C re d it  A pplic a tio n : ( F in te ch ) \nLe ad in g  t o  m y 2  b ud dy&#039;s  a n d  d eve lo pin g  M obil e  A pplic a tio n\nis  b ase d  o n ﬁ nan cia l a n d  a cco unt m an ag em en t s e rv ic e s \nUse  s k il ls  C ode o ptim iz a tio n, A pplic a tio n s e cu rit y , d esig n\npatte rn s a n d  r e so lv e  l o w  p erfo rm an ce  i s su es. \n                 \n           \nAsso cia te  C onsu lt a n t \nCap gem in i I n d ia  \n02/2 020 -  0 4/2 022\n, \n  Pun e \nHSB C B an k I n dia  \nWork e d  o n F in an ce  D om ain  &amp;  B an kin g  d o m ain  a p plic a tio n.\nIm ple m en te d  s o rt in g , s e arc h in g  a lg o rit h m s a n d  d esig n\npatte rn s. \n                         \nQR c o de, T ra n sa ctio n h is to ry , R ais e  d is p ute . \nAnd ro id , K otlin , R xJav a , D ag ger 2 ,M VP, R etro ﬁ t, J e n kin s,\n                    \nConte xt, H ooks. \nApplic a tio n E ng in eer -  M obil e  A pplic a tio n\nDeve lo per \nRaw  E n g in eerin g  I n d . P vt. L td . \n08/2 018 -  0 1/2 020\n, \n  Vir a r -  M um bai \nIn  R aw  E ngin eerin g i  h ave  w ork e d  o n s p o rt s  d o m ain  p ro je cts  \n                   \n                             \nso rt in g  a n d  s e arc h in g  a lg o rit h m s. \n                 \nRetro ﬁ t, J e n kin s, G it , A W S, X M PP,F ir e b ase , C ra sh ly tic s \nMobil e  A pplic a tio n D eve lo per \nG.N .R eatil  S e rv ic e s P vt. L td .( Z ap m art .c o m ) \n05/2 016 -  0 7/2 018\n, \n  Mum bai \nZa p m art  i s  O nlin e G ro ce ry  P ro du ct B ase d  C om pan y \nReq uir e m en t &amp;  A naly sis , D esig n a n d  D eve lo p A pplic a tio ns,\nWrit e  A PI&#039;s , W ork  o n B ack -e n d  a n d  D B. \nWork e d  o n z a p m art  a p plic a tio n w hic h  b ase d  o n o nlin e\ngro ce ry  s to re . D eve lo ped  o rd er t ra ck in g  f u nctio nalit y  u sin g\nGoogle  M ap . \nAnd ro id , j a v a , V olle y, G it , B it b uck e t, S Q LLit e , F ir e b ase ,\nCra sh ly tic s. \nSK IL L S  \nAnd ro id  S D K \nJav a  \nGit h u b  \nSQ Lit e  \nRest A PI \nMyS Q L \nFir e b ase  \nRxJav a  \nSo narQ  \nAW S \nMVC \nMVVM  \nRO OM  \nJIR A  \nMock it o  \nSyste m  D esig n \nKotlin  \nMult iT h re ad in g  \nJe tp ack  \n \n    \nAlg o rit h m s \nRetro ﬁ t \nData  s tru ctu re  \nFir e b ase  \nRxJav a  \nLiv e d ata  \nReact N ativ e  \nTyp esc rip t \n    \n \n \n  \nPR O FE SSIO NAL P R O JE C TS \nFo rd  C re d it\n ( 0 4/2 022 -  P re se n t)\n \nHSB C b an kin g\n ( 0 3/2 020 -  0 4/2 022)\n \nHaw ks A re n a F a rm  S ta te  &amp;  S acra m en to  K in g &#039;s\n ( 0 1/2 019 -  0 1/2 020)\n \nJD  P ow er\n ( 0 8/2 018 -  1 2/2 018)\n \nMed ic a lw ale  D octo r A pp\n ( 0 3/2 018 -  0 7/2 018)\n \nza p m art .c o m\n ( 0 8/2 016 -  0 1/2 018)\n \nED UCATIO N \nMCA  ( M aste r i n  C om pute r A pplic a tio n) \nKIT &#039;S  I M ER  K olh ap ur \n07/2 013 -  0 6/2 016\n, \n  Kolh ap u r,M ah ara sh tra , I n dia  \nBCA  \nGopal K ris h n a G okh ale  C olle g e K olh ap ur \n06/2 009 -  0 4/2 012\n, \n  Kolh ap u r ,  M ah ara sh tra  ,  I n dia  \n12th  \nS.M .L o hia  C olle g e, K olh ap ur \n06/2 007 -  0 2/2 009\n, \n  Kolh ap u r \n10th  \nJyo tir lin g  v id ya m an d ir  V ad an ag e \n06/2 002 -  0 3/2 007\n, \n  Kolh ap u r \nIN TER EST S \nPho to gra p hy \nSin g in g  \nCric k e t \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s 	\nUnitTest	\nMVP\nAOSP	\nSplunk	CSS	  Jacoco	\n8369096660	\nMobile Application Developer with 8 years of experience in coding, team lead, architecture design and\non HSBC Bank on financial domain . I have also worked on Sports, Health Care, Automative and E-Commerce.	\nReact Native, Typescript, Android, Kotlin, MVVM,\nJWT, Jetpack, Coroutine, Git, Splunk\nDeveloped application with key features like money transfer,\nNexus, SonarQ, Git, SSL pinning, React Native,\nDeveloped application for NBA teams and Automative App\nLive score update with xmpp protocol. Used multithreading,\nAndroid, Java, Kotlin, RxJava, Dagger2, MVP, AOSP,', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 15:52:25', 0),
(390, 92, 73, NULL, NULL, '73_92_158610506566993a392ecb3_Muhammed_Shihab_HMI_Developer.pdf', 'Muhammed Shihab_HMI Developer.pdf', 'MUHAMMED SHIHAB V K	 	\nSenior Engineer Android	 HMI	 	\nThrissur, Kerala, India	 	\n+91	-9526199466	 	\nShihabvk99@gmail.com	 	\nlinkedin.com	/muhammedshihabvk	 	\ngithub.com/muhammedshihabvk	 	\nhackerrank	.com/muhammedshihabvk	 	\nProfile	 	\nEnergetic, Creative, and 	curiosity	-driven Android/Mobile	/HMI 	Developer with 4+ years of experience, I have a deep understanding 	\nof the Android ecosystem	 with 	different	 domain	s like 	Retail	(Leading brands)	 and 	Automotive	(OEM	), including the latest tools and 	\ntechnologies.  I  specialize  in  building  robust  and  efficient  Android  applications  that  provide  seamless  user  experiences.  I  ha	ve 	\nextensive knowledge in various mobile development languages, including Java, Kotlin, and Dart. 	I have experience in working with 	\nAndroid Studio, the Android SDK, and popular libraries.	 	\n \nCore Qualifications	 	\n▪ 	Native 	Android development	 	\n▪ 	Quality assurance	 	\n▪ 	App	 development life cycle	 	\n▪ 	User experience design	 	\n▪ 	Information architecture	 	\n▪ 	Agile software development methodologies	 	\nSkills	 \n▪ 	Programming Languages: Java, Kotlin, Dart	 	\n▪ 	Android Development: Android SDK, Android Studio, \nGradle, Retrofit, RxJava,	 Coroutine,	 Picasso, Glide. 	 	\n▪ 	Tools and Technologies: Git, GitHub, Bitbucket, JIRA, \nFirebase, RESTful APIs, JSON, Google Maps API.	 	\nProfessional experience	 	\nMahindra	 &amp; Mahindra	, Automotive, 	Coi	mbatore,	 Tamil Nadu	              	         	        	Sep 20	23-Present	 	Senior Engineer 	&ndash; Android HMI	 	\nI work	 as an Android Developer, focusing on creating user interfaces and functionality like battery 	\nmanagement, vehicle 	drive mode	, and gallery	, using	 structured	 MVVM architecture	 for Mahindra 	\nBorn 	Ele	ctric Vehicles	. I also worked on connecting our app with car systems using CAN signals. In 	\nteam  meetings,  I  shared  ideas  and  kept  everyone  updated  on  our  progress  and  any  new \ndevelopments. 	Working closely with the product team, I made sure our technical solutions aligned 	\nwith business needs. Even with tight deadlines, I successfully delivered results. I&#039;m known for being \nfriendly,  respectful,  and  always  ready  to  lend  a  hand.  When  faced  with 	challenges,  I&#039;m  good  at 	\nbreaking them down, finding solutions, and making decisions. Whether I&#039;m working independently \nor with a team, I&#039;m effective and adaptable.	 	\n \nSkills	:  Java,  Kotlin,  Android,	 Service,	 Content 	Provider,	 Broadcast	 Receivers	, Retrofit,  M	QTT	, 	\nMVVM,  ViewModel,  LiveData,	 Coroutine,	 Flow,	 Datastore,  Hilt, 	Car	 &amp; CarPropertyManager	 Libs	, 	\nCAN/Ethernet  Signals,	 Glide,  Git	, GitHub	, Canoe	 17,  QFIL  &amp;  Ren	esas(	Device  Flashing)	, Tera  Term, 	\nLottie Animation, Adobe After Effect for Lottie Json with Bodymovin	, Figma, Visure	, LeapX	. 	\nLitmus	7 Systems Consulting,	 Retail, Kochi	,Kerala	                                  	       	            	 Jul 2019	-Sep 2023	 	\nSenior Engineer 	&ndash; Android	 	\nI  made  a 	user	-friendly  e	-commerce  app  for  Android  that  makes  shopping  easy.  I  worked  with 	\ndifferent teams to make sure the app met all the needs and worked well. We added features like \nproduct listings, search, and payment. I also helped junior developers learn and	 grow. I&#039;m good at 	\nall parts of making an app, like testing and putting it on the app store.	 	\n \nSkills: 	Java,Kotlin,Dart,Android,Flutter,	MVVM,  MVP,  ViewModel,  LiveData,  REST  APIs,  Postman, 	\nRecyclerView,  Glide,  WebView  Retrofit/Fast	-Android	-Networking,    Gson/Jackson  Serialization, 	\nRxJava,  Moengage(Analytics,  geofence,  Notification  center),    Chucker(API  logger),Auth  Token \nHandling  with  OkHttp	 Authenticator,  Firebase(Auth,  Crashlytics)  Zendesk  (Chat),  Google  Maps, 	\nCheckout.com  (Payment),  Ticketing  Systems  (Jira/ServiceNow),  and  Git  VCS  (Bitbucket/GitHub \nRemote).	 	\nL3 Associate POS Engineer	 	\nI managed store software like Oracle Micros Point of Sale for retail shops. Every day, I did \nmaintenance for these systems. I worked with different teams to fix any problems, like POS \ndevelopers and database admins. I managed tickets and solved issues, eve	n outside of regular 	\nhours. I also made sure updates were done smoothly and used PowerShell to automate tasks for \nstores in the US and Canada.	 	\n 	\nEducation	 	\nBachelor of Technology (7.07cgpa) \nComputer science and Engineering \nKMEA Engineering College, IN APJ Abdul \nKalam Technological University 	2019	 	\n \nHobbies	 	\nPhotography, Badminton, Listening \nMusic	, Travelling,	 	\n \nLanguage	 	\nEnglish, Malayalam	 	\n \nPersonal Data	 	\n28yrs, DOB 28 March 1996 	S/O Kadher	 	\n9383	-9181	-5394(Aadhaar IN)', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 15:52:25', 0),
(391, 92, 73, NULL, NULL, '73_92_72397335666993a392ef4d_Rajat_Dogra-HMI_Developer_2.pdf', 'Rajat Dogra-HMI Developer 2.pdf', 'RA JA T D O GRA\nAndro id  A pplic a tio n  D eve lo p er	\n8329268366 / 9545898398	kakar ajat10@gmail.com	\nhttps://www .linkedin.com/in/r ajat-dogra-a24409105	Bangalore, White	\nSU M MARY\nEnthusiastic Andr oid Developer with a pr oven tr ack record in leading Andr oid IVI	 	\nsolutions and enhancing user e xperience. Skilled in Core Java, Kotlin, Android	 	\nSDK, and Android Application De velopment. Recognized for boosting customer	 	\nsatisfaction through innovative Andr oid Automotive solutions and str eamlining	 	\ndevelopment pr ocesses. Exceptional pr oblem-solving abilities and a passion for	 	\ndeveloping cutting-edge applications. Eager to contribute to impactful pr ojects	 	\nin line with the company&#039;s mission and vision.\nE X PER IE N CE\nIT  A naly st\nTata Consultancy Services	\n01/2019 - Pr esent	&nbsp;	Bangalore	\nBoosted customer satisfaction b y	 20%	 by leading the tr ansition to Andr oid	 	\nAutomotive for IVI solutions thr ough developing POCs.\nDeveloped multiple Andr oid IVI applications enhancing vehicle inter activity	 	\nand user experience.\nLed 	requir ement analysis	 for (5+ years) major pr ojects, streamlining	 	\ndevelopment and documentation pr ocesses.\nIncreased code performance b y 	20%	 by addr essing pr oduction defects using	 	\nJIRA and GitLab CI/CD .\nExperience of agile methodology such as 	SCRUM 	and 	KANBAN	.	\nDeveloped 	5+	 Andr oid applications, o verseeing full lifecycle de velopment	 	\nfrom 	concept	 to 	deplo yment	.	\nOversaw a team of 	7 developers ensuring timely and quality deliver able.	\nSK IL LS\nCor e Java	Kotlin	Andr oid Application De velopment	\nAndroid SDK	Android Jetpack	Android Testing	MVVM	\nUI/UX Design	RESTful APIs	XML	JSON	UML Diagr ams	\nGitlab CI/CD	GIT	Problem-Solving	Debugging	\nBug T racking	Requir ement Analysis	Softwar e Design	\nST R EN GTH S	\nIn nova tiv e  A ndro id  S o lu tio n s\nPr oven tr ack record in leading Andr oid IVI solutions and enhancing user	 	\nexperience.\nE ffe ctiv e  P ro b le m -S o lv in g S kil ls\nEx ceptional pr oblem-solving abilities in identifying and addr essing	 	\nproduction defects e\nStr e a m lin in g D eve lo p m en t P ro ce sse s\nRecognized for str eamlining development and documentation pr ocesses	 	\nfor major projects.\nPassio n  f o r C u ttin g-E d ge A pplic a tio n s\nEager to contribute to impactful pr ojects and develop cutting-edge	 	\napplications in line with company &#039;s vision.	\nE D UCA T IO N\nBach elo r o f E n gin eerin g i n  C om pute r	 	\nS cie n ce\nUniversity of Mumbai	\n2014 - 2018	&nbsp;	\nA CH IE V EM EN TS	\nEmplo yee of the Month\nRecognized as &#039;Emplo yee of the Month&#039; 5 times	 	\nover a span of 5+ years, sho wcasing	 	\nexceptional performance and contribution to	 	\nthe pr oject.\nHigh Performance Ratings\nReceived the highest performance r ating	 	\nconsistently over a period of 5+ years for	 	\noutstanding skill, work quality , deliverables,	 	\nownership and dedication.\nNominated for Ex cellent Work Award\nNominated for an e xcellent work awar d by TCS	 	\nJapan pr esident in r ecognition of e xceptional	 	\ncontributions.\nIVI Solution Pioneer\nLed Andr oid Automotive tr ansition, developed	 	\ncritical POCs\nAndroid IVI De velopment\nCreated andr oid IVI apps for cars lik e 	Nissan	 	\nAriya	, Nissan Rogue	, enhancing user	 	\nexperience\nE\nOptimized memory usage, impr oved	 	\napplication performance signi\nInno vative Publication\nPublished on auto colorization of gr ayscale	 	\nimages and videos using deep learning in	 	\nICSCET	\nPU BLIC A T IO N S\nAuto m atic  I m ag e a n d V id eo  C olo riz a tio n	 	\nu sin g D eep  L e a rn in g\n2018 International Confer ence on Smart City	 	\nand Emerging Technology(ICSCET)\nRaja t D ogra	\n2018	&nbsp;	\nhttps://ieee xplore.ieee.or g/document/8537308	\n10.1109/ICSCET .2018.8537308	\nE		\nq		\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n\n\n\n	\n)\n)\n)\n)\n)\n)\n)', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 15:52:25', 0),
(392, 92, 73, NULL, NULL, '73_92_3562022366993a392f316_Suresh_HMI_Developer.pdf', 'Suresh_HMI Developer.pdf', 'Suresh_Android Developer	 	\n \n \n \nSuresh Reddy B	 	 	 	 	 	 	 	 	 	Mobile	                     	 	\n 	 	 	 	 	 	 	 	 	 	    	+91 8309076590	                     	\nAndroid Developer	 	\nsuresh.bhumireddy94@gmail.com	                                                                               	 	\n \nProfessional Summary:	 	\n	 		 	\nas a 	Android	 Developer 	for	 Sasken Technologies P	vt Ltd	, Banglore	  . 	\n	 Worked as a 	Android Developer	 from 	 CssCorp	 Pvt	 Ltd	  from 	August	,20	20	 to 	25 Oct,	20	21.	 	\n	  Worked as a 	Android Developer	 from 	 Nextbrain Technologies 	Pvt	 Ltd	  from June,201	8 	\nto Ju	ly,20	20	. 	\n	 Worked as a 	Android Developer	 from 	 KRYPTOBLOCKS 	from June,2017 to 	June,2018.	 	\n	 Significant experience in Developing Mobile (Android) Application and Designing.	 	\n	 An effective communicator with excellent relationship building &amp; interpersonal skills. \nPossess a flexible &amp; detail oriented attitude.	 	\n \n \nMajor Strengths:	 	\n➢ 	Designing a	nd programming 	Android	 apps	 using with UI Components and CoreJava	. 	 	\n➢ 	End to end application development including requirement study and designing.	 	\n➢ 	Implement effective customer satisfaction strategies by identifying the root causes of \ncustomer problems.	 	\n➢ 	Clie	nts management	 	\n➢ 	Adapt in defect analysis and time managed work.	 	\n➢ 	Excellent analytic, design and problem solving skills.	 	\n➢ 	Ability to do disciplined and time managed work.	 	\n➢ 	Strictly adhere to the quality standards, following 	Android	 development guidelines and 	\nQuality system.	 	\n 	\n \nTechnical Background:	 	\n 	\n✓ 	Languages	: CoreJava, Android	,Kotlin	 	\n✓ 	Platform	: Windows,	 Linux	 	\n✓ 	Database	: Sqlite,Room.	 	\n✓ 	Framework	: Android 	SDK	 	\n✓ 	IDE:	 Android Studio	 	\nHaving 6.5 years of experience in Android Application development and currently working	\n,AOSP and Android Framework\n\n✓ 	Tools:	 Bug Tracker ,Active Collab,Gitlab	,Mantis Tracker.	 	\n✓ 	Architecture:	 MVVM, MVP, Clean Architecture.	 	\n \n \nEducational Qualification:	 	 	\n 	Completed B.Tech(E.C.E) from Madanapalle institute of Technolgy and Science 	(JNTU) 	\n,Madanapalle 	in the year 2016.	 	\n 	Completed +2  from	Sri Siddartha Junior College(A.P. board), Andhra 	Pradesh in year	2012.	 	\n 	Completed 10	thwith SathyaSai High School	 (A.P. board), Andhra Pradesh in 	year 2010.	 	\nProfessional Experience	: 	\nProject 1: 	OLA HMI ( Human Machine 	- Interface)	 	\nClient	: OLA Electric 	 	\nRole : Android Firmware Developer	 	\nProject Details:	 	\n OLA 	Electric is a electric scooter which is already available in the market and upgrowing scooter. 	\nEvery part of the scooter is controlled by CAN IDs and it includes sensors for all parts of the \nscooter.	 	\n \nRole: 	worked on HMI and display of the 	scooter,indicators,start buttons ,brakes and side stand 	\n.we used Kanzi UI for display and code base is Android and services.Worked on Wifi feature and \nbluetooth functionality.	 	\n \nProject 	2: SHIKHAR	 	\nClient	: Hindustan Unilever Ltd.	 	\nRole : Android Developer	 	\nPro	ject Details:	 	\nThis  is  a 	Business  to  Business  Android  application  by  Hindustan  Unilever  Ltd.  The  base 	\nfunctionality  of  this  app  is  to  deliver  the  parcels  to  local  stores  or  local  outlets  which  are  tied  up \nto  Unilever.  The  customer  can  order  products  and  do 	payments  in  installment  method  .This  is  a 	\nbig  program  run  by  HUL  where  the  billing  of  ordered  products  will  be  done  by  IKEA.Based  on \ncustomer  purchase  he  can  get  reward  points  and  can  utilise  those  points  while  ordering  the \nproduct.We have integrated you p	ayment and SBI banking process to this application.\n\nProject 	3: Thobey Driver	 	\nRole: 	Developer	 	\nProject Details:	 	\nThis is a laundry service app which includes three panels as they are customer, driver and vendor. \nDriver  can  receive  orders  from  customer  and  a	ssigned  by  vendor,where  thi	s  app  includes 	\nhardware 	printer  integration	 using  AIDL	 and  Google  directions  and  tracking  facility  of 	\ncustomer.  Once  an  order  is  assigned  by  vendor  then  this  driver  will  go  to  customer  location  and \nhe will collect cloths and gene	rate one QRcode for that pickup bag. Then he will deliver the cloths 	\nto same location after laundry.	 	\n \nProject 	4:  DROPR: Delivery and Transportation Service	 	\nRole: 	Developer	 	\nDescription:	 	\nThis is Indian parcel Delivery Appication with 100km Range.By using th	is app customer can assign 	\norder to driver by giving pickup and Drop locations using Google maps Drag and Drop methods as \nwell as Auto Complete address. We can deliver up to 20 Delivery Locations with parcel images \nupload option. While Driver is on Deliver	y ,Customer can able to track the Driver and can able to 	\ncontact via phone. Implemented Offline payment and Online payment (Razorpay payment \ngateway)	 	\nPlaystore Link: 	https://play.google.com/store/apps/details?id=com.app.dropr	 	\n \nProject 	5: DROPR Delivery 	Partner	 	\nRole: 	Developer	 	\nDescription:	 	\nThis app mainly used for track order status,parcel delivery app, can get order from the \ncustomer.By using change order status, He can able to change status also.View order information \nof particular order and should comp	lete order with Digital signature for verification purpose. We 	\ncan view order information of particular order and Notifies order status using push notification.	 	\n \nPlaystore Link: 	 https://play.google.com/store/apps/details?id=com.app.droprdriver	 	\n \nProject 	6: Laparalah Rider	 	\nRole: 	Developer	 	\nDescription:	 	\nAfter payments are made by our customers online, digital delivery orders with details such as\n\norder ID, order items, vendors, customer delivery addresses are generated through our \nmainframe and distributed to o	ur delivery teams so that they can pick up the orders and make 	\ndelivery to our customers. Driver can track customer location also.	 	\nDriver will get orders in two ways ,Manually assign ( admin or vendor can assign order manually \nby using assign to option) an	d Automation (order will assign automatically to the nearest 	\ndriver).Both cases driver will notified using push notification.	 	\n 	 	\nPlaystore Link: 	https://play.google.com/store/apps/details?id=com.app.laparlahdriver	   	\n \nProject 	7: Dumbo Delivery 	- cambodia	 	\nRol	e: 	Developer	 	\nDescription:	 	\nThis is Cambodia parcel Delivery Appication.By using this app customer can assign order to driver \nby giving pickup and Drop locations using Google maps Drag and Drop methods as well as \nAutocomplete address. We can deliver up to 20	 Delivery Locations with parcel images upload 	\noption. While Driver is on Delivery ,Customer can able to track the Driver and can able to contact \nvia phone. Implemented Offline payment and Online payment (Paypal payment gateway).	 	\n 	 	\nPlaystore Link: 	https://play.google.com/store/apps/details?id=com.app.dumbodelivery	 	\n \nProject 	8: Antflip Customer	 	\nRole: 	Developer	 	\nDescription:	 	\nThis is Indian parcel Delivery Appication with 100km Range.By using this app customer can assign \norder to driver by giving pickup 	and Drop locations using Google maps Drag and Drop methods as 	\nwell as Auto Complete address. We can deliver up to 20 Delivery Locations with parcel images \nupload option. While Driver is on Delivery ,Customer can able to track the Driver and can able to \ncon	tact via phone. Implemented Offline payment and Online payment (Razorpay payment 	\ngateway)	 	\nPlaystore Link: 	https://play.google.com/store/apps/details?id=com.app.antflip	 	\n \nProject 	9: Antflip 	- Driver\n\nRole: 	Developer	 	\nDescription:	 	\nThis app mainly used for track	 order status,parcel delivery app, can get order from the 	\ncustomer.By using change order status, He can able to change status also.View order information \nof particular order and should complete order with Digital signature for verification purpose. We \ncan 	view order information of particular order and Notifies order status using push notification.	 	\n 	 	\nPlaystore Link: 	 https://play.google.com/store/apps/details?id=com.app.antflip_driver 	 	\n  \n 	 	 	 	 	 	 	 	 	 	 	 	\n                                                                                                                             	                   	 	\n \n \n \n \n \n \n \n \n \n \n                                                                                                     	                                                 	Signature', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 15:52:25', 0);
INSERT INTO `resume` (`id`, `screeningId`, `adminId`, `candidateId`, `candidateDetailsId`, `resumeName`, `resumeOriginalName`, `resumeContent`, `isSkillScreened`, `isResumeScreened`, `isCron`, `isCandidate`, `candidateShortlist`, `enableInterviewReport`, `gptLanguageId`, `isInterviewAssign`, `interviewValidity`, `interviewAssignDate`, `isPsychoAssign`, `psychoValidity`, `psychoAssignDate`, `created`, `createdBy`) VALUES
(393, 92, 73, NULL, NULL, '73_92_37818924366993a392f584_Tabassum_Sayyad-HMI_Developer.docx', 'Tabassum Sayyad-HMI Developer.docx', '\r\nTABASSUM\r\nRESUME\r\n617855199279617855319294Experience Summary and Skill Set\r\nExperience Summary and Skill Set\r\ntabassum.sayyad1@gmail.comContact No: +91-9834112268\r\nResult oriented professional with 8.6 years of versatile experience in Android, Kotlin and Java technology.\r\nCurrently functioning as a Lead product Engineer with Harman.\r\nWorking on Android Automotive domain HMI, DCSM, Android Auto, CarPlay.\r\nWorked on AOSP code.\r\nInvolved pro-actively in various phases of Software Development Life Cycle in terms Analysis, Design, Development, Testing, Implementation, and Maintenance &amp;amp; Support.\r\nProficient experience in developing applications using Android using Java, Kotlin, React Native.\r\nHighly dedicated to produce professional work with highest quality and creativity.\r\nCommitment, hardworking, can grasp things quickly and think strategically.\r\nSUMMARY:\r\nGood knowledge of Android Framework API and Core Java and Kotlin.\r\nKnowledge of Design Patterns(MVP,MVVM), UI Material design(Recycler View, Coordinate layout and Constraint layout)\r\nExperience on remote data via REST and SOAP\r\nUnderstanding of JSON,XML parsing\r\nExperience in payment gateway\r\nExperience in third party libraries Retrofit, Volley, Picasso and Glide\r\nExcellent analytical and logical programming skills with a good understanding at the conceptual level\r\nGood in problem solving, communication skills and good team player\r\nAbility to learn new technologies and work in a dynamic environment and under pressure situations.\r\nHave working experience in agile and waterfall development process.\r\nExperience in Git and have basic knowledge of Jenkins configuration management tools.\r\nExperience to publish Apk on Google play store.\r\nComprehensive knowledge of React Native platform and core principle\r\nCommand over Kotlin.\r\nUsed Live Data\r\nImplemented Kotlin Coroutines for Thread Management.\r\nWorked using Room DB\r\nUsed data classes, Extension function\r\nWorked on RxjavaWorked on Jetpack component\r\nCOMPUTER SKILLS:\r\nLanguage/Platform: Kotlin, Core Java, Android, React Native, JavaScript, Apex\r\nDatabase: SQLite, Room Database, MySQL.\r\nOperating System: Win 10, Microsoft Win 7, Win 8, Ubuntu, Harmony OS\r\nEnvironment /Tools: Eclipse, Android Studio,STS, Android SDK, Git,Gerrit, BitBucketGitLab(Github),BugZilla, JIRA, Jenkins, SonarQube,VS code\r\n\r\nHarman. &ndash; BangaloreMay 2023 &ndash; Present\r\n    Project: PSA \r\n Client: Stellantis Description: The Android Automotive application for car brand called Peugeot, where car driver can   control climate, connect to mirroring projection like Android Auto or Car Play via Bluetooth or USB, able to play music by connecting to USB or Bluetooth, by projection user can connect voice call like incoming or outgoing call.\r\nTechnology: Android SDK, Java\r\n    Role:\r\n  Some of the key responsibilities while executing this project are as listed below -\r\nImplementation of features.\r\nFixing Framework Defects.\r\nWipro Ltd. &ndash; Pune, MHOCT 2020 &ndash; May 2023\r\nProject: ZRPL\r\nDescription: This application provides Wipro employees with substantial savings on ecommerce products. Employees can use this app to log in using their Wipro credentials and buy the product. This app provides a variety of brands, many of which provide substantial discounts on premium brands.\r\nTechnology: Android SDK, Kotlin, React Native\r\n    Role:\r\nPrepare solution based on understanding of the challenges.\r\nImplementation of the solution\r\nWorked in different module such as the product management, Address management and the Cart Module\r\n    Project: HR Direct\r\nDescription: The employee HR capabilities are accessed using this application. Once logged in, the user has access to timesheet, last six months&#039; worth of salary slips, and leave management. Here, employees can use the app to access their leaves and request leaves. Additionally, this application allows you to view and download an employee&#039;s pay slip.\r\nTechnology: Android SDK, Kotlin, React native\r\n    Role:\r\nUnderstand the various challenges faced by employee, management and HR and document the challenges in detail.\r\nDesign and development of the solution\r\nImplementation of the solution\r\nDelivered the project with 0 post-delivery defect\r\nTech Mahindra &ndash; Pune, MHAug 2019 &ndash; Oct 2020\r\n    Project: Messaging App\r\n   Client: HMD Global\r\nDescription: This application offers its users chat (RCS) and texting (MMS, SMS). Everyone has access to group texts and the ability to share images, GIFs, Emojis, videos, and voice communications.\r\nTechnology: Android SDK, Java\r\n     Role:\r\nDesign and development of the solution.\r\nImplementation of the solution.\r\nDevelopment of user friendly UI/UX added additional features like auto deletion of messages, auto texting at scheduled time and other features.\r\nBlue Planet Info Solutions (India) Pvt. LtdJan 2016 &ndash; Aug 2019\r\n \r\nWorked on various products across multiple domains. Product were developed using Android, React native and Java. Below is the list of products developed.\r\nSmartCookie Application which is a student teacher reward system\r\nOne Bay TouchPill Box\r\nTravel PillBoxVirtual PillBoxiTake-med\r\nSafety on Wheels\r\nKnow Your Medi\r\nEducation\r\nAmrutvahini College of Engineering, SangamnerBE in Information Technology | 2012-2015 | Percentage : 60%\r\nPVVP College of Engineering, LoniDiploma in Information Technology | 2009-2012 | Percentage : 67.25%\r\nSharda Kanya Vidya Mandir, RahataSecondary (12th Standard) | 2002-2003 | Percentage : 45.00%\r\nChandak Kanya Vidya Mandir, SinnarSecondary (10th Standard) | 2000-2001 | Percentage : 54.00%\r\nPersonal Details\r\nFull Name:Tabassum Abdul Latif Sayyad\r\nDate Of Birth:22nd May 1986\r\nGender:Female\r\nNationality:Indian\r\nLanguages Known:English, Hindi and Marathi\r\nAddress:Rabiya Nagar, behind Shri Hari hospital, Rahata 423107, Maharashtra.\r\nDeclaration\r\nI hereby declare that above mentioned information is genuine and true to the best of my knowledge.\r\nDate:/  / 2024Sincerely\r\nPlace:  Rahata(Tabassum Sayyad)\r\n', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 15:52:25', 0),
(394, 92, 73, NULL, NULL, '73_92_165843090266993a392f7b2_Vishwas_HMI_Developer.pdf', 'Vishwas HMI Developer.pdf', 'Pag e 1  o f 2  \nWORK  E X PER IE N CE :  \nMah in d ra  &amp;  M ah in d ra  L td  (  M ah in d ra  S o ft w are  D efin ed\nVeh ic le  C en te r )  \nSen io r S o ft w are  E n g in eer (  L 7-O pera tio nal  )  \n10 /2 0 23 -  P re se n t\n, \n  Coim bato re  \nFu ll  T im e \nWork e d  a s H M I  D eve lo p er  fo r  M ah in d ra  V eh ic le s a t M SD VC b y E le vatin g  c lu ste r\nfe atu re s w it h  k o tlin  &amp;  J a v a. \nEn han ce d  IV I  M ed ia   ap plic a tio n  b y  im ple m en tin g   ad van ce d  so urc e   se le ctio n\nfe atu re s a n d  f u lf illin g  n ew  r e q uir e m en ts ,  o p tim iz in g  f u nctio nalit y  t o  m eet s p ecif ic\npro je ct o b je ctiv e s. \nSp earh ead ed  th e d eve lo p m en t  o f  S en try  M od e,  P ark  A pp,  M yV eh ic le ,  A m bie n t\nLig hts   IV I \nApplic a tio ns,  in co rp ora tin g   esse n tia l  fe atu re s  to   en han ce   use r\nexp erie n ce  a n d  S ecu rit y . \nSu cce ssfu lly   in te g ra te d   Vid eo   Pla y e r,  Exo   Pla y e r  &amp;  sc re en sh o t  fu nctio n\nim ple m en ta tio ns,  e n ric h in g  th e a p plic a tio n w it h  se am le ss  m ult im ed ia  p la y b ack\nca p ab ilit ie s. \nIm ple m en te d  s e ekb ar f u nctio nalit y  w it h in  t h e a p plic a tio n,  e n han cin g  u se r c o ntro l\nan d  n av ig atio n t h ro ug h v id eo  p la y b ack . \nLe ve ra g ed   JIR A  to   cre ate   co m pre h en siv e   te st  se ts ,  stre am lin in g   th e  te stin g\npro ce ss a n d  e n su rin g  t h o ro ug h c o ve ra g e o f U I e le m en ts  a n d  f u nctio nalit ie s. \nCond ucte d  U I  t e stin g  a n d  in stru m en ta tio n t e stin g  t o  id en tif y  a n d  re ctif y  is su es,\nth ere b y e n han cin g  t h e o ve ra ll  u sa b ilit y  a n d  p erf o rm an ce  o f t h e a p plic a tio n. \nExp ert  in  a ctiv e ly  re so lv in g  B ug s fo r  a  w id e a rra y  o f  a p plic a tio ns,  s p ecia liz in g  in\nboth   se lf - d eve lo p ed   ap plic a tio ns  an d   fo r  In -V eh ic le   In fo ta in m en t  (  IV I  )\nap plic a tio ns. \nUtiliz e d  C A N oe a n d  V eh ic le  S p y s o ft w are  to  p erf o rm  c o m pre h en siv e  h ard w are\nte stin g  o f (C A N )  a n d  (E C U )  s ig nals  f o r V eh ic le  T e stin g ,  e n su rin g  s y ste m  r e lia b ilit y\nan d  f u nctio nalit y  t h ro ug h d eta ile d  s ig nal  a n aly sis  a n d  t ro ub le sh o otin g . \nCap gem in i  En g in eerin g   (  R &amp; D Su b sid ia ry   of \nCap gem in i\nGro u p  )  \nSo ft w are  E n g in eerin g  L e ad  (  P ro fe ssio nal  I / B 1 )  \n04/2 0 23 -  1 0 /2 0 23\n, \n  Ban g alo re  \nFu ll  T im e \nSp ecia liz e d   in   co nnectiv it y   wit h   Apple   devic e s  an d   work e d   on  Apple &#039;s\nte ch no lo gie s s u ch  a s iA P1,  iA P2 a n d  A pple  C ar P la y . \nMan ag ed   a  te am  fo r  deve lo p m en t  of  Apple   co nnectiv it y   fo r  Auto m otiv e\nin fo ta in m en t a n d  m an ag in g  A pple &#039;s  c e rt if ic a tio n p ro ce ss g lo b ally . \nSp earh ead ed   th e  Connectiv it y   dom ain   fo r  sm art   pho ne  in te g ra tio n  w it h\nau to m otiv e  in fo ta in m en t a n d  p ro je ctio n t e ch no lo gie s. \nSp earh ead ed  th e  In fo ta in m en t  sy ste m  an d  re sp onsib le   fo r  han d lin g   m ult ip le\nap plic a tio ns  a n d  re sp onsib le  fo r  d eve lo p m en t  o f  A nd ro id  In fo ta in m en t  S yste m\nwhic h  in clu d es w ork in g  w it h  w ir e le ss p ro to co ls . \nHan d le d  a  t e am  fo r  d esig n a n d  d eve lo p m en t fo r  S m art  P ho ne C onnectiv it y  a n d\nPro je ctio n t e ch no lo gie s in  C onnecte d  C ars . \nHav e  g o od  u nd ers ta n d in g  o f  iA P1,  IA P2,  A O SP  A nd ro id  C ar  P la y  C ontro l  B onjo ur\nse rv ic e  a n d  p erf o rm an ce  t u nin g  o f A pple  C ar P la y  s o lu tio n f o r M Fi  c e rt if ic a tio n. \nSK IL LS  /  T O OLS  :  \nAnd ro id  A pplic a tio n D eve lo p m en t \nCore  J a v a \nGen eric  F ra m ew ork  \nHA L L a y e r \nJa v a 8  \nC P ro gra m min g  L a n g uag e \nC++ \nAnd ro id  T e le p ho ny \nAUTO SA R \nIn fo ta in m en t H ard w are  T e stin g  \nSo narc u b e \nJIR A  \nMVVM  \nIn stru m en ta tio n T e stin g  (  U I T e stin g  )  \nRo om  D ata b ase  \nPerf o rm an ce  T e stin g  \nAD AS \nJIR A  X -R ay  \nGIT H U B \nKotlin  \nKotlin  C oro utin es \nLIN UX \nAnd ro id  S D K \nNav ig atio n C om ponen t \nAuto m otiv e  I n fo ta in m en t \nAO SP  \nAnd ro id  A uto  P ro je ctio n \nApple  C ar P la y  \nTh ir d  P art y  L ib ra rie s &amp;  A PI&#039;s  \nMult im ed ia  I n fo ta in m en t \nFig m a(U I/ U X) \nFlu tte r \nGoogle  P la y  S to re  \nDart  P ro gra m min g  \nBin d er I P C  \nApplic a tio n S ecu rit y  \nSA ST /  D AST \nAnd ro id  F ra m ew ork  \nAnd ro id  A pp D eve lo p m en t \nAID L /  H ID L \nUnit  T e stin g  \nPen etra tio n T e stin g  \nTe le m atic s \nPro je ctio n T e ch no lo gy \nConnectiv it y  \nGIT  \nGIT H U B \nCA N oe \nVeh ic le  S p y \nRA D -G ig asta r \nPR O JE C TS :  \nCogniz a n t :  G oogle  P la y  P ro te ct (  G .P .P  )\n ( 1 2 /2 0 20  -  0 4/2 0 20 )\n \nCap gem in i  :  H A RM AN  (  T o yo ta  T A S70 0 )\n ( 0 4/2 0 23 -  1 0 /2 0 23)\n \nMah in d ra  &amp;  M ah in d ra  :  M ah in d ra  E le ctric  S U Vs H M I I V I\nApplic a tio ns (  B E.0 5,  B E.0 7,  B E.R A LL-E ,  X U V.e 8 ,  X U V.e 9\n ( 1 0 /2 0 23 -  P re se n t)\n Ach ie ve m en ts /T a sk s \nTa sk s \nhk.v is h w as2 0 23@ gm ail.c o m  \n+91 :  7 9 75 35 0 95 8  \nBan g alo re ,  I N DIA  \nlin ke d in .c o m /in /v is h w as-h -k -0 610 4616 6 \nVIS H W AS H  K  \nAnd ro id  A uto m otiv e  H M I / F ra m ew ork / I n fo ta in m en t\nDeve lo p er \nAn e n th usia stic  M ob ile  A pplic a tio n D eve lo p er  (  S o ft w are  E n g in eer  L e ad  )  w it h  a\nro b ust  A nd ro id  Secu rit y   &amp;  p ro gra m min g  exp osu re   h av in g  clo se   to  4  ye ars   o f\nexp erie n ce  in  A nd ro id  H M I/ S D K,  R eve rs e  e n g in eerin g  w it h  h an d s o n e xp ert is e  in\nko tlin ,  J a v a,  F lu tte r,  A nd ro id  S tu d io ,  G IT ,  J IR A  a n d  A uto m otiv e  P ro je ctio n D om ain\nConnectiv it y .  C urre n tly  w ork in g  a s a  S en io r E n g in eer in  M ah in d ra  &amp;  M ah in d ra  \nin  t h e\nAuto m otiv e  so ft w are  la n e a s  a  d ed ic a te d  a n d  fo cu se d  H M I  e n g in eer  p rim arily\nfo cu sin g  o n d eve lo p in g  I V I a p plic a tio ns f o r N ext-G en  M ah in d ra  E V  V eh ic le s.\n\nPag e 2  o f 2  \nWORK  E X PER IE N CE :  \nCog niz a n t T ech nolo g y S o lu tio n s (  C TS )  \nTe ch nic a l  L e ad  (  A pplic a tio n D eve lo p m en t &amp;  A nd ro id  S ecu rit y\nLe ad  )  \n12 /2 0 20  -  0 4/2 0 23\n, \n  Ban g alo re  \nFu ll  T im e \nExp ert is e   in   re ve rs e -e n g in eerin g   an d  co d e-le ve l  se cu rit y   au d it in g ,  as  w ell  as\nexp erie n ce  in  h an d lin g  o b fu sc a te d  c o d es o f a n d ro id  a p plic a tio ns. \nGood  E xp osu re  in  c o nd uctin g  S ecu rit y  T e stin g  o f  b oth  S A ST a n d  D AST a n d  to\nsa fe g uard  a p plic a tio n c o d e f ro m  m alw are  s u ch  a s s p yw are ,  p his h in g ,  r a n so m ware ,\ntro ja n s,  b ack d oor,  r o otin g  a n d  o th er c y b er t h re ats . \nPerf o rm in g  in te rn al  a n d  e xte rn al  v u ln era b ilit y  a sse ssm en ts  a n d  p erf o rm in g  d ata\nan aly sis  a n d  c re atin g  d ete ctio n r o utin es f o r d if fe re n t in te rn al  p ip elin es. \nExp erie n ce  in  M alw are  a n aly sis  o n A nd ro id  M ob ile  p la tfo rm ,  id en tif y  t h re ats  a n d\ncla ssif y  t h em  a cco rd in g  t o  t h eir  f a m ily . \nCond ucte d  M alw are  A ud it in g  o f c lo se  t o  1 0 ,0 00 A nd ro id  A pplic a tio ns in  t h e\nMuW S,  P SL t ra ck s a s a  S M E. \nED UCA TIO N :  \nM.T ech  (  U niv ers it y  V is v esv ara y a C olle g e o f E n g in eerin g  )  \nCom pute r S cie n ce  &amp;  E n g in eerin g  \n10 /2 0 18  -  1 2 /2 0 20\n, \n  Ban g alo re  \n8.9 3 C G PA\n  PU BLIC A TIO NS :  \nTru st M an ag em en t f o r S erv ic e -O rie n te d  S Io T S yste m s \nPub lis h er :  A CM  D ig it a l  L ib ra ry  \nhttp s:/ /d oi.o rg /10 .1 14 5/3 4 46999.3 4 476 35  \nTa sk s \nGra d e', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 15:52:25', 0),
(395, 93, 1, NULL, NULL, '1_93_17994541566994f690d71e_Ajay_Chaudhari_-_HMI_Developer.pdf', 'Ajay Chaudhari - HMI Developer.pdf', '/  	\nA JAY  C H AU DH ARI\nSoft w are  D eve lo p er	\narc h au d hari1 4 0 2@ gm ail. c o m	h ttp s:/ /w ww.lin ke d in .c o m /in /a ja y -\nc h au d hari- 0 15 6 ba16 9/	\nK an ag aw a, J a p an	\nS U M MARY\nExp erie n ce d  S oft w are  D eve lo p er w it h  o ve r 4 .3  y e ars  s p ecia liz in g  in  A nd ro id -\nbase d  A uto m otiv e  In fo ta in m en t s y ste m s 	 \n 	\nP ostg re S Q L,  a n d  O doo.  I  a m  e ag er t o  c o lla b ora te  o n a d va n cin g  c u ttin g -e d ge	 	\nte ch no lo g y a n d  d eliv e rin g  e xc e p tio nal  r e su lt s .\nE X PER IE N CE\nOnsit e  D eve lo p m en t E ngin eer\nTata  C on su lt a n cy S erv ic e s L td	\n0 5/2 0 24	&nbsp;	K an ag aw a,  J a p an	\nA ssig ned  F e atu re :  R ad io  	 	\nR ad io ,  P od ca st)\nO nsit e  S PO C f o r R ad io  f e atu re ,  C lie n t c o m mun ic a tio n,  M an ag e S O P /  Q LU	 	\n/ M ain lin e d eliv e rie s f o r N is sa n  V eh ic le s,  B ug  t r ia g in g  a n d  f ix in g\nW ork in g  w it h  c ro ss-fu n ctio nal  t e am s s u ch  a s X peri,   L G ,  G oog le ,  B osc h ,	 	\netc .\nT e ch S ta ck:  A nd ro id ,  K otlin ,  J a va ,  A O SP,  A ASP	\nS yste m s E ngin eer\nTata  C on su lt a n cy S erv ic e s L td	\n0 1/2 0 22 	&nbsp;	G an d hin ag ar,  In d ia	\nN is sa n  IV I  f e atu re s:  T e le m atic s 	 	\nC onnm an  \nF i,   a n d  H ots p ot).\nH M I  d eve lo p m en t t h at w ork s w it h  A O SP a n d  H AL p ro vid ed  b y L G  a n d	 	\nB osc h ,  f e atu rin g  1 0 0\nB uilt  p yth o n s c rip t t h at r e d uce d  S ST R g en era tio n t im e b y 8 0 %\nTe ch S ta ck:  A nd ro id ,  K otlin ,  J a va	\nJ r. A pplic atio n  E ngin eer\nTin yE R P P vt. L td	\n1 0 /2 0 20  	&nbsp;	A hm ed ab ad ,  In d ia	\nO doo:  E R P B usin ess S uit e  o f o p en -s o urc e  b usin ess a p ps c o ve rin g  C RM ,	 	\neC om merc e ,  A cco un tin g ,  In ve n to ry ,  P O S e tc\nD eve lo p m en t o f c u sto m  m od ule s a s p er c lie n ts &#039;  n eed s.  A ddre sse d  m ain ly	 	\ng en eric  &amp;  s p ecif ic  is su e s d urin g  d ata b ase  u p gra d es.  1  g en eric  f ix  c a n	 	\nre so lv e  r o ug hly  1 0  C lie n ts  d ata b ase  u p gra d e is su e s\nTe ch S ta ck:  P yth o n,  P ostg re sq l,   J S ,  U bun tu	\nP yth on /O doo D eve lo p er\nBro w se ln fo  P vt. L td	\n0 3 /2 0 20  	&nbsp;	A hm ed ab ad ,  In d ia	\nD eve lo p ed  C usto m  L ib ra ry  m an ag em en t O doo A pp,  P ro d uct Q ualit y	 	\nA ssu ra n ce  A pp u sin g  g en eric  m od ule s\nC ontr ib ute d  t o  e xis tin g  O doo A pps lik e  B atc h  P ay m en t d urin g  in vo ic in g\nTe ch S ta ck:  P yth o n,  J S ,  O doo	\nE D U CATIO N\nBach elo r o f E ngin eerin g\nSA L E n g in eerin g  A nd  T e ch nic al I n stit u te , G TU	\n04 /2 0 17  	&nbsp;	A hm ed ab ad ,  In d ia	\nGP A	\n8.2 7	10	\nC om pute r E ng in eerin g  M ajo r	\nS KIL LS\nTe ch S ta ck\nA nd ro id	J av a	K otlin	P yth on	\nO doo	P ostg re sq l	M atp lo tL ib	\nN um py	O pen C V	Pan d as	S eab orn	\nS kle arn	G it	\nT e ch nic al  E xp ert is e\nA uto m otiv e  I n fo ta in m en t f o r C CS\nER P S oft w are  	M ac h in e L e arn in g	\nP R O JEC TS\nAuto m atic  A tte n dan ce  S yste m	\nhttp s:/ /g it h ub .c o m /A jja rv is /A uto m atic _A tte n d an ce _S\ny ste m	\nF ace  R eco g nit io n-b ase d  A uto m atic  A tte n d an ce	 	\nS yste m  u sin g  C CTV  f o r r e al- tim e s tu d en t	 	\natte n d an ce .	\nTe ch S ta ck:  P yth o n,  T kin te r,  X lr d ,  X ls x w rit e r,	 	\nO pen C v	\nIn diM on ey : A n E xp en se  T ra cke r A pp	\nhttp s:/ /g it h ub .c o m /A jja rv is /In d iM oney	\nA nd ro id  E xp en se  T ra cke r A pp f o r e ffic ie n tly	 	\nm onit o rin g  o f e xp en se  a n d  in co m e w it h  le ss e ffo rts	\nT e ch S ta ck:  A nd ro id ,  S Q Lit e ,  G oog le  M L k it	\nA C H IE V EM EN TS	\nPala d in  o f t h e I V IT  C ham pio n s\nRece iv e d  b eca u se  o f h ig h p erfo rm an ce  o n	 	\ncrit ic a l  p hase  o f t h e p ro je ct\nD ig it a l M ile sto n e a t T C S\nCle are d  c o d in g  c h alle n g es in  P yth o n a n d	 	\nd em onstr a te d  c o m pete n cie s in  A gile	 	\nm eth o d olo g y.\nIn nova to r M ile sto n e a t T C S\nCle are d  c o d in g  c h alle n g e o n M ach in e	 	\nLe arn in g	\nwww .enhancv .com	\n	\nPow er ed b y	\nE		q	\n\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;	\n&bull;\n&bull;\n&amp;\n\n', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 17:22:49', 0),
(396, 93, 1, NULL, NULL, '1_93_214493262266994f690d90e_Arjun_V_Menon_-_HMI_Developer.pdf', 'Arjun V Menon - HMI Developer.pdf', '. \n. \n 	 	\nARJUN V MENON	 	\nSoftware Engineer 	 	\n +91 9744816460	  	\n\ncom	 	 	\n https://www.linkedin.co\nm/in/arjun	-menon	-	\n937159141/	 	 	\n 	\n 	\nAn  inspired  android  developer  dedicated  to  continuously  developing, \nimplementing,  and  adopting  new  technologies  to  maximize  development \nefficiency  and  produce  innovative  applications.  I  have  a  total  technical \nexperience of more than 4 years &amp; passionate to	wards solving problems. 	 	\n \n 	Skills	 	\n Native Android Development ( Java , Kotlin) 	 	 \n JSON, RESTful web services. 	 	 \n Retrofit, Volley, Coroutines. 	 	 \n SQL Lite, Room DB, MySql, Shared Preferences. 	 	 \n Markup language (XML). 	 	 \n Version Control (Git, Bitbuket, SVN, Gerrit). 	 	 \n Project Management (Jira, Jenkins, Polarion, Confluence). 	 	 \n AOSP 	 	 \n Android HMI 	 	 	 	\n 	\nWork History	 	\n Senior Software Enginner	 	\nTata Elxsi, Bangalore	 	\n Worked on Android Map application using Mapbox for automotive 	 	\n Worked on Telematics CV2X project, In Android Telematics Service \nApplication. 	 	\n Testing and Debugging on Hardware for Android Telematics. 	 	\n Worked on Android HMI for Launcher App. 	 	\n Skills: Jira 	- Confluence 	- Polarion 	- Gerrit 	- AOSP 	- BinderIPC 	- Android 	\nFramework 	- Java 	- Mqtt 	- AIDL 	 	\n Programmer Analyst	 	\nCognizant, Bangalore	 	\n Worked on Google Play Protect Project. 	 	\n Worked on android security and android reverse engineering. 	 	\n Worked on Identifying security threats and malware in Playstore. 	 	\n Worked Android Malware analysis. 	 	\n Skills: Jira 	- Android Studio 	- Reverse Engineering 	- Java 	- Kotlin 	 	\n 	\n2022	-11 	- Current	 	\n2021	-09 	- 2022	-11	 	\narjunvenumenon@gmail.\n\n. \n. 	\n Software Engineer	 	\nQuest Global, Trivandrum	 	\n Software development in Android Automotive HMI 	 	\n Worked on Phonebook team of HMI, Version control using SVN. 	 	\n Developed features for Phonebook and Contacts of HMI. 	 	\n Testing and debugging of Build in Hardware. 	 	\n Skills: Jira 	- Gerrit 	- AOSP 	- BinderIPC 	- Android Studio 	- AIDL 	 	\n Software Engineer	 	\nAutocon India Pvt. Ltd, Kochi	 	\n Developed new features for proprietary Android applications used on \nphones and tablets; worked with developers to develop toptier solutions \nfor restaurant and retail customers 	 	\n Uses Coroutines for long	-running tasks (database and network access) 	 	\n Maintaine	d long and short	-range deliverables with product 	\nmanagement team according to product roadmaps 	 	\n Created custom mobile applications using native technologies 	 	\n Database access through Room persistence library. 	 	\n Android Developer	 	\nTradeasy Technologies, Kannur	 	\n Created custom mobile applications for retail customers 	 	\n Documented architecture and implementation for internal and external \nconsumption 	 	\n Applied various techniques to locate bugs and errors in applications 	 	\n Designed and built sales applications for Android platform 	 	\n Provided dedicated support and timely issue resolution to clients \nfollowing successful app launch. 	 	 	\n 	\nEducation	 	\n B-tech: 	Electronics And Communication Engineering	 	\nKannur 	University 	- Kannur	 	\nPercentage: 63 	 	\n 12th: 	Science	 	\nChapparapadava HSS 	- Kannur	 	\nPercentage: 70% 	 	\n 10th Std	 	\nChapparapadava HSS 	- Kannur	 	\nPercentage: 85% 	 	 	\n 	\nAccomplishments	 	\n  Conducted Android App Development workshops in various colleges 	 	\n Participated in workshop on Internet of Things by Innovians Technologies 	 	\n Participated in Cannovation 2018 startup exhibition of Kannur University 	 	\n 	 	 	\n. 	\n2021	-04 	- 2021	-09	 	\n2020	-08 	- 2021	-04	 	\n2019	-03 	- 2020	-08	 	\n2014	-07 	- 2018	-05	 	\n2011	-06 	- 2013	-03	 	\n2010	-06 	- 2011	-03', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 17:22:49', 0),
(397, 93, 1, NULL, NULL, '1_93_4540281866994f690dac2_Gowtham_Mohanraj_HMI_Developer_Resume_1_(1).pdf', 'Gowtham    Mohanraj HMI Developer Resume 1 (1).pdf', 'ED U C ATIO N\nG OW TH AM  SA SSIS TA N T M AN AG ER	 	C O NTA C T+91 6 383311446go w tth am s6 @ gm ail.c o m ch en naiS K IL LS	Pro je ct M an ag e m en t	 	\nT eam work\nT im e M an ag e m en t\nLe ad ers h ip\nE ffe ctiv e  C om mun ic a tio n\nC rit ic a l  T hin kin g	\nV ELA LA R C O LLE G E O F\nEN GIN EER IN G A N D T EC H NO LO GY\nEle ctr o nic s &amp;  C om mun ic a tio n -  7 5%2 010  -  2 01 32009PO NNU M ATR IC U LA TIO N H R S E C\nSC H O OL\nHig h er s e co nd ary  e d uca tio n -  8 5%W ORK  E X PER IE N CEPR O JE C TS	 	P R O FIL EDyn am ic   an d  in no vativ e   in fo ta in m en t  sy ste m  exp ert  w it h  o ve r  4  ye ars   o f\nexp erie n ce   in   deve lo pin g  an d   im ple m en tin g  cu ttin g-e d ge   in   au to m otiv e\nin d ustr y  a n d  in fo rm atio n s y ste m s.  O ve r a ll  1 0 y e ars  o f e xp erie n ce  in  S o ft w are\nin d ustr y .  P ro ve n  a b ili t y  to  le ad  c ro ss-fu n ctio nal  te am s  a n d  m an ag e  p ro je cts\nfr o m  co nce p t  to   co m ple tio n,  en su rin g  se am le ss  in te gra tio n  of  m ult im ed ia ,\nn av ig atio n,  an d   co nnectiv it y   fe atu re s.  Adep t  at  le ve ra g in g  ad van ce d\nte ch no lo gie s t o  e n han ce  u se r e xp erie n ce  a n d  d riv e  m ark e t c o m petit iv e n ess.\n2 023 -  P R ESE N TM on tr a  - T I c le an  m ob il it y  p riv ate  l im it e dA ssis ta n t m an ag er	 	\nP ro d uct d eve lo p m en t &amp;  R eq uir e m en ts  h an d lin g	  -  C en tr a l R &amp; D	The  cre atio n   an d   exe cu tio n   of  m an ual  te st  ca se s  fo r  all  m od ule s  an d\nap plic a tio n s o f v e h ic le  t e le m atic s.\nT he c re atio n  o f  v e h ic le  a le rts  a n d  in fo rm atio n  th ro u g h th e te le m atic s c lo u d\nfo r m ob il e  a p plic a tio n s a n d  O EM .\nFu n ctio n al  a n d  in te g ra tio n  te stin g  o f  a p plic a tio n  fe atu re s a t  b oth  th e te st\nb en ch  a n d  v e h ic le  l e ve ls  u sin g  a  C AN  A naly ze r.\nC usto m iz in g  th e te le m atic s d ash b oard  a n d  m an ag in g  it   a cco rd in g  to  re al-\nt im e f ie ld  i s su es a n d  s e rv ic e  r e q uir e m en ts .\nD eve lo p m en t  te stin g  o f  v e h ic le  fe atu re s s u ch  a s g eo fe n cin g ,  liv e  tr a ckin g ,\nan d  v e h ic le  a le rts  a n d  A nd ro id  d eve lo p m en t i n  i n fo ta in m en t s y ste m .\nTele m atic s p erfo rm an ce  a n aly sis  t h ro u g h v a rio u s c o m petit iv e  b en ch m ark in g .\nSu p port t h e v e n d or s e le ctio n  p ro ce ss a n d  m an ag e v e n d ors  t o  e n su re  t im ely\nd eliv e ry  a n d  t h e r e q uir e d  q ualit y .\nG ood  k n ow le d ge a n d  u n d ers ta n d in g  o f  E V  a rc h it e ctu re  w it h  m ult ip le  C AN\nnetw ork s i n  t h e v e h ic le .\nP re p ara tio n   of  8D  re p orts   in   co ord in atio n   w it h   pro d uctio n   an d   cro ss-\nfu n ctio n al t e am s t o  s o lv e  c rit ic a l q ualit y  i s su es.\nE xp ertis e  i n  p re p arin g  S co p e o f R eq uir e m en ts  d ocu m en ts .\nT eam  s iz e  :  2\nI n it ia tin g  a n d  im ple m en tin g  U D S p ro to co l  a cro ss  a ll  ve h ic le  d ow nstr e am\nE C Us, c o n sid erin g  a ll a sp ects  a n d  v e rtic e s.\nS u p portin g  t h e d eve lo p m en t o f a  s in g le  c lo u d  p la tfo rm  f o r v a rio u s t e le m atic s\nu n it s .\nA ctiv e ly  in vo lv e d  in  t h e im ple m en ta tio n  a n d  v a lid atio n  o f	  t e le m atic s f e atu re s	\nsu ch  a s :\n D eep  l o g ger -	  V erif ic a tio n  a n d  v a lid atio n  o f e ach  v e h ic le  d ata  p oin t.	1.\n D eep  u p d ate r -	  D eve lo p m en t o f U D S p ro to co l i n  a ll E C Us t o  s u p port	\nF ir m ware  O ve r-T he-A ir  	(F O TA	) u p d ate s.	\n2.\nD eep  c o m man d er -  D eve lo p m en t o f v e h ic le  I m m ob il iz a tio n  s y ste m s.	3.	\nT O OLS	 	CA N oe\nC A N an aly ze r\nB us M aste r\nP -C A N\nJT A G\n\nDoco m o I n te rto u ch  I n d ia  L td  ,  B an g alo re , I n d ia	 	IT  S u p port E n g in eer	M S O utlo ok c o n fig ura tio n , b acku p  ,  r e sto re  a n d  t r o u b le sh ootin g .\nM an ag e D om ain  e n vir o n m en t f o r t w o s it e s t h ro u g h r e m ote  s u p port.\nW ir e le ss n etw ork in g  i n  D om ain  e n vir o n m en t.\nA sse m blin g , h ard w are  u p  g ra d atio n  a n d  t r o u b le sh ootin g .\nPro vid in g  s u p port t o  i n sta llin g  O S f o r t h e u se r m ach in es a n d  s e rv e rs .	\n G em alt o  M id dle  E ast F Z  L LC , D ub ai, U .A .E	                              	2 016 - 2 020	 	 2013- 2 016	 	IS S/N etw ork  a n d  S u p port E n g in eer	R esp on sib le   fo r	   	LA N  an d  W AN  n etw ork   op era tio n s,  sy ste m  d is a ste r	\nre co ve ry ,  data b ase   an d   sy ste m  backu p ,  Pla ye d   ke y  ro le   in   backu p\nm an ag em en t o f I T  d ep artm en t.\nC IS C O   :  Rou te rs ,  Sw it c h es,  Serv e r,  wir e le ss  devic e s,  an d   Acce ss\nte ch nolo g ie s.\nS tr o n g  t r o u b le sh ootin g  s k il ls  o n  L A N , W AN  a n d  W ir e le ss t e ch nolo g ie s.\nM an ag ed  u se r a cco u n ts  w it h  ( A D ) A ctiv e  D ir e cto ry  f o r t h e u se rs  t o  p ro vid e\ncre atio n ,  d ele tio n ,  u se r p erm is sio n  a n d  m an ag ed  u se r s e cu rit y  w it h  g ro u p\np olic ie s\nG ood  e xp erie n ce  i n  i n sta llin g  a n d  m ain ta in in g  t h e v ir tu al w ork sta tio n s	\n        	( E 2C )\nH an d lin g  P K I a n d  V PN  b ase d  s e cu rit y  i s su es.  p erfo rm  t r o u b le sh ootin g  e n d -\nto -e n d  b etw een  t h e s it e s.  P ro vid in g  t r a in in g  fo r t h e u se rs  t o  c o n fig ure  t h e\nce rtif ic a te  a n d  s e cu re  d om ain  w it h  t w o f a cto r a u th en tic a tio n .\nP erfo rm in g   Reg is tr a tio n   an d   Auth orit y   dutie s  to   in clu d e  ce rtif ic a te\ne n ro lm en t a n d  r e vo ca tio n .\nM an ag ed  A cce ss C on tr o l  S yste m  to  m ain ta in  a ll  th e b ad ges o f  u se rs  a n d\nvis it o rs .  T o p ro vid e p erm is sio n s fo r  th e re co m men d ed  d ep ortm en t  a n d\nse cu re d  a re a.\nIn sta llin g  G em alt o  B om gar  a p plic a tio n  fo r  a ll  th e m ach in es in  p ro d uctio n\nare a.	\nK in g sto n  I n fo  s o lu tio n s,B an g alo re .	                                       	2 020 -	  2 023	            	\n        \n       	 T est E n g in eer	\n 	\nperfo rm in g  v a lid atio n  o n  i n fo ta in m en t f e atu re s i n  a ll p ossib le  c o n d it io n s.\nV alid atin g  d if fe re n t m od ule s l ik e  U SB ,F M ,H M I a n d  P hon e	 	\nP erfo rm in g  th e ra p id  v a lid atio n  te sts   fo r  a ll  te st  c o n d it io n s  a n d  in va lid\nc a se s	 	\nP re p arin g  s o ft w are  v a lid atio n  s ta tu s r e p ort .\nD eve lo p m en t a n d  v a lid atio n  o f i n te g ra te d  T ele m atic s a n d  C lu ste r.	\n 	\nI h ave  a ctiv e ly  in it ia te d  a n d  d eve lo p ed  F O TA  im ple m en ta tio n  in  3 W  ( L 5 M ,\nL5 N ),  T ra cto r,  S C V,  a n d  H CV.  S u cce ssfu lly ,  I  h ave  g iv e n  a  d em o w it h  t w o\nve rtic e s.	 	\nI p ro p ose d  F O TA  e n tr y -le ve l c o n d it io n s a n d  c h ecklis ts  b ase d  o n  i n d iv id ual\nE C U a n d  v e h ic le  b eh avio u r,  e n su rin g  n o im pact o n  t h e e n d  c u sto m er a n d\nm ain ta in in g  v e h ic le  p erfo rm an ce .	\nL A N G UAG ES	Engli s h	 	\nIE LT S w it h  b an d  6\nT am il	 	\nS TA C K H O LD ER S	Sib ro s ,  N esh  ,  C onnectm  ,\nP ric o l  ,  E le ctr o nik a ,  A W EV ,\nSo na C om sta r ,E xid e	 	\n      \nO TH ER  I N FO	Passp o rt n o  - K 2849988	 	\nH obbie s - S ke tc h in g &amp;\nG ard en in g	 	\nT han ks	 	G O W TH AM  S A KTH IV EL	,  C hen nai,  2 4 J u n e 2 024', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 17:22:49', 0),
(398, 93, 1, 4, NULL, '1_93_214232615866994f690de33_HMI_Developer-Shailendra_Semwal.docx', 'HMI Developer-Shailendra Semwal.docx', '\r\nShailendra Semwal\r\n# 3047 Janapriya Havens\r\nYalanka, Bangalore-560065)\r\n✉E-mail Id  shailendarsemwal@gmail.com☎Contact No +91-8548074898\r\n  LinkedIn: https://www.linkedin.com/in/shailendrasemwalCareer Objective:\r\nTo work with maximum potential in a challenging and dynamic environment, with an opportunity of working with diverse group of people and enhancing my professional skills with learning and experience for career growth.\r\nExperience Summary:\r\nWith 8 years of experience in Android Application Development, Android Automotive, and AMS Engineering Application Support, I bring a wealth of expertise to my roles. I have working navigation systems for Scania trucks, kitchen management apps for restaurant chains, and provided critical support for engineering applications at Black &amp;amp; Veatch.\r\nTechnical Skills:\r\nTools &ndash; Git SVN, ADB tools, QFIL Tools, AOSP\r\nLanguage &ndash;  JAVA, Kotlin, Java(Android SDK)\r\nDatabase &ndash; SQLite, MySQL.\r\nTechnology &ndash; Android,AOSPOperating System &ndash; Windows, Mac,LinexIDE &ndash;Android Studio, Eclipse,Microsoft PowerBITicketing Tools- ServiceNow, Jira, Conference, Figma\r\nAreas Of Expertise:\r\n&bull;    Familiar with the Android SDK, Eclipse, Google services and APIs.\r\n&bull;    Knowledge of SQLite, MySQL or Oracle database management system.\r\n&bull;    Proficient in design, problem-solving, and debugging.\r\n&bull;    Proficient with Developer Console in publishing and managing the application.\r\n&bull;    Knowledge in integrating web services, TCP and UDP socket programming.\r\n&bull;    Familiarity with HERE SDK Navigation. \r\n&bull;    Knowledge of Android AOSP Automotive ROM  Development.\r\n&bull;    Knowledge of Android build system.\r\n&bull;    Knowledge of Android boot process Deep Analysis.\r\n&bull;    Knowledge of Car Api, Car Services, VHAL.\r\n&bull;    Knowledge of Car Launcher.\r\n&bull;    Knowledge of Boot Animation.\r\n&bull;    Knowledge of SELinux.\r\n&bull;    Knowledge of Car Settings.\r\n&bull;    Knowledge of System UI.\r\n&bull;    Knowledge of Mobile Penetration Testing of Android Application.\r\nOrganization Experience\r\nEmployer :  L&amp;amp;T Technology Services Ltd\r\nDuration : March 2021 &ndash; Till now\r\nDesignation : Senior Engineer(Android  Developer)\r\n Project Name: -Navigation\r\nClient: Scania \r\nAs part of our Android automotive project, we are developing a navigation app specifically tailored for Scania trucks. This app aims to provide Scania truck drivers with reliable and efficient navigation assistance to optimize their driving experience. Our focus is on creating a user-friendly interface that takes into account the unique requirements of truck drivers, such as vehicle dimensions, weight restrictions, and specific road regulations. The navigation features will include truck-specific routing options, real-time traffic updates, and points of interest relevant to truck drivers, such as rest areas and truck stops. To ensure seamless integration with Scania trucks, we are collaborating closely with the client to understand their specific needs and requirements. Our development process involves leveraging the latest technologies and best practices in Android automotive development to deliver a high-quality and robust navigation solution. By working closely with Scania and leveraging our expertise in Android development, we aim to create a navigation app that enhances the driving experience for Scania truck drivers, improving efficiency and safety on the road. \r\nDDU,RIG,QFIL Tools, AOSP, Gadget Testing, HERE SDK, JIRA, Figma, Coverity static analysis.\r\nEmployer :  Barbeque Nation Hospitality Ltd\r\nDuration : August2020 &ndash; Till now\r\nDesignation : Assistant Manager(Android  Developer)\r\nProject Name:-KDS:( Hospitality Management)\r\nhttps://play.google.com/store/apps/details?id=com.bbqn.relayProject based on Hospitality Management.\r\nProject Name:- Samiksha:( ERP)\r\nhttps://play.google.com/store/apps/details?id=com.app.bbqn.samikshaEmployer :  DFoE (Digital Future of Education Pvt. Ltd.)\r\nDuration : February 2020 &ndash; August2020\r\nDesignation : Android  Research Engineer\r\nProject Name:-FRI:( Hospitality Management)\r\nhttps://play.google.com/store/apps/details?id=com.dfoe.friclienthttps://play.google.com/store/apps/details?id=com.dfoe.frimasterhttps://play.google.com/store/apps/details?id=com.dfoe.frikitchenTechnologies used:&nbsp; JSON, REST, TCP and UDP Socket Programming, SQLite Db.\r\nProject based on Hospitality Management.\r\nPayment Gateway integration using Stripe Payment, PayU.\r\ncommunication protocols Socket.\r\nOrganization Experience\r\nEmployer : Ayshwarya syndicate LLP, Bangalore\r\nDuration :August 2019 &ndash; November 2019\r\nDesignation :Software Developer\r\nProject Name:-Spark IN:\r\nhttps://play.google.com/store/apps/details?id=com.assccl.spark.coopProject based on Banking Consumer Account.\r\nPush notification is implemented using Google Firebase.\r\nPayment Gateway integration using Paytm, Razor pay;\r\nImplemented finger print access security and Device lock security.\r\nHere customer can create Health Insurance, Debit and Credit Cards, Bill Payment.\r\nEmployer :  Technoforte Software (p) Ltd\r\nDuration :  August  2018 &ndash; August  2019\r\nDesignation : Associate Engineer -Software. \r\nClient: Toyota\r\nProject Name:- Polygon:\r\nManufacturer of inventory management &amp;amp; parts tracking systems for real-time inventory control    &amp;amp; tracking serial number, date tracking, trace the movement of materials.\r\nAn Integrated ZebraBarCode scanner, library to scan the barcode.\r\nDesigned the database, UI pattern, data-flow between different modules.\r\nTesting the end to end app, database &amp;amp; web-services.\r\nEmployer : Pronto Software Solutions (p) Ltd, Bangalore\r\nDuration :  November 2016 &ndash; August 2018\r\nDesignation : Associate Software Engineer\r\nProject Name:- Sangama:\r\nClient: Karnataka Forest Department - Belagavi Circle.\r\nhttps://play.google.com/store/apps/details?id=com.pronto.sangamaSangama is an application which is designed to help the officers monitor and Update their work status online/offline.Key Features of the app are as follows: \r\nProject Name:- Cricket Score Pad:\r\nhttps://play.google.com/store/apps/details?id=com.pronto.scorepadCricket Score Pad comes closest to the cricket score card you have filled manually all this years. A scorer&rsquo;s delight, Cricket Score Pad&#039;s neat, clean and intuitive design ensures the cricket score book stays upto-the-ball without you breaking a sweat. Use Cricket Score Pad to score multiple match formats (T20 or ODI) or even custom make your own match.\r\nDesign UI pattern &amp;amp; database.\r\nIdentify and correct fix bugs\r\nEmployer : SPH Vibhava Private (p) Ltd, Bangalore\r\nDuration :  April 2016 &ndash; October 2016\r\nDesignation : Software  Developer\r\nProject Name:- SmartPropertyHunt:\r\nCertified Course\r\n4  month Java &amp;amp; Testing Training In &ldquo;ABC For java &amp;amp; Testing&rdquo; in Bangalore\r\n4 month .Net Technology Training in DUCAT Gwalior.\r\n5 month  C,C++,Core Java Training In GLOBAL ICS Delhi\r\n2 Month  Android Training in Falgee Software Development Pvt Ltd Bangalore.\r\nAcademic Background\r\nYear(s) Qualification  Board/University College/ Institute Percentage\r\n2015  Bachelor of Engineering \r\n(Information Technology) Rajiv Gandhi Proudyogiki   Vishwavidyalaya Bhopal\r\n(Madhya Pradesh)\r\nRustamji Institute of  Technology  BSF Academy Tekanpur Gwalior \r\n(Madhya Pradesh)\r\n 7.75 CGPA \r\n2012           Diploma\r\n(Computer Engineering)\r\nBoard Of Technical Education Delhi(B.T.E) BSF Polytechnic STS \r\nTigri Camp, New Delhi    68.00%\r\nPersonal Details Name : Shailendra Semwal\r\nFather&rsquo;s Name : Prakash Chandra Semwal\r\nMother&rsquo;s Name : Prabha Devi Semwal\r\nDate of birth : 06/11/1992\r\nNationality : Indian\r\nLanguages known : English, Hindi (read, write and speak)\r\nPermanent Address : Tehri Garhwal Uttarakhand \r\nDeclaration I do hereby confirm that the details furnished above are true to the best of my knowledge. I bear the responsibility for the correctness of the above-mentioned particulars.\r\nPlace: Bengaluru\r\nDate: (Shailendra Semwal)\r\n', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-21 17:30:04', '2024-07-18 17:30:04', 0, NULL, NULL, '2024-07-18 17:22:49', 0),
(399, 93, 1, NULL, NULL, '1_93_116745945766994f690e005_HMI_Developer-Swapnil_Thamake.pdf', 'HMI Developer-Swapnil_Thamake.pdf', 'Sw ap nil  T h am ake  \nTe am  L e ad  \n                                             \nap plic a tio n i m pro ve m en ts . C urre n t p ro je ct w ork in g  o n F o rd  C re d it  ( ﬁ nte ch ) a n d  L a st p ro je ct w as w ork e d\n                                       \nsw ap 3848@ gm ail .c o m  \n\nPune, I n d ia  \nlin ke d in .c o m /in /s w ap nil - t h am ake -2 14314a0  \nWORK  E X PER IE N CE \nTe am  L e ad  \nTe ch  M ah in d ra  \n04/2 022 -  P re se n t\n, \n  Pun e \nFo rd  C re d it  A pplic a tio n : ( F in te ch ) \nLe ad in g  t o  m y 2  b ud dy&#039;s  a n d  d eve lo pin g  M obil e  A pplic a tio n\nis  b ase d  o n ﬁ nan cia l a n d  a cco unt m an ag em en t s e rv ic e s \nUse  s k il ls  C ode o ptim iz a tio n, A pplic a tio n s e cu rit y , d esig n\npatte rn s a n d  r e so lv e  l o w  p erfo rm an ce  i s su es. \n                 \n           \nAsso cia te  C onsu lt a n t \nCap gem in i I n d ia  \n02/2 020 -  0 4/2 022\n, \n  Pun e \nHSB C B an k I n dia  \nWork e d  o n F in an ce  D om ain  &amp;  B an kin g  d o m ain  a p plic a tio n.\nIm ple m en te d  s o rt in g , s e arc h in g  a lg o rit h m s a n d  d esig n\npatte rn s. \n                         \nQR c o de, T ra n sa ctio n h is to ry , R ais e  d is p ute . \nAnd ro id , K otlin , R xJav a , D ag ger 2 ,M VP, R etro ﬁ t, J e n kin s,\n                    \nConte xt, H ooks. \nApplic a tio n E ng in eer -  M obil e  A pplic a tio n\nDeve lo per \nRaw  E n g in eerin g  I n d . P vt. L td . \n08/2 018 -  0 1/2 020\n, \n  Vir a r -  M um bai \nIn  R aw  E ngin eerin g i  h ave  w ork e d  o n s p o rt s  d o m ain  p ro je cts  \n                   \n                             \nso rt in g  a n d  s e arc h in g  a lg o rit h m s. \n                 \nRetro ﬁ t, J e n kin s, G it , A W S, X M PP,F ir e b ase , C ra sh ly tic s \nMobil e  A pplic a tio n D eve lo per \nG.N .R eatil  S e rv ic e s P vt. L td .( Z ap m art .c o m ) \n05/2 016 -  0 7/2 018\n, \n  Mum bai \nZa p m art  i s  O nlin e G ro ce ry  P ro du ct B ase d  C om pan y \nReq uir e m en t &amp;  A naly sis , D esig n a n d  D eve lo p A pplic a tio ns,\nWrit e  A PI&#039;s , W ork  o n B ack -e n d  a n d  D B. \nWork e d  o n z a p m art  a p plic a tio n w hic h  b ase d  o n o nlin e\ngro ce ry  s to re . D eve lo ped  o rd er t ra ck in g  f u nctio nalit y  u sin g\nGoogle  M ap . \nAnd ro id , j a v a , V olle y, G it , B it b uck e t, S Q LLit e , F ir e b ase ,\nCra sh ly tic s. \nSK IL L S  \nAnd ro id  S D K \nJav a  \nGit h u b  \nSQ Lit e  \nRest A PI \nMyS Q L \nFir e b ase  \nRxJav a  \nSo narQ  \nAW S \nMVC \nMVVM  \nRO OM  \nJIR A  \nMock it o  \nSyste m  D esig n \nKotlin  \nMult iT h re ad in g  \nJe tp ack  \n \n    \nAlg o rit h m s \nRetro ﬁ t \nData  s tru ctu re  \nFir e b ase  \nRxJav a  \nLiv e d ata  \nReact N ativ e  \nTyp esc rip t \n    \n \n \n  \nPR O FE SSIO NAL P R O JE C TS \nFo rd  C re d it\n ( 0 4/2 022 -  P re se n t)\n \nHSB C b an kin g\n ( 0 3/2 020 -  0 4/2 022)\n \nHaw ks A re n a F a rm  S ta te  &amp;  S acra m en to  K in g &#039;s\n ( 0 1/2 019 -  0 1/2 020)\n \nJD  P ow er\n ( 0 8/2 018 -  1 2/2 018)\n \nMed ic a lw ale  D octo r A pp\n ( 0 3/2 018 -  0 7/2 018)\n \nza p m art .c o m\n ( 0 8/2 016 -  0 1/2 018)\n \nED UCATIO N \nMCA  ( M aste r i n  C om pute r A pplic a tio n) \nKIT &#039;S  I M ER  K olh ap ur \n07/2 013 -  0 6/2 016\n, \n  Kolh ap u r,M ah ara sh tra , I n dia  \nBCA  \nGopal K ris h n a G okh ale  C olle g e K olh ap ur \n06/2 009 -  0 4/2 012\n, \n  Kolh ap u r ,  M ah ara sh tra  ,  I n dia  \n12th  \nS.M .L o hia  C olle g e, K olh ap ur \n06/2 007 -  0 2/2 009\n, \n  Kolh ap u r \n10th  \nJyo tir lin g  v id ya m an d ir  V ad an ag e \n06/2 002 -  0 3/2 007\n, \n  Kolh ap u r \nIN TER EST S \nPho to gra p hy \nSin g in g  \nCric k e t \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s 	\nUnitTest	\nMVP\nAOSP	\nSplunk	CSS	  Jacoco	\n8369096660	\nMobile Application Developer with 8 years of experience in coding, team lead, architecture design and\non HSBC Bank on financial domain . I have also worked on Sports, Health Care, Automative and E-Commerce.	\nReact Native, Typescript, Android, Kotlin, MVVM,\nJWT, Jetpack, Coroutine, Git, Splunk\nDeveloped application with key features like money transfer,\nNexus, SonarQ, Git, SSL pinning, React Native,\nDeveloped application for NBA teams and Automative App\nLive score update with xmpp protocol. Used multithreading,\nAndroid, Java, Kotlin, RxJava, Dagger2, MVP, AOSP,', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 17:22:49', 0);
INSERT INTO `resume` (`id`, `screeningId`, `adminId`, `candidateId`, `candidateDetailsId`, `resumeName`, `resumeOriginalName`, `resumeContent`, `isSkillScreened`, `isResumeScreened`, `isCron`, `isCandidate`, `candidateShortlist`, `enableInterviewReport`, `gptLanguageId`, `isInterviewAssign`, `interviewValidity`, `interviewAssignDate`, `isPsychoAssign`, `psychoValidity`, `psychoAssignDate`, `created`, `createdBy`) VALUES
(400, 94, 1, 32, NULL, '1_94_2173266446699508f28a80_Ajay_Chaudhari_-_HMI_Developer.pdf', 'Ajay Chaudhari - HMI Developer.pdf', '/  	\nA JAY  C H AU DH ARI\nSoft w are  D eve lo p er	\narc h au d hari1 4 0 2@ gm ail. c o m	h ttp s:/ /w ww.lin ke d in .c o m /in /a ja y -\nc h au d hari- 0 15 6 ba16 9/	\nK an ag aw a, J a p an	\nS U M MARY\nExp erie n ce d  S oft w are  D eve lo p er w it h  o ve r 4 .3  y e ars  s p ecia liz in g  in  A nd ro id -\nbase d  A uto m otiv e  In fo ta in m en t s y ste m s 	 \n 	\nP ostg re S Q L,  a n d  O doo.  I  a m  e ag er t o  c o lla b ora te  o n a d va n cin g  c u ttin g -e d ge	 	\nte ch no lo g y a n d  d eliv e rin g  e xc e p tio nal  r e su lt s .\nE X PER IE N CE\nOnsit e  D eve lo p m en t E ngin eer\nTata  C on su lt a n cy S erv ic e s L td	\n0 5/2 0 24	&nbsp;	K an ag aw a,  J a p an	\nA ssig ned  F e atu re :  R ad io  	 	\nR ad io ,  P od ca st)\nO nsit e  S PO C f o r R ad io  f e atu re ,  C lie n t c o m mun ic a tio n,  M an ag e S O P /  Q LU	 	\n/ M ain lin e d eliv e rie s f o r N is sa n  V eh ic le s,  B ug  t r ia g in g  a n d  f ix in g\nW ork in g  w it h  c ro ss-fu n ctio nal  t e am s s u ch  a s X peri,   L G ,  G oog le ,  B osc h ,	 	\netc .\nT e ch S ta ck:  A nd ro id ,  K otlin ,  J a va ,  A O SP,  A ASP	\nS yste m s E ngin eer\nTata  C on su lt a n cy S erv ic e s L td	\n0 1/2 0 22 	&nbsp;	G an d hin ag ar,  In d ia	\nN is sa n  IV I  f e atu re s:  T e le m atic s 	 	\nC onnm an  \nF i,   a n d  H ots p ot).\nH M I  d eve lo p m en t t h at w ork s w it h  A O SP a n d  H AL p ro vid ed  b y L G  a n d	 	\nB osc h ,  f e atu rin g  1 0 0\nB uilt  p yth o n s c rip t t h at r e d uce d  S ST R g en era tio n t im e b y 8 0 %\nTe ch S ta ck:  A nd ro id ,  K otlin ,  J a va	\nJ r. A pplic atio n  E ngin eer\nTin yE R P P vt. L td	\n1 0 /2 0 20  	&nbsp;	A hm ed ab ad ,  In d ia	\nO doo:  E R P B usin ess S uit e  o f o p en -s o urc e  b usin ess a p ps c o ve rin g  C RM ,	 	\neC om merc e ,  A cco un tin g ,  In ve n to ry ,  P O S e tc\nD eve lo p m en t o f c u sto m  m od ule s a s p er c lie n ts &#039;  n eed s.  A ddre sse d  m ain ly	 	\ng en eric  &amp;  s p ecif ic  is su e s d urin g  d ata b ase  u p gra d es.  1  g en eric  f ix  c a n	 	\nre so lv e  r o ug hly  1 0  C lie n ts  d ata b ase  u p gra d e is su e s\nTe ch S ta ck:  P yth o n,  P ostg re sq l,   J S ,  U bun tu	\nP yth on /O doo D eve lo p er\nBro w se ln fo  P vt. L td	\n0 3 /2 0 20  	&nbsp;	A hm ed ab ad ,  In d ia	\nD eve lo p ed  C usto m  L ib ra ry  m an ag em en t O doo A pp,  P ro d uct Q ualit y	 	\nA ssu ra n ce  A pp u sin g  g en eric  m od ule s\nC ontr ib ute d  t o  e xis tin g  O doo A pps lik e  B atc h  P ay m en t d urin g  in vo ic in g\nTe ch S ta ck:  P yth o n,  J S ,  O doo	\nE D U CATIO N\nBach elo r o f E ngin eerin g\nSA L E n g in eerin g  A nd  T e ch nic al I n stit u te , G TU	\n04 /2 0 17  	&nbsp;	A hm ed ab ad ,  In d ia	\nGP A	\n8.2 7	10	\nC om pute r E ng in eerin g  M ajo r	\nS KIL LS\nTe ch S ta ck\nA nd ro id	J av a	K otlin	P yth on	\nO doo	P ostg re sq l	M atp lo tL ib	\nN um py	O pen C V	Pan d as	S eab orn	\nS kle arn	G it	\nT e ch nic al  E xp ert is e\nA uto m otiv e  I n fo ta in m en t f o r C CS\nER P S oft w are  	M ac h in e L e arn in g	\nP R O JEC TS\nAuto m atic  A tte n dan ce  S yste m	\nhttp s:/ /g it h ub .c o m /A jja rv is /A uto m atic _A tte n d an ce _S\ny ste m	\nF ace  R eco g nit io n-b ase d  A uto m atic  A tte n d an ce	 	\nS yste m  u sin g  C CTV  f o r r e al- tim e s tu d en t	 	\natte n d an ce .	\nTe ch S ta ck:  P yth o n,  T kin te r,  X lr d ,  X ls x w rit e r,	 	\nO pen C v	\nIn diM on ey : A n E xp en se  T ra cke r A pp	\nhttp s:/ /g it h ub .c o m /A jja rv is /In d iM oney	\nA nd ro id  E xp en se  T ra cke r A pp f o r e ffic ie n tly	 	\nm onit o rin g  o f e xp en se  a n d  in co m e w it h  le ss e ffo rts	\nT e ch S ta ck:  A nd ro id ,  S Q Lit e ,  G oog le  M L k it	\nA C H IE V EM EN TS	\nPala d in  o f t h e I V IT  C ham pio n s\nRece iv e d  b eca u se  o f h ig h p erfo rm an ce  o n	 	\ncrit ic a l  p hase  o f t h e p ro je ct\nD ig it a l M ile sto n e a t T C S\nCle are d  c o d in g  c h alle n g es in  P yth o n a n d	 	\nd em onstr a te d  c o m pete n cie s in  A gile	 	\nm eth o d olo g y.\nIn nova to r M ile sto n e a t T C S\nCle are d  c o d in g  c h alle n g e o n M ach in e	 	\nLe arn in g	\nwww .enhancv .com	\n	\nPow er ed b y	\nE		q	\n\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;	\n&bull;\n&bull;\n&amp;\n\n', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-21 17:38:25', '2024-07-18 17:38:25', 0, NULL, NULL, '2024-07-18 17:27:43', 0),
(401, 94, 1, 4, NULL, '1_94_16477892056699508f28c61_Arjun_V_Menon_-_HMI_Developer.pdf', 'Arjun V Menon - HMI Developer.pdf', '. \n. \n 	 	\nARJUN V MENON	 	\nSoftware Engineer 	 	\n +91 9744816460	  	\n\ncom	 	 	\n https://www.linkedin.co\nm/in/arjun	-menon	-	\n937159141/	 	 	\n 	\n 	\nAn  inspired  android  developer  dedicated  to  continuously  developing, \nimplementing,  and  adopting  new  technologies  to  maximize  development \nefficiency  and  produce  innovative  applications.  I  have  a  total  technical \nexperience of more than 4 years &amp; passionate to	wards solving problems. 	 	\n \n 	Skills	 	\n Native Android Development ( Java , Kotlin) 	 	 \n JSON, RESTful web services. 	 	 \n Retrofit, Volley, Coroutines. 	 	 \n SQL Lite, Room DB, MySql, Shared Preferences. 	 	 \n Markup language (XML). 	 	 \n Version Control (Git, Bitbuket, SVN, Gerrit). 	 	 \n Project Management (Jira, Jenkins, Polarion, Confluence). 	 	 \n AOSP 	 	 \n Android HMI 	 	 	 	\n 	\nWork History	 	\n Senior Software Enginner	 	\nTata Elxsi, Bangalore	 	\n Worked on Android Map application using Mapbox for automotive 	 	\n Worked on Telematics CV2X project, In Android Telematics Service \nApplication. 	 	\n Testing and Debugging on Hardware for Android Telematics. 	 	\n Worked on Android HMI for Launcher App. 	 	\n Skills: Jira 	- Confluence 	- Polarion 	- Gerrit 	- AOSP 	- BinderIPC 	- Android 	\nFramework 	- Java 	- Mqtt 	- AIDL 	 	\n Programmer Analyst	 	\nCognizant, Bangalore	 	\n Worked on Google Play Protect Project. 	 	\n Worked on android security and android reverse engineering. 	 	\n Worked on Identifying security threats and malware in Playstore. 	 	\n Worked Android Malware analysis. 	 	\n Skills: Jira 	- Android Studio 	- Reverse Engineering 	- Java 	- Kotlin 	 	\n 	\n2022	-11 	- Current	 	\n2021	-09 	- 2022	-11	 	\narjunvenumenon@gmail.\n\n. \n. 	\n Software Engineer	 	\nQuest Global, Trivandrum	 	\n Software development in Android Automotive HMI 	 	\n Worked on Phonebook team of HMI, Version control using SVN. 	 	\n Developed features for Phonebook and Contacts of HMI. 	 	\n Testing and debugging of Build in Hardware. 	 	\n Skills: Jira 	- Gerrit 	- AOSP 	- BinderIPC 	- Android Studio 	- AIDL 	 	\n Software Engineer	 	\nAutocon India Pvt. Ltd, Kochi	 	\n Developed new features for proprietary Android applications used on \nphones and tablets; worked with developers to develop toptier solutions \nfor restaurant and retail customers 	 	\n Uses Coroutines for long	-running tasks (database and network access) 	 	\n Maintaine	d long and short	-range deliverables with product 	\nmanagement team according to product roadmaps 	 	\n Created custom mobile applications using native technologies 	 	\n Database access through Room persistence library. 	 	\n Android Developer	 	\nTradeasy Technologies, Kannur	 	\n Created custom mobile applications for retail customers 	 	\n Documented architecture and implementation for internal and external \nconsumption 	 	\n Applied various techniques to locate bugs and errors in applications 	 	\n Designed and built sales applications for Android platform 	 	\n Provided dedicated support and timely issue resolution to clients \nfollowing successful app launch. 	 	 	\n 	\nEducation	 	\n B-tech: 	Electronics And Communication Engineering	 	\nKannur 	University 	- Kannur	 	\nPercentage: 63 	 	\n 12th: 	Science	 	\nChapparapadava HSS 	- Kannur	 	\nPercentage: 70% 	 	\n 10th Std	 	\nChapparapadava HSS 	- Kannur	 	\nPercentage: 85% 	 	 	\n 	\nAccomplishments	 	\n  Conducted Android App Development workshops in various colleges 	 	\n Participated in workshop on Internet of Things by Innovians Technologies 	 	\n Participated in Cannovation 2018 startup exhibition of Kannur University 	 	\n 	 	 	\n. 	\n2021	-04 	- 2021	-09	 	\n2020	-08 	- 2021	-04	 	\n2019	-03 	- 2020	-08	 	\n2014	-07 	- 2018	-05	 	\n2011	-06 	- 2013	-03	 	\n2010	-06 	- 2011	-03', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-21 17:38:59', '2024-07-18 17:38:59', 0, NULL, NULL, '2024-07-18 17:27:43', 0),
(402, 94, 1, NULL, NULL, '1_94_2046887716699508f28e19_Gowtham_Mohanraj_HMI_Developer_Resume_1_(1).pdf', 'Gowtham    Mohanraj HMI Developer Resume 1 (1).pdf', 'ED U C ATIO N\nG OW TH AM  SA SSIS TA N T M AN AG ER	 	C O NTA C T+91 6 383311446go w tth am s6 @ gm ail.c o m ch en naiS K IL LS	Pro je ct M an ag e m en t	 	\nT eam work\nT im e M an ag e m en t\nLe ad ers h ip\nE ffe ctiv e  C om mun ic a tio n\nC rit ic a l  T hin kin g	\nV ELA LA R C O LLE G E O F\nEN GIN EER IN G A N D T EC H NO LO GY\nEle ctr o nic s &amp;  C om mun ic a tio n -  7 5%2 010  -  2 01 32009PO NNU M ATR IC U LA TIO N H R S E C\nSC H O OL\nHig h er s e co nd ary  e d uca tio n -  8 5%W ORK  E X PER IE N CEPR O JE C TS	 	P R O FIL EDyn am ic   an d  in no vativ e   in fo ta in m en t  sy ste m  exp ert  w it h  o ve r  4  ye ars   o f\nexp erie n ce   in   deve lo pin g  an d   im ple m en tin g  cu ttin g-e d ge   in   au to m otiv e\nin d ustr y  a n d  in fo rm atio n s y ste m s.  O ve r a ll  1 0 y e ars  o f e xp erie n ce  in  S o ft w are\nin d ustr y .  P ro ve n  a b ili t y  to  le ad  c ro ss-fu n ctio nal  te am s  a n d  m an ag e  p ro je cts\nfr o m  co nce p t  to   co m ple tio n,  en su rin g  se am le ss  in te gra tio n  of  m ult im ed ia ,\nn av ig atio n,  an d   co nnectiv it y   fe atu re s.  Adep t  at  le ve ra g in g  ad van ce d\nte ch no lo gie s t o  e n han ce  u se r e xp erie n ce  a n d  d riv e  m ark e t c o m petit iv e n ess.\n2 023 -  P R ESE N TM on tr a  - T I c le an  m ob il it y  p riv ate  l im it e dA ssis ta n t m an ag er	 	\nP ro d uct d eve lo p m en t &amp;  R eq uir e m en ts  h an d lin g	  -  C en tr a l R &amp; D	The  cre atio n   an d   exe cu tio n   of  m an ual  te st  ca se s  fo r  all  m od ule s  an d\nap plic a tio n s o f v e h ic le  t e le m atic s.\nT he c re atio n  o f  v e h ic le  a le rts  a n d  in fo rm atio n  th ro u g h th e te le m atic s c lo u d\nfo r m ob il e  a p plic a tio n s a n d  O EM .\nFu n ctio n al  a n d  in te g ra tio n  te stin g  o f  a p plic a tio n  fe atu re s a t  b oth  th e te st\nb en ch  a n d  v e h ic le  l e ve ls  u sin g  a  C AN  A naly ze r.\nC usto m iz in g  th e te le m atic s d ash b oard  a n d  m an ag in g  it   a cco rd in g  to  re al-\nt im e f ie ld  i s su es a n d  s e rv ic e  r e q uir e m en ts .\nD eve lo p m en t  te stin g  o f  v e h ic le  fe atu re s s u ch  a s g eo fe n cin g ,  liv e  tr a ckin g ,\nan d  v e h ic le  a le rts  a n d  A nd ro id  d eve lo p m en t i n  i n fo ta in m en t s y ste m .\nTele m atic s p erfo rm an ce  a n aly sis  t h ro u g h v a rio u s c o m petit iv e  b en ch m ark in g .\nSu p port t h e v e n d or s e le ctio n  p ro ce ss a n d  m an ag e v e n d ors  t o  e n su re  t im ely\nd eliv e ry  a n d  t h e r e q uir e d  q ualit y .\nG ood  k n ow le d ge a n d  u n d ers ta n d in g  o f  E V  a rc h it e ctu re  w it h  m ult ip le  C AN\nnetw ork s i n  t h e v e h ic le .\nP re p ara tio n   of  8D  re p orts   in   co ord in atio n   w it h   pro d uctio n   an d   cro ss-\nfu n ctio n al t e am s t o  s o lv e  c rit ic a l q ualit y  i s su es.\nE xp ertis e  i n  p re p arin g  S co p e o f R eq uir e m en ts  d ocu m en ts .\nT eam  s iz e  :  2\nI n it ia tin g  a n d  im ple m en tin g  U D S p ro to co l  a cro ss  a ll  ve h ic le  d ow nstr e am\nE C Us, c o n sid erin g  a ll a sp ects  a n d  v e rtic e s.\nS u p portin g  t h e d eve lo p m en t o f a  s in g le  c lo u d  p la tfo rm  f o r v a rio u s t e le m atic s\nu n it s .\nA ctiv e ly  in vo lv e d  in  t h e im ple m en ta tio n  a n d  v a lid atio n  o f	  t e le m atic s f e atu re s	\nsu ch  a s :\n D eep  l o g ger -	  V erif ic a tio n  a n d  v a lid atio n  o f e ach  v e h ic le  d ata  p oin t.	1.\n D eep  u p d ate r -	  D eve lo p m en t o f U D S p ro to co l i n  a ll E C Us t o  s u p port	\nF ir m ware  O ve r-T he-A ir  	(F O TA	) u p d ate s.	\n2.\nD eep  c o m man d er -  D eve lo p m en t o f v e h ic le  I m m ob il iz a tio n  s y ste m s.	3.	\nT O OLS	 	CA N oe\nC A N an aly ze r\nB us M aste r\nP -C A N\nJT A G\n\nDoco m o I n te rto u ch  I n d ia  L td  ,  B an g alo re , I n d ia	 	IT  S u p port E n g in eer	M S O utlo ok c o n fig ura tio n , b acku p  ,  r e sto re  a n d  t r o u b le sh ootin g .\nM an ag e D om ain  e n vir o n m en t f o r t w o s it e s t h ro u g h r e m ote  s u p port.\nW ir e le ss n etw ork in g  i n  D om ain  e n vir o n m en t.\nA sse m blin g , h ard w are  u p  g ra d atio n  a n d  t r o u b le sh ootin g .\nPro vid in g  s u p port t o  i n sta llin g  O S f o r t h e u se r m ach in es a n d  s e rv e rs .	\n G em alt o  M id dle  E ast F Z  L LC , D ub ai, U .A .E	                              	2 016 - 2 020	 	 2013- 2 016	 	IS S/N etw ork  a n d  S u p port E n g in eer	R esp on sib le   fo r	   	LA N  an d  W AN  n etw ork   op era tio n s,  sy ste m  d is a ste r	\nre co ve ry ,  data b ase   an d   sy ste m  backu p ,  Pla ye d   ke y  ro le   in   backu p\nm an ag em en t o f I T  d ep artm en t.\nC IS C O   :  Rou te rs ,  Sw it c h es,  Serv e r,  wir e le ss  devic e s,  an d   Acce ss\nte ch nolo g ie s.\nS tr o n g  t r o u b le sh ootin g  s k il ls  o n  L A N , W AN  a n d  W ir e le ss t e ch nolo g ie s.\nM an ag ed  u se r a cco u n ts  w it h  ( A D ) A ctiv e  D ir e cto ry  f o r t h e u se rs  t o  p ro vid e\ncre atio n ,  d ele tio n ,  u se r p erm is sio n  a n d  m an ag ed  u se r s e cu rit y  w it h  g ro u p\np olic ie s\nG ood  e xp erie n ce  i n  i n sta llin g  a n d  m ain ta in in g  t h e v ir tu al w ork sta tio n s	\n        	( E 2C )\nH an d lin g  P K I a n d  V PN  b ase d  s e cu rit y  i s su es.  p erfo rm  t r o u b le sh ootin g  e n d -\nto -e n d  b etw een  t h e s it e s.  P ro vid in g  t r a in in g  fo r t h e u se rs  t o  c o n fig ure  t h e\nce rtif ic a te  a n d  s e cu re  d om ain  w it h  t w o f a cto r a u th en tic a tio n .\nP erfo rm in g   Reg is tr a tio n   an d   Auth orit y   dutie s  to   in clu d e  ce rtif ic a te\ne n ro lm en t a n d  r e vo ca tio n .\nM an ag ed  A cce ss C on tr o l  S yste m  to  m ain ta in  a ll  th e b ad ges o f  u se rs  a n d\nvis it o rs .  T o p ro vid e p erm is sio n s fo r  th e re co m men d ed  d ep ortm en t  a n d\nse cu re d  a re a.\nIn sta llin g  G em alt o  B om gar  a p plic a tio n  fo r  a ll  th e m ach in es in  p ro d uctio n\nare a.	\nK in g sto n  I n fo  s o lu tio n s,B an g alo re .	                                       	2 020 -	  2 023	            	\n        \n       	 T est E n g in eer	\n 	\nperfo rm in g  v a lid atio n  o n  i n fo ta in m en t f e atu re s i n  a ll p ossib le  c o n d it io n s.\nV alid atin g  d if fe re n t m od ule s l ik e  U SB ,F M ,H M I a n d  P hon e	 	\nP erfo rm in g  th e ra p id  v a lid atio n  te sts   fo r  a ll  te st  c o n d it io n s  a n d  in va lid\nc a se s	 	\nP re p arin g  s o ft w are  v a lid atio n  s ta tu s r e p ort .\nD eve lo p m en t a n d  v a lid atio n  o f i n te g ra te d  T ele m atic s a n d  C lu ste r.	\n 	\nI h ave  a ctiv e ly  in it ia te d  a n d  d eve lo p ed  F O TA  im ple m en ta tio n  in  3 W  ( L 5 M ,\nL5 N ),  T ra cto r,  S C V,  a n d  H CV.  S u cce ssfu lly ,  I  h ave  g iv e n  a  d em o w it h  t w o\nve rtic e s.	 	\nI p ro p ose d  F O TA  e n tr y -le ve l c o n d it io n s a n d  c h ecklis ts  b ase d  o n  i n d iv id ual\nE C U a n d  v e h ic le  b eh avio u r,  e n su rin g  n o im pact o n  t h e e n d  c u sto m er a n d\nm ain ta in in g  v e h ic le  p erfo rm an ce .	\nL A N G UAG ES	Engli s h	 	\nIE LT S w it h  b an d  6\nT am il	 	\nS TA C K H O LD ER S	Sib ro s ,  N esh  ,  C onnectm  ,\nP ric o l  ,  E le ctr o nik a ,  A W EV ,\nSo na C om sta r ,E xid e	 	\n      \nO TH ER  I N FO	Passp o rt n o  - K 2849988	 	\nH obbie s - S ke tc h in g &amp;\nG ard en in g	 	\nT han ks	 	G O W TH AM  S A KTH IV EL	,  C hen nai,  2 4 J u n e 2 024', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 17:27:43', 0),
(403, 94, 1, NULL, NULL, '1_94_15805785086699508f291f6_HMI_Developer-Shailendra_Semwal.docx', 'HMI Developer-Shailendra Semwal.docx', '\r\nShailendra Semwal\r\n# 3047 Janapriya Havens\r\nYalanka, Bangalore-560065)\r\n✉E-mail Id  shailendarsemwal@gmail.com☎Contact No +91-8548074898\r\n  LinkedIn: https://www.linkedin.com/in/shailendrasemwalCareer Objective:\r\nTo work with maximum potential in a challenging and dynamic environment, with an opportunity of working with diverse group of people and enhancing my professional skills with learning and experience for career growth.\r\nExperience Summary:\r\nWith 8 years of experience in Android Application Development, Android Automotive, and AMS Engineering Application Support, I bring a wealth of expertise to my roles. I have working navigation systems for Scania trucks, kitchen management apps for restaurant chains, and provided critical support for engineering applications at Black &amp;amp; Veatch.\r\nTechnical Skills:\r\nTools &ndash; Git SVN, ADB tools, QFIL Tools, AOSP\r\nLanguage &ndash;  JAVA, Kotlin, Java(Android SDK)\r\nDatabase &ndash; SQLite, MySQL.\r\nTechnology &ndash; Android,AOSPOperating System &ndash; Windows, Mac,LinexIDE &ndash;Android Studio, Eclipse,Microsoft PowerBITicketing Tools- ServiceNow, Jira, Conference, Figma\r\nAreas Of Expertise:\r\n&bull;    Familiar with the Android SDK, Eclipse, Google services and APIs.\r\n&bull;    Knowledge of SQLite, MySQL or Oracle database management system.\r\n&bull;    Proficient in design, problem-solving, and debugging.\r\n&bull;    Proficient with Developer Console in publishing and managing the application.\r\n&bull;    Knowledge in integrating web services, TCP and UDP socket programming.\r\n&bull;    Familiarity with HERE SDK Navigation. \r\n&bull;    Knowledge of Android AOSP Automotive ROM  Development.\r\n&bull;    Knowledge of Android build system.\r\n&bull;    Knowledge of Android boot process Deep Analysis.\r\n&bull;    Knowledge of Car Api, Car Services, VHAL.\r\n&bull;    Knowledge of Car Launcher.\r\n&bull;    Knowledge of Boot Animation.\r\n&bull;    Knowledge of SELinux.\r\n&bull;    Knowledge of Car Settings.\r\n&bull;    Knowledge of System UI.\r\n&bull;    Knowledge of Mobile Penetration Testing of Android Application.\r\nOrganization Experience\r\nEmployer :  L&amp;amp;T Technology Services Ltd\r\nDuration : March 2021 &ndash; Till now\r\nDesignation : Senior Engineer(Android  Developer)\r\n Project Name: -Navigation\r\nClient: Scania \r\nAs part of our Android automotive project, we are developing a navigation app specifically tailored for Scania trucks. This app aims to provide Scania truck drivers with reliable and efficient navigation assistance to optimize their driving experience. Our focus is on creating a user-friendly interface that takes into account the unique requirements of truck drivers, such as vehicle dimensions, weight restrictions, and specific road regulations. The navigation features will include truck-specific routing options, real-time traffic updates, and points of interest relevant to truck drivers, such as rest areas and truck stops. To ensure seamless integration with Scania trucks, we are collaborating closely with the client to understand their specific needs and requirements. Our development process involves leveraging the latest technologies and best practices in Android automotive development to deliver a high-quality and robust navigation solution. By working closely with Scania and leveraging our expertise in Android development, we aim to create a navigation app that enhances the driving experience for Scania truck drivers, improving efficiency and safety on the road. \r\nDDU,RIG,QFIL Tools, AOSP, Gadget Testing, HERE SDK, JIRA, Figma, Coverity static analysis.\r\nEmployer :  Barbeque Nation Hospitality Ltd\r\nDuration : August2020 &ndash; Till now\r\nDesignation : Assistant Manager(Android  Developer)\r\nProject Name:-KDS:( Hospitality Management)\r\nhttps://play.google.com/store/apps/details?id=com.bbqn.relayProject based on Hospitality Management.\r\nProject Name:- Samiksha:( ERP)\r\nhttps://play.google.com/store/apps/details?id=com.app.bbqn.samikshaEmployer :  DFoE (Digital Future of Education Pvt. Ltd.)\r\nDuration : February 2020 &ndash; August2020\r\nDesignation : Android  Research Engineer\r\nProject Name:-FRI:( Hospitality Management)\r\nhttps://play.google.com/store/apps/details?id=com.dfoe.friclienthttps://play.google.com/store/apps/details?id=com.dfoe.frimasterhttps://play.google.com/store/apps/details?id=com.dfoe.frikitchenTechnologies used:&nbsp; JSON, REST, TCP and UDP Socket Programming, SQLite Db.\r\nProject based on Hospitality Management.\r\nPayment Gateway integration using Stripe Payment, PayU.\r\ncommunication protocols Socket.\r\nOrganization Experience\r\nEmployer : Ayshwarya syndicate LLP, Bangalore\r\nDuration :August 2019 &ndash; November 2019\r\nDesignation :Software Developer\r\nProject Name:-Spark IN:\r\nhttps://play.google.com/store/apps/details?id=com.assccl.spark.coopProject based on Banking Consumer Account.\r\nPush notification is implemented using Google Firebase.\r\nPayment Gateway integration using Paytm, Razor pay;\r\nImplemented finger print access security and Device lock security.\r\nHere customer can create Health Insurance, Debit and Credit Cards, Bill Payment.\r\nEmployer :  Technoforte Software (p) Ltd\r\nDuration :  August  2018 &ndash; August  2019\r\nDesignation : Associate Engineer -Software. \r\nClient: Toyota\r\nProject Name:- Polygon:\r\nManufacturer of inventory management &amp;amp; parts tracking systems for real-time inventory control    &amp;amp; tracking serial number, date tracking, trace the movement of materials.\r\nAn Integrated ZebraBarCode scanner, library to scan the barcode.\r\nDesigned the database, UI pattern, data-flow between different modules.\r\nTesting the end to end app, database &amp;amp; web-services.\r\nEmployer : Pronto Software Solutions (p) Ltd, Bangalore\r\nDuration :  November 2016 &ndash; August 2018\r\nDesignation : Associate Software Engineer\r\nProject Name:- Sangama:\r\nClient: Karnataka Forest Department - Belagavi Circle.\r\nhttps://play.google.com/store/apps/details?id=com.pronto.sangamaSangama is an application which is designed to help the officers monitor and Update their work status online/offline.Key Features of the app are as follows: \r\nProject Name:- Cricket Score Pad:\r\nhttps://play.google.com/store/apps/details?id=com.pronto.scorepadCricket Score Pad comes closest to the cricket score card you have filled manually all this years. A scorer&rsquo;s delight, Cricket Score Pad&#039;s neat, clean and intuitive design ensures the cricket score book stays upto-the-ball without you breaking a sweat. Use Cricket Score Pad to score multiple match formats (T20 or ODI) or even custom make your own match.\r\nDesign UI pattern &amp;amp; database.\r\nIdentify and correct fix bugs\r\nEmployer : SPH Vibhava Private (p) Ltd, Bangalore\r\nDuration :  April 2016 &ndash; October 2016\r\nDesignation : Software  Developer\r\nProject Name:- SmartPropertyHunt:\r\nCertified Course\r\n4  month Java &amp;amp; Testing Training In &ldquo;ABC For java &amp;amp; Testing&rdquo; in Bangalore\r\n4 month .Net Technology Training in DUCAT Gwalior.\r\n5 month  C,C++,Core Java Training In GLOBAL ICS Delhi\r\n2 Month  Android Training in Falgee Software Development Pvt Ltd Bangalore.\r\nAcademic Background\r\nYear(s) Qualification  Board/University College/ Institute Percentage\r\n2015  Bachelor of Engineering \r\n(Information Technology) Rajiv Gandhi Proudyogiki   Vishwavidyalaya Bhopal\r\n(Madhya Pradesh)\r\nRustamji Institute of  Technology  BSF Academy Tekanpur Gwalior \r\n(Madhya Pradesh)\r\n 7.75 CGPA \r\n2012           Diploma\r\n(Computer Engineering)\r\nBoard Of Technical Education Delhi(B.T.E) BSF Polytechnic STS \r\nTigri Camp, New Delhi    68.00%\r\nPersonal Details Name : Shailendra Semwal\r\nFather&rsquo;s Name : Prakash Chandra Semwal\r\nMother&rsquo;s Name : Prabha Devi Semwal\r\nDate of birth : 06/11/1992\r\nNationality : Indian\r\nLanguages known : English, Hindi (read, write and speak)\r\nPermanent Address : Tehri Garhwal Uttarakhand \r\nDeclaration I do hereby confirm that the details furnished above are true to the best of my knowledge. I bear the responsibility for the correctness of the above-mentioned particulars.\r\nPlace: Bengaluru\r\nDate: (Shailendra Semwal)\r\n', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 17:27:43', 0),
(404, 94, 1, 4, NULL, '1_94_19820779266699508f293dd_HMI_Developer-Swapnil_Thamake.pdf', 'HMI Developer-Swapnil_Thamake.pdf', 'Sw ap nil  T h am ake  \nTe am  L e ad  \n                                             \nap plic a tio n i m pro ve m en ts . C urre n t p ro je ct w ork in g  o n F o rd  C re d it  ( ﬁ nte ch ) a n d  L a st p ro je ct w as w ork e d\n                                       \nsw ap 3848@ gm ail .c o m  \n\nPune, I n d ia  \nlin ke d in .c o m /in /s w ap nil - t h am ake -2 14314a0  \nWORK  E X PER IE N CE \nTe am  L e ad  \nTe ch  M ah in d ra  \n04/2 022 -  P re se n t\n, \n  Pun e \nFo rd  C re d it  A pplic a tio n : ( F in te ch ) \nLe ad in g  t o  m y 2  b ud dy&#039;s  a n d  d eve lo pin g  M obil e  A pplic a tio n\nis  b ase d  o n ﬁ nan cia l a n d  a cco unt m an ag em en t s e rv ic e s \nUse  s k il ls  C ode o ptim iz a tio n, A pplic a tio n s e cu rit y , d esig n\npatte rn s a n d  r e so lv e  l o w  p erfo rm an ce  i s su es. \n                 \n           \nAsso cia te  C onsu lt a n t \nCap gem in i I n d ia  \n02/2 020 -  0 4/2 022\n, \n  Pun e \nHSB C B an k I n dia  \nWork e d  o n F in an ce  D om ain  &amp;  B an kin g  d o m ain  a p plic a tio n.\nIm ple m en te d  s o rt in g , s e arc h in g  a lg o rit h m s a n d  d esig n\npatte rn s. \n                         \nQR c o de, T ra n sa ctio n h is to ry , R ais e  d is p ute . \nAnd ro id , K otlin , R xJav a , D ag ger 2 ,M VP, R etro ﬁ t, J e n kin s,\n                    \nConte xt, H ooks. \nApplic a tio n E ng in eer -  M obil e  A pplic a tio n\nDeve lo per \nRaw  E n g in eerin g  I n d . P vt. L td . \n08/2 018 -  0 1/2 020\n, \n  Vir a r -  M um bai \nIn  R aw  E ngin eerin g i  h ave  w ork e d  o n s p o rt s  d o m ain  p ro je cts  \n                   \n                             \nso rt in g  a n d  s e arc h in g  a lg o rit h m s. \n                 \nRetro ﬁ t, J e n kin s, G it , A W S, X M PP,F ir e b ase , C ra sh ly tic s \nMobil e  A pplic a tio n D eve lo per \nG.N .R eatil  S e rv ic e s P vt. L td .( Z ap m art .c o m ) \n05/2 016 -  0 7/2 018\n, \n  Mum bai \nZa p m art  i s  O nlin e G ro ce ry  P ro du ct B ase d  C om pan y \nReq uir e m en t &amp;  A naly sis , D esig n a n d  D eve lo p A pplic a tio ns,\nWrit e  A PI&#039;s , W ork  o n B ack -e n d  a n d  D B. \nWork e d  o n z a p m art  a p plic a tio n w hic h  b ase d  o n o nlin e\ngro ce ry  s to re . D eve lo ped  o rd er t ra ck in g  f u nctio nalit y  u sin g\nGoogle  M ap . \nAnd ro id , j a v a , V olle y, G it , B it b uck e t, S Q LLit e , F ir e b ase ,\nCra sh ly tic s. \nSK IL L S  \nAnd ro id  S D K \nJav a  \nGit h u b  \nSQ Lit e  \nRest A PI \nMyS Q L \nFir e b ase  \nRxJav a  \nSo narQ  \nAW S \nMVC \nMVVM  \nRO OM  \nJIR A  \nMock it o  \nSyste m  D esig n \nKotlin  \nMult iT h re ad in g  \nJe tp ack  \n \n    \nAlg o rit h m s \nRetro ﬁ t \nData  s tru ctu re  \nFir e b ase  \nRxJav a  \nLiv e d ata  \nReact N ativ e  \nTyp esc rip t \n    \n \n \n  \nPR O FE SSIO NAL P R O JE C TS \nFo rd  C re d it\n ( 0 4/2 022 -  P re se n t)\n \nHSB C b an kin g\n ( 0 3/2 020 -  0 4/2 022)\n \nHaw ks A re n a F a rm  S ta te  &amp;  S acra m en to  K in g &#039;s\n ( 0 1/2 019 -  0 1/2 020)\n \nJD  P ow er\n ( 0 8/2 018 -  1 2/2 018)\n \nMed ic a lw ale  D octo r A pp\n ( 0 3/2 018 -  0 7/2 018)\n \nza p m art .c o m\n ( 0 8/2 016 -  0 1/2 018)\n \nED UCATIO N \nMCA  ( M aste r i n  C om pute r A pplic a tio n) \nKIT &#039;S  I M ER  K olh ap ur \n07/2 013 -  0 6/2 016\n, \n  Kolh ap u r,M ah ara sh tra , I n dia  \nBCA  \nGopal K ris h n a G okh ale  C olle g e K olh ap ur \n06/2 009 -  0 4/2 012\n, \n  Kolh ap u r ,  M ah ara sh tra  ,  I n dia  \n12th  \nS.M .L o hia  C olle g e, K olh ap ur \n06/2 007 -  0 2/2 009\n, \n  Kolh ap u r \n10th  \nJyo tir lin g  v id ya m an d ir  V ad an ag e \n06/2 002 -  0 3/2 007\n, \n  Kolh ap u r \nIN TER EST S \nPho to gra p hy \nSin g in g  \nCric k e t \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s 	\nUnitTest	\nMVP\nAOSP	\nSplunk	CSS	  Jacoco	\n8369096660	\nMobile Application Developer with 8 years of experience in coding, team lead, architecture design and\non HSBC Bank on financial domain . I have also worked on Sports, Health Care, Automative and E-Commerce.	\nReact Native, Typescript, Android, Kotlin, MVVM,\nJWT, Jetpack, Coroutine, Git, Splunk\nDeveloped application with key features like money transfer,\nNexus, SonarQ, Git, SSL pinning, React Native,\nDeveloped application for NBA teams and Automative App\nLive score update with xmpp protocol. Used multithreading,\nAndroid, Java, Kotlin, RxJava, Dagger2, MVP, AOSP,', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-21 18:16:12', '2024-07-18 18:16:12', 0, NULL, NULL, '2024-07-18 17:27:43', 0),
(405, 94, 1, 4, NULL, '1_94_876861466699508f29579_Muhammed_Shihab_HMI_Developer.pdf', 'Muhammed Shihab_HMI Developer.pdf', 'MUHAMMED SHIHAB V K	 	\nSenior Engineer Android	 HMI	 	\nThrissur, Kerala, India	 	\n+91	-9526199466	 	\nShihabvk99@gmail.com	 	\nlinkedin.com	/muhammedshihabvk	 	\ngithub.com/muhammedshihabvk	 	\nhackerrank	.com/muhammedshihabvk	 	\nProfile	 	\nEnergetic, Creative, and 	curiosity	-driven Android/Mobile	/HMI 	Developer with 4+ years of experience, I have a deep understanding 	\nof the Android ecosystem	 with 	different	 domain	s like 	Retail	(Leading brands)	 and 	Automotive	(OEM	), including the latest tools and 	\ntechnologies.  I  specialize  in  building  robust  and  efficient  Android  applications  that  provide  seamless  user  experiences.  I  ha	ve 	\nextensive knowledge in various mobile development languages, including Java, Kotlin, and Dart. 	I have experience in working with 	\nAndroid Studio, the Android SDK, and popular libraries.	 	\n \nCore Qualifications	 	\n▪ 	Native 	Android development	 	\n▪ 	Quality assurance	 	\n▪ 	App	 development life cycle	 	\n▪ 	User experience design	 	\n▪ 	Information architecture	 	\n▪ 	Agile software development methodologies	 	\nSkills	 \n▪ 	Programming Languages: Java, Kotlin, Dart	 	\n▪ 	Android Development: Android SDK, Android Studio, \nGradle, Retrofit, RxJava,	 Coroutine,	 Picasso, Glide. 	 	\n▪ 	Tools and Technologies: Git, GitHub, Bitbucket, JIRA, \nFirebase, RESTful APIs, JSON, Google Maps API.	 	\nProfessional experience	 	\nMahindra	 &amp; Mahindra	, Automotive, 	Coi	mbatore,	 Tamil Nadu	              	         	        	Sep 20	23-Present	 	Senior Engineer 	&ndash; Android HMI	 	\nI work	 as an Android Developer, focusing on creating user interfaces and functionality like battery 	\nmanagement, vehicle 	drive mode	, and gallery	, using	 structured	 MVVM architecture	 for Mahindra 	\nBorn 	Ele	ctric Vehicles	. I also worked on connecting our app with car systems using CAN signals. In 	\nteam  meetings,  I  shared  ideas  and  kept  everyone  updated  on  our  progress  and  any  new \ndevelopments. 	Working closely with the product team, I made sure our technical solutions aligned 	\nwith business needs. Even with tight deadlines, I successfully delivered results. I&#039;m known for being \nfriendly,  respectful,  and  always  ready  to  lend  a  hand.  When  faced  with 	challenges,  I&#039;m  good  at 	\nbreaking them down, finding solutions, and making decisions. Whether I&#039;m working independently \nor with a team, I&#039;m effective and adaptable.	 	\n \nSkills	:  Java,  Kotlin,  Android,	 Service,	 Content 	Provider,	 Broadcast	 Receivers	, Retrofit,  M	QTT	, 	\nMVVM,  ViewModel,  LiveData,	 Coroutine,	 Flow,	 Datastore,  Hilt, 	Car	 &amp; CarPropertyManager	 Libs	, 	\nCAN/Ethernet  Signals,	 Glide,  Git	, GitHub	, Canoe	 17,  QFIL  &amp;  Ren	esas(	Device  Flashing)	, Tera  Term, 	\nLottie Animation, Adobe After Effect for Lottie Json with Bodymovin	, Figma, Visure	, LeapX	. 	\nLitmus	7 Systems Consulting,	 Retail, Kochi	,Kerala	                                  	       	            	 Jul 2019	-Sep 2023	 	\nSenior Engineer 	&ndash; Android	 	\nI  made  a 	user	-friendly  e	-commerce  app  for  Android  that  makes  shopping  easy.  I  worked  with 	\ndifferent teams to make sure the app met all the needs and worked well. We added features like \nproduct listings, search, and payment. I also helped junior developers learn and	 grow. I&#039;m good at 	\nall parts of making an app, like testing and putting it on the app store.	 	\n \nSkills: 	Java,Kotlin,Dart,Android,Flutter,	MVVM,  MVP,  ViewModel,  LiveData,  REST  APIs,  Postman, 	\nRecyclerView,  Glide,  WebView  Retrofit/Fast	-Android	-Networking,    Gson/Jackson  Serialization, 	\nRxJava,  Moengage(Analytics,  geofence,  Notification  center),    Chucker(API  logger),Auth  Token \nHandling  with  OkHttp	 Authenticator,  Firebase(Auth,  Crashlytics)  Zendesk  (Chat),  Google  Maps, 	\nCheckout.com  (Payment),  Ticketing  Systems  (Jira/ServiceNow),  and  Git  VCS  (Bitbucket/GitHub \nRemote).	 	\nL3 Associate POS Engineer	 	\nI managed store software like Oracle Micros Point of Sale for retail shops. Every day, I did \nmaintenance for these systems. I worked with different teams to fix any problems, like POS \ndevelopers and database admins. I managed tickets and solved issues, eve	n outside of regular 	\nhours. I also made sure updates were done smoothly and used PowerShell to automate tasks for \nstores in the US and Canada.	 	\n 	\nEducation	 	\nBachelor of Technology (7.07cgpa) \nComputer science and Engineering \nKMEA Engineering College, IN APJ Abdul \nKalam Technological University 	2019	 	\n \nHobbies	 	\nPhotography, Badminton, Listening \nMusic	, Travelling,	 	\n \nLanguage	 	\nEnglish, Malayalam	 	\n \nPersonal Data	 	\n28yrs, DOB 28 March 1996 	S/O Kadher	 	\n9383	-9181	-5394(Aadhaar IN)', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-21 18:12:07', '2024-07-18 18:12:07', 0, NULL, NULL, '2024-07-18 17:27:43', 0),
(406, 95, 74, NULL, NULL, '74_95_15014582156699557b64b03_Ajay_Chaudhari_-_HMI_Developer.pdf', 'Ajay Chaudhari - HMI Developer.pdf', '/  	\nA JAY  C H AU DH ARI\nSoft w are  D eve lo p er	\narc h au d hari1 4 0 2@ gm ail. c o m	h ttp s:/ /w ww.lin ke d in .c o m /in /a ja y -\nc h au d hari- 0 15 6 ba16 9/	\nK an ag aw a, J a p an	\nS U M MARY\nExp erie n ce d  S oft w are  D eve lo p er w it h  o ve r 4 .3  y e ars  s p ecia liz in g  in  A nd ro id -\nbase d  A uto m otiv e  In fo ta in m en t s y ste m s 	 \n 	\nP ostg re S Q L,  a n d  O doo.  I  a m  e ag er t o  c o lla b ora te  o n a d va n cin g  c u ttin g -e d ge	 	\nte ch no lo g y a n d  d eliv e rin g  e xc e p tio nal  r e su lt s .\nE X PER IE N CE\nOnsit e  D eve lo p m en t E ngin eer\nTata  C on su lt a n cy S erv ic e s L td	\n0 5/2 0 24	&nbsp;	K an ag aw a,  J a p an	\nA ssig ned  F e atu re :  R ad io  	 	\nR ad io ,  P od ca st)\nO nsit e  S PO C f o r R ad io  f e atu re ,  C lie n t c o m mun ic a tio n,  M an ag e S O P /  Q LU	 	\n/ M ain lin e d eliv e rie s f o r N is sa n  V eh ic le s,  B ug  t r ia g in g  a n d  f ix in g\nW ork in g  w it h  c ro ss-fu n ctio nal  t e am s s u ch  a s X peri,   L G ,  G oog le ,  B osc h ,	 	\netc .\nT e ch S ta ck:  A nd ro id ,  K otlin ,  J a va ,  A O SP,  A ASP	\nS yste m s E ngin eer\nTata  C on su lt a n cy S erv ic e s L td	\n0 1/2 0 22 	&nbsp;	G an d hin ag ar,  In d ia	\nN is sa n  IV I  f e atu re s:  T e le m atic s 	 	\nC onnm an  \nF i,   a n d  H ots p ot).\nH M I  d eve lo p m en t t h at w ork s w it h  A O SP a n d  H AL p ro vid ed  b y L G  a n d	 	\nB osc h ,  f e atu rin g  1 0 0\nB uilt  p yth o n s c rip t t h at r e d uce d  S ST R g en era tio n t im e b y 8 0 %\nTe ch S ta ck:  A nd ro id ,  K otlin ,  J a va	\nJ r. A pplic atio n  E ngin eer\nTin yE R P P vt. L td	\n1 0 /2 0 20  	&nbsp;	A hm ed ab ad ,  In d ia	\nO doo:  E R P B usin ess S uit e  o f o p en -s o urc e  b usin ess a p ps c o ve rin g  C RM ,	 	\neC om merc e ,  A cco un tin g ,  In ve n to ry ,  P O S e tc\nD eve lo p m en t o f c u sto m  m od ule s a s p er c lie n ts &#039;  n eed s.  A ddre sse d  m ain ly	 	\ng en eric  &amp;  s p ecif ic  is su e s d urin g  d ata b ase  u p gra d es.  1  g en eric  f ix  c a n	 	\nre so lv e  r o ug hly  1 0  C lie n ts  d ata b ase  u p gra d e is su e s\nTe ch S ta ck:  P yth o n,  P ostg re sq l,   J S ,  U bun tu	\nP yth on /O doo D eve lo p er\nBro w se ln fo  P vt. L td	\n0 3 /2 0 20  	&nbsp;	A hm ed ab ad ,  In d ia	\nD eve lo p ed  C usto m  L ib ra ry  m an ag em en t O doo A pp,  P ro d uct Q ualit y	 	\nA ssu ra n ce  A pp u sin g  g en eric  m od ule s\nC ontr ib ute d  t o  e xis tin g  O doo A pps lik e  B atc h  P ay m en t d urin g  in vo ic in g\nTe ch S ta ck:  P yth o n,  J S ,  O doo	\nE D U CATIO N\nBach elo r o f E ngin eerin g\nSA L E n g in eerin g  A nd  T e ch nic al I n stit u te , G TU	\n04 /2 0 17  	&nbsp;	A hm ed ab ad ,  In d ia	\nGP A	\n8.2 7	10	\nC om pute r E ng in eerin g  M ajo r	\nS KIL LS\nTe ch S ta ck\nA nd ro id	J av a	K otlin	P yth on	\nO doo	P ostg re sq l	M atp lo tL ib	\nN um py	O pen C V	Pan d as	S eab orn	\nS kle arn	G it	\nT e ch nic al  E xp ert is e\nA uto m otiv e  I n fo ta in m en t f o r C CS\nER P S oft w are  	M ac h in e L e arn in g	\nP R O JEC TS\nAuto m atic  A tte n dan ce  S yste m	\nhttp s:/ /g it h ub .c o m /A jja rv is /A uto m atic _A tte n d an ce _S\ny ste m	\nF ace  R eco g nit io n-b ase d  A uto m atic  A tte n d an ce	 	\nS yste m  u sin g  C CTV  f o r r e al- tim e s tu d en t	 	\natte n d an ce .	\nTe ch S ta ck:  P yth o n,  T kin te r,  X lr d ,  X ls x w rit e r,	 	\nO pen C v	\nIn diM on ey : A n E xp en se  T ra cke r A pp	\nhttp s:/ /g it h ub .c o m /A jja rv is /In d iM oney	\nA nd ro id  E xp en se  T ra cke r A pp f o r e ffic ie n tly	 	\nm onit o rin g  o f e xp en se  a n d  in co m e w it h  le ss e ffo rts	\nT e ch S ta ck:  A nd ro id ,  S Q Lit e ,  G oog le  M L k it	\nA C H IE V EM EN TS	\nPala d in  o f t h e I V IT  C ham pio n s\nRece iv e d  b eca u se  o f h ig h p erfo rm an ce  o n	 	\ncrit ic a l  p hase  o f t h e p ro je ct\nD ig it a l M ile sto n e a t T C S\nCle are d  c o d in g  c h alle n g es in  P yth o n a n d	 	\nd em onstr a te d  c o m pete n cie s in  A gile	 	\nm eth o d olo g y.\nIn nova to r M ile sto n e a t T C S\nCle are d  c o d in g  c h alle n g e o n M ach in e	 	\nLe arn in g	\nwww .enhancv .com	\n	\nPow er ed b y	\nE		q	\n\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;	\n&bull;\n&bull;\n&amp;\n\n', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 17:48:43', 0),
(407, 95, 74, 43, NULL, '74_95_6820022856699557b64d36_Arjun_V_Menon_-_HMI_Developer.pdf', 'Arjun V Menon - HMI Developer.pdf', '. \n. \n 	 	\nARJUN V MENON	 	\nSoftware Engineer 	 	\n +91 9744816460	  	\n\ncom	 	 	\n https://www.linkedin.co\nm/in/arjun	-menon	-	\n937159141/	 	 	\n 	\n 	\nAn  inspired  android  developer  dedicated  to  continuously  developing, \nimplementing,  and  adopting  new  technologies  to  maximize  development \nefficiency  and  produce  innovative  applications.  I  have  a  total  technical \nexperience of more than 4 years &amp; passionate to	wards solving problems. 	 	\n \n 	Skills	 	\n Native Android Development ( Java , Kotlin) 	 	 \n JSON, RESTful web services. 	 	 \n Retrofit, Volley, Coroutines. 	 	 \n SQL Lite, Room DB, MySql, Shared Preferences. 	 	 \n Markup language (XML). 	 	 \n Version Control (Git, Bitbuket, SVN, Gerrit). 	 	 \n Project Management (Jira, Jenkins, Polarion, Confluence). 	 	 \n AOSP 	 	 \n Android HMI 	 	 	 	\n 	\nWork History	 	\n Senior Software Enginner	 	\nTata Elxsi, Bangalore	 	\n Worked on Android Map application using Mapbox for automotive 	 	\n Worked on Telematics CV2X project, In Android Telematics Service \nApplication. 	 	\n Testing and Debugging on Hardware for Android Telematics. 	 	\n Worked on Android HMI for Launcher App. 	 	\n Skills: Jira 	- Confluence 	- Polarion 	- Gerrit 	- AOSP 	- BinderIPC 	- Android 	\nFramework 	- Java 	- Mqtt 	- AIDL 	 	\n Programmer Analyst	 	\nCognizant, Bangalore	 	\n Worked on Google Play Protect Project. 	 	\n Worked on android security and android reverse engineering. 	 	\n Worked on Identifying security threats and malware in Playstore. 	 	\n Worked Android Malware analysis. 	 	\n Skills: Jira 	- Android Studio 	- Reverse Engineering 	- Java 	- Kotlin 	 	\n 	\n2022	-11 	- Current	 	\n2021	-09 	- 2022	-11	 	\narjunvenumenon@gmail.\n\n. \n. 	\n Software Engineer	 	\nQuest Global, Trivandrum	 	\n Software development in Android Automotive HMI 	 	\n Worked on Phonebook team of HMI, Version control using SVN. 	 	\n Developed features for Phonebook and Contacts of HMI. 	 	\n Testing and debugging of Build in Hardware. 	 	\n Skills: Jira 	- Gerrit 	- AOSP 	- BinderIPC 	- Android Studio 	- AIDL 	 	\n Software Engineer	 	\nAutocon India Pvt. Ltd, Kochi	 	\n Developed new features for proprietary Android applications used on \nphones and tablets; worked with developers to develop toptier solutions \nfor restaurant and retail customers 	 	\n Uses Coroutines for long	-running tasks (database and network access) 	 	\n Maintaine	d long and short	-range deliverables with product 	\nmanagement team according to product roadmaps 	 	\n Created custom mobile applications using native technologies 	 	\n Database access through Room persistence library. 	 	\n Android Developer	 	\nTradeasy Technologies, Kannur	 	\n Created custom mobile applications for retail customers 	 	\n Documented architecture and implementation for internal and external \nconsumption 	 	\n Applied various techniques to locate bugs and errors in applications 	 	\n Designed and built sales applications for Android platform 	 	\n Provided dedicated support and timely issue resolution to clients \nfollowing successful app launch. 	 	 	\n 	\nEducation	 	\n B-tech: 	Electronics And Communication Engineering	 	\nKannur 	University 	- Kannur	 	\nPercentage: 63 	 	\n 12th: 	Science	 	\nChapparapadava HSS 	- Kannur	 	\nPercentage: 70% 	 	\n 10th Std	 	\nChapparapadava HSS 	- Kannur	 	\nPercentage: 85% 	 	 	\n 	\nAccomplishments	 	\n  Conducted Android App Development workshops in various colleges 	 	\n Participated in workshop on Internet of Things by Innovians Technologies 	 	\n Participated in Cannovation 2018 startup exhibition of Kannur University 	 	\n 	 	 	\n. 	\n2021	-04 	- 2021	-09	 	\n2020	-08 	- 2021	-04	 	\n2019	-03 	- 2020	-08	 	\n2014	-07 	- 2018	-05	 	\n2011	-06 	- 2013	-03	 	\n2010	-06 	- 2011	-03', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-21 17:56:11', '2024-07-18 17:56:11', 0, NULL, NULL, '2024-07-18 17:48:43', 0);
INSERT INTO `resume` (`id`, `screeningId`, `adminId`, `candidateId`, `candidateDetailsId`, `resumeName`, `resumeOriginalName`, `resumeContent`, `isSkillScreened`, `isResumeScreened`, `isCron`, `isCandidate`, `candidateShortlist`, `enableInterviewReport`, `gptLanguageId`, `isInterviewAssign`, `interviewValidity`, `interviewAssignDate`, `isPsychoAssign`, `psychoValidity`, `psychoAssignDate`, `created`, `createdBy`) VALUES
(408, 95, 74, NULL, NULL, '74_95_4609098526699557b64ee4_Gowtham_Mohanraj_HMI_Developer_Resume_1_(1).pdf', 'Gowtham    Mohanraj HMI Developer Resume 1 (1).pdf', 'ED U C ATIO N\nG OW TH AM  SA SSIS TA N T M AN AG ER	 	C O NTA C T+91 6 383311446go w tth am s6 @ gm ail.c o m ch en naiS K IL LS	Pro je ct M an ag e m en t	 	\nT eam work\nT im e M an ag e m en t\nLe ad ers h ip\nE ffe ctiv e  C om mun ic a tio n\nC rit ic a l  T hin kin g	\nV ELA LA R C O LLE G E O F\nEN GIN EER IN G A N D T EC H NO LO GY\nEle ctr o nic s &amp;  C om mun ic a tio n -  7 5%2 010  -  2 01 32009PO NNU M ATR IC U LA TIO N H R S E C\nSC H O OL\nHig h er s e co nd ary  e d uca tio n -  8 5%W ORK  E X PER IE N CEPR O JE C TS	 	P R O FIL EDyn am ic   an d  in no vativ e   in fo ta in m en t  sy ste m  exp ert  w it h  o ve r  4  ye ars   o f\nexp erie n ce   in   deve lo pin g  an d   im ple m en tin g  cu ttin g-e d ge   in   au to m otiv e\nin d ustr y  a n d  in fo rm atio n s y ste m s.  O ve r a ll  1 0 y e ars  o f e xp erie n ce  in  S o ft w are\nin d ustr y .  P ro ve n  a b ili t y  to  le ad  c ro ss-fu n ctio nal  te am s  a n d  m an ag e  p ro je cts\nfr o m  co nce p t  to   co m ple tio n,  en su rin g  se am le ss  in te gra tio n  of  m ult im ed ia ,\nn av ig atio n,  an d   co nnectiv it y   fe atu re s.  Adep t  at  le ve ra g in g  ad van ce d\nte ch no lo gie s t o  e n han ce  u se r e xp erie n ce  a n d  d riv e  m ark e t c o m petit iv e n ess.\n2 023 -  P R ESE N TM on tr a  - T I c le an  m ob il it y  p riv ate  l im it e dA ssis ta n t m an ag er	 	\nP ro d uct d eve lo p m en t &amp;  R eq uir e m en ts  h an d lin g	  -  C en tr a l R &amp; D	The  cre atio n   an d   exe cu tio n   of  m an ual  te st  ca se s  fo r  all  m od ule s  an d\nap plic a tio n s o f v e h ic le  t e le m atic s.\nT he c re atio n  o f  v e h ic le  a le rts  a n d  in fo rm atio n  th ro u g h th e te le m atic s c lo u d\nfo r m ob il e  a p plic a tio n s a n d  O EM .\nFu n ctio n al  a n d  in te g ra tio n  te stin g  o f  a p plic a tio n  fe atu re s a t  b oth  th e te st\nb en ch  a n d  v e h ic le  l e ve ls  u sin g  a  C AN  A naly ze r.\nC usto m iz in g  th e te le m atic s d ash b oard  a n d  m an ag in g  it   a cco rd in g  to  re al-\nt im e f ie ld  i s su es a n d  s e rv ic e  r e q uir e m en ts .\nD eve lo p m en t  te stin g  o f  v e h ic le  fe atu re s s u ch  a s g eo fe n cin g ,  liv e  tr a ckin g ,\nan d  v e h ic le  a le rts  a n d  A nd ro id  d eve lo p m en t i n  i n fo ta in m en t s y ste m .\nTele m atic s p erfo rm an ce  a n aly sis  t h ro u g h v a rio u s c o m petit iv e  b en ch m ark in g .\nSu p port t h e v e n d or s e le ctio n  p ro ce ss a n d  m an ag e v e n d ors  t o  e n su re  t im ely\nd eliv e ry  a n d  t h e r e q uir e d  q ualit y .\nG ood  k n ow le d ge a n d  u n d ers ta n d in g  o f  E V  a rc h it e ctu re  w it h  m ult ip le  C AN\nnetw ork s i n  t h e v e h ic le .\nP re p ara tio n   of  8D  re p orts   in   co ord in atio n   w it h   pro d uctio n   an d   cro ss-\nfu n ctio n al t e am s t o  s o lv e  c rit ic a l q ualit y  i s su es.\nE xp ertis e  i n  p re p arin g  S co p e o f R eq uir e m en ts  d ocu m en ts .\nT eam  s iz e  :  2\nI n it ia tin g  a n d  im ple m en tin g  U D S p ro to co l  a cro ss  a ll  ve h ic le  d ow nstr e am\nE C Us, c o n sid erin g  a ll a sp ects  a n d  v e rtic e s.\nS u p portin g  t h e d eve lo p m en t o f a  s in g le  c lo u d  p la tfo rm  f o r v a rio u s t e le m atic s\nu n it s .\nA ctiv e ly  in vo lv e d  in  t h e im ple m en ta tio n  a n d  v a lid atio n  o f	  t e le m atic s f e atu re s	\nsu ch  a s :\n D eep  l o g ger -	  V erif ic a tio n  a n d  v a lid atio n  o f e ach  v e h ic le  d ata  p oin t.	1.\n D eep  u p d ate r -	  D eve lo p m en t o f U D S p ro to co l i n  a ll E C Us t o  s u p port	\nF ir m ware  O ve r-T he-A ir  	(F O TA	) u p d ate s.	\n2.\nD eep  c o m man d er -  D eve lo p m en t o f v e h ic le  I m m ob il iz a tio n  s y ste m s.	3.	\nT O OLS	 	CA N oe\nC A N an aly ze r\nB us M aste r\nP -C A N\nJT A G\n\nDoco m o I n te rto u ch  I n d ia  L td  ,  B an g alo re , I n d ia	 	IT  S u p port E n g in eer	M S O utlo ok c o n fig ura tio n , b acku p  ,  r e sto re  a n d  t r o u b le sh ootin g .\nM an ag e D om ain  e n vir o n m en t f o r t w o s it e s t h ro u g h r e m ote  s u p port.\nW ir e le ss n etw ork in g  i n  D om ain  e n vir o n m en t.\nA sse m blin g , h ard w are  u p  g ra d atio n  a n d  t r o u b le sh ootin g .\nPro vid in g  s u p port t o  i n sta llin g  O S f o r t h e u se r m ach in es a n d  s e rv e rs .	\n G em alt o  M id dle  E ast F Z  L LC , D ub ai, U .A .E	                              	2 016 - 2 020	 	 2013- 2 016	 	IS S/N etw ork  a n d  S u p port E n g in eer	R esp on sib le   fo r	   	LA N  an d  W AN  n etw ork   op era tio n s,  sy ste m  d is a ste r	\nre co ve ry ,  data b ase   an d   sy ste m  backu p ,  Pla ye d   ke y  ro le   in   backu p\nm an ag em en t o f I T  d ep artm en t.\nC IS C O   :  Rou te rs ,  Sw it c h es,  Serv e r,  wir e le ss  devic e s,  an d   Acce ss\nte ch nolo g ie s.\nS tr o n g  t r o u b le sh ootin g  s k il ls  o n  L A N , W AN  a n d  W ir e le ss t e ch nolo g ie s.\nM an ag ed  u se r a cco u n ts  w it h  ( A D ) A ctiv e  D ir e cto ry  f o r t h e u se rs  t o  p ro vid e\ncre atio n ,  d ele tio n ,  u se r p erm is sio n  a n d  m an ag ed  u se r s e cu rit y  w it h  g ro u p\np olic ie s\nG ood  e xp erie n ce  i n  i n sta llin g  a n d  m ain ta in in g  t h e v ir tu al w ork sta tio n s	\n        	( E 2C )\nH an d lin g  P K I a n d  V PN  b ase d  s e cu rit y  i s su es.  p erfo rm  t r o u b le sh ootin g  e n d -\nto -e n d  b etw een  t h e s it e s.  P ro vid in g  t r a in in g  fo r t h e u se rs  t o  c o n fig ure  t h e\nce rtif ic a te  a n d  s e cu re  d om ain  w it h  t w o f a cto r a u th en tic a tio n .\nP erfo rm in g   Reg is tr a tio n   an d   Auth orit y   dutie s  to   in clu d e  ce rtif ic a te\ne n ro lm en t a n d  r e vo ca tio n .\nM an ag ed  A cce ss C on tr o l  S yste m  to  m ain ta in  a ll  th e b ad ges o f  u se rs  a n d\nvis it o rs .  T o p ro vid e p erm is sio n s fo r  th e re co m men d ed  d ep ortm en t  a n d\nse cu re d  a re a.\nIn sta llin g  G em alt o  B om gar  a p plic a tio n  fo r  a ll  th e m ach in es in  p ro d uctio n\nare a.	\nK in g sto n  I n fo  s o lu tio n s,B an g alo re .	                                       	2 020 -	  2 023	            	\n        \n       	 T est E n g in eer	\n 	\nperfo rm in g  v a lid atio n  o n  i n fo ta in m en t f e atu re s i n  a ll p ossib le  c o n d it io n s.\nV alid atin g  d if fe re n t m od ule s l ik e  U SB ,F M ,H M I a n d  P hon e	 	\nP erfo rm in g  th e ra p id  v a lid atio n  te sts   fo r  a ll  te st  c o n d it io n s  a n d  in va lid\nc a se s	 	\nP re p arin g  s o ft w are  v a lid atio n  s ta tu s r e p ort .\nD eve lo p m en t a n d  v a lid atio n  o f i n te g ra te d  T ele m atic s a n d  C lu ste r.	\n 	\nI h ave  a ctiv e ly  in it ia te d  a n d  d eve lo p ed  F O TA  im ple m en ta tio n  in  3 W  ( L 5 M ,\nL5 N ),  T ra cto r,  S C V,  a n d  H CV.  S u cce ssfu lly ,  I  h ave  g iv e n  a  d em o w it h  t w o\nve rtic e s.	 	\nI p ro p ose d  F O TA  e n tr y -le ve l c o n d it io n s a n d  c h ecklis ts  b ase d  o n  i n d iv id ual\nE C U a n d  v e h ic le  b eh avio u r,  e n su rin g  n o im pact o n  t h e e n d  c u sto m er a n d\nm ain ta in in g  v e h ic le  p erfo rm an ce .	\nL A N G UAG ES	Engli s h	 	\nIE LT S w it h  b an d  6\nT am il	 	\nS TA C K H O LD ER S	Sib ro s ,  N esh  ,  C onnectm  ,\nP ric o l  ,  E le ctr o nik a ,  A W EV ,\nSo na C om sta r ,E xid e	 	\n      \nO TH ER  I N FO	Passp o rt n o  - K 2849988	 	\nH obbie s - S ke tc h in g &amp;\nG ard en in g	 	\nT han ks	 	G O W TH AM  S A KTH IV EL	,  C hen nai,  2 4 J u n e 2 024', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-18 17:48:43', 0),
(409, 96, 73, 44, NULL, '73_96_9514763636699eb21f28a7_Develoeper-_Connected_Vehicle-Avinash_Thakur.pdf', 'Develoeper- Connected Vehicle-Avinash Thakur.pdf', 'A vin ash	\nT haku r	\nA nd ro id	\nF ra m ew ork	\nD eve lo per	\nB ach e lo r	\no f	\nE ng in e erin g	\ni n	\nE C E	\n-\n2 0 16	\n7 4 118 79 73 8\nt h aku ra vi2 19 1@ gm ail.c o m\n\nP R O FE S SIO NAL	\nP R O FIL E	\n\nE xp erie nce d	\nA nd ro id	\nf r a m ew ork	\ne ng in e er	\nw it h	\no ve r	\n6	\ny e ars	\ni n	\nA uto m otiv e	\nI n fo ta in m ent,	\nI V I	\ns y ste m s,	\nA O SP	\nP ortin g ,	\na n d	\nC onsu m er	\nE le ctr o nic s.	\n\nT E C H NIC A L	\nE X PER TIS E	\n\n●	\nA nd ro id	\nA uto m otiv e :	\nC ar	\nA PI,	\nC arS erv ic e ,	\nS yste m	\nS ta te	\nM an ag em ent,	\nO TA .	\n●	\nH yp erv is o r:	\nX en	\nH yp erv is o r.	\n●	\nD eve lo p m en t	\nT o ols :	\nA nd ro id	\nS tu d io ,	\na d b,	\nP utty ,	\nG it ,	\nC lo ne zilla	\n●	\nL a n g uag es:	\nJ a va ,	\nC ++,	\nC ,	\nR x-J a va	\n●	\nO S:	\nA O SP,	\nU buntu ,	\nW in d ow s,	\nL in ux	\n●	\nP ro to co ls :	\nO BD -II,	\nJ 19 39	\n●	\nV ers io n	\nC on tr o l:	\nG it ,	\nS ub ve rs io n,	\nG it h ub ,	\nB it b uck e t	\n●	\nC on ﬁ g ura tio n	\nM an ag em en t:	\nJ ir a ,	\nJ e nkin s,	\nC onﬂu e nce	\n\nP R O JE C TS	\nE X PER IE N CE	\n\nL u xo ft	\n@	\nA M D,	\nB en g alu ru	\n&ndash;	\nS enio r	\nS oft w are	\nE ng in e er	\n2 nd	\nM ay	\n2 0 23	\n&ndash;	\na t	\np re se nt	\n●	\nB oard	\nb rin g -u p	\nf o r	\nA AO SP	\na s	\nD UAN	\no n	\nt h e	\nU buntu /Y o cto	\np la tfo rm ,	\nu sin g	\na	\nh yp erv is o r.	\n●	\nS etu p	\na n d	\nc o nﬁg ura tio n	\no f	\nh yp erv is o r	\nf o r	\nd is p la y,	\nU SB ,	\na n d	\nd eb ug	\ns e tu p .	\n●	\nC usto m iz e d	\nA AO SP	\nf o r	\nc lie nt	\nn e ed s.	\n●	\nD eb ug ged	\na n d	\nﬁ xe d	\nA AO SP	\ni s su e s.	\n\nL u xo ft	\n@	\nF o rd	\nM oto rs ,	\nB en g alu ru	\n&ndash;	\nS oft w are	\nE ng in e er	\n9 th	\nJ u ly	\n2 0 21	\n&ndash;	\n1\ns t\nM ay	\n2 0 23	\n●	\nA O SP	\np la tfo rm	\nd eve lo pm ent	\na n d	\ne nh an ce m ent.	\n●	\nI m pro ve	\nt h e	\ns ta rtu p	\nt im e	\ni n	\nt h e	\nO S	\nl a ye r	\nw it h	\nl e ss	\nf u tu re	\nm ain te nan ce .	\n●	\nA TS ,	\nC TS	\ni s su e s	\nd eb ug gin g ,	\na n d	\nb ug	\nﬁ xin g\n\nH arm an	\nC on necte d	\nS erv ic e ,	\nB en g alu ru	\n&ndash;	\nS oft w are	\nE ng in e er-P ro d uct	\nD eve lo pm ent\n1 1th	\nN ov	\n2 0 19	\n&ndash;	\n5 th	\nJ u ly	\n2 0 21	\n●	\nM an ag ed	\nN AD	\ns ta te ,	\nC PU	\nu sa g e,	\na n d	\nm em ory	\no ptim iz a tio ns.	\n●	\nC ond ucte d	\nF O TA	\nu p d ate s	\nu sin g	\nR ed	\nB end .	\n●	\nW ork e d	\no n	\nA D AS	\nF FC ,	\nC FC	\ns e ttin g s,	\na n d	\ns y ste m	\na p p	\nc o m patib ilit y .	\n\nS ask e n	\nT e ch nolo g ie s,	\nB en g alu ru	\n-\nE N G IN EER	\n-\nA PP	\nS O FT W ARE	\nD ES IG N	\n&amp;	\n\nD EV ELO PM EN T\n1 0 th	\nJ a n	\n2 0 19	\n&ndash;	\n8\nt h	\nN ov	\n2 0 19	\n●	\nI m ple m ente d	\nR eal- T im e	\nT e xt	\nf o r	\nO re o .	\n●	\nC re ate d	\nc u sto m	\ns y ste m	\ns e rv ic e s	\nf o r	\nA nd ro id	\nO re o .	\nN atio n al	\nI n fo rm atic s	\nC en te r,	\nB en g alu ru	\n-\nA nd ro id	\nd eve lo per	\n1 s t	\nF e b	\n2 0 18	\n-\n7 th	\nJ a n	\n2 0 19	\n●	\nD eve lo ped	\na	\nR atio n	\nD is tr ib utio n	\nA pp	\nw it h	\nb io m etr ic	\na u th e ntic a tio n.	\nA gile	\nH ealt h	\nT e ch nolo g ie s,	\nB en g alu ru	\n-\nA nd ro id	\nd eve lo per	\n1 s t	\nA pril	\n2 0 17	\n-\n2 nd	\nJ a n	\n2 0 18	\n●	\nD eve lo ped	\nD r.S ah e li	\nA pp	\na n d	\nA H TN ET	\nT im esh e et	\na p plic a tio n.	\nE D U CATIO N\nN IE	\nI n stit u te	\no f	\nE ng in eerin g ,	\nM yso re	\n-\nB ach e lo r	\no f	\nE ng in e erin g	\ni n	\nE C E	\nS EP TEM BER	\n2 0 12	\n-\nA U G UST	\n2 0 16	\nS co re :	\n5 6 %	\nL .C	\nC olle g e,	\nB ih ar	\n-\nP U C	\nY EA R	\n2 0 11	\nS co re :	\n6 1%	\nS T	\nM ary &rsquo;s	\nH ig h	\nS ch ool,	\nJ h ark h an d	\n-\nS C H O OL	\nY EA R	\n2 0 08	\nS co re :	\n7 2 %', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-22 05:49:49', '2024-07-19 05:49:49', 0, NULL, NULL, '2024-07-19 04:27:13', 0),
(410, 97, 73, 35, NULL, '73_97_3304958496699f09ec2ab7_Bhushan_Bende_Developer_Connected_Platform_(1).pdf', 'Bhushan Bende_Developer_Connected Platform (1).pdf', 'Bhushan	Bende	\nSoftware	Engineer	\nRoles	:Senior	Software	Engineer	\nE-mail:	bhushanyahoo@gmail.com	\nMobile:	9405708908	\nProfessional	Synopsis:	\n	Experience	inPython	Developer	,Building	APIand	Data	Pipeline	,with	PRDomain	\n	Experience	onworking/building	Python-Fast	API	hosted	onLambda	connected	with	Elastic	Search	\n	Building	ETL	&amp;ELT	Data	Pipeline	inPython	with	AWS	Managed	Streaming	Application	Flink,	Self	Managed	Flink	and	AWS	Lambda	\n	5years	ofFunctional	and	Automation	Testing	experience	inInvestment	Banking	Domain	,Payment	Domain	and	Media	Monitoring.	\n	Keen	understanding	onCapital	Market	and	Money	Market.	\n	Well	versed	knowledge	ofPayments	system	and	Gateway	transaction	\n	Well	versed	inallphases	ofSoftware	Development	Life	Cycle	(SDLC)	and	Software	Testing	Life	Cycle	(STLC).	\n	Experience	inTesting	Web	Based	Application,	Windows	Based	Application	,Web-Service	and	Database	.	\n	Extensive	Knowledge	inwriting	Functional	and	Regression	Test-cases	,maintaining	and	modifying	test	cases.	\n	Proficient	inautomation	using	Selenium	Web-driver	with	Java	programming	language	.	\n	Extensive	knowledge	ofwriting	scripts	using	Element	locators	,Web-driver	methods	and	Java	Programming	.	\n	Generating	defect	report	and	interacting	with	developers	toresolve	the	defects.	\n	Having	good	exposure	todefect	management,	raising	defect/bugs.	\n	Having	good	time	management	towork	ondifferent	types	ofreleases	simultaneously	(BAU/OOC/Strategic).	\n	Has	rigorously	worked	onAPI	Testing	and	API	Test	Automation	with	JavaScript	-Mocha	Framework	\n	Extensive	knowledge	onvarious	testing	methodologies	like	UAT,	SIT,	Regression	testing,	Sanity	testing,	Smoke	testing,	and	\nFunctional	testing	.	\n	Experience	inusing	Test	Management	tool	HP-ALM,	JIRA	,Rally	.	\n	Great	exposure	toMS-OFFICE	suite	,Google	Suite	.	\n	Worked	extensively	onautomating	BFS	applications	from	enhancing	the	Automation	framework	inEclipse	using	Maven	tocommitting	\nthe	code	toBitBucket	/GITHUB	and	storing	test	artefacts	inJIRA	after	every	sprint	completion	.	\n	Have	working	experience	inCI/CD	model.	\n	Has	Good	Understanding	onEvent	Driven	System,	that	takes	data	asevent	process	it.	\n	Worked	onsetting	upKAFKA	and	KINESIS	for	Data	Stream	Processing	\n	Worked	onBuilding	Data	Pipeline	inPython	and	Deploying	itonAWS	Lambda	\n	Has	good	interpersonal,	communication	and	organizational	skill	with	ability	tointeract	effectively	with	colleagues	atalllevel.	\nTech	Stack:\nLanguages:	Python,	Core	Java,	SQL	,Javascript-NodeJS	\nOperating	System:	Windows,	Linux	,MacOS	\nTest	Management	Tool:	HP-ALM,	JIRA	,Rally	\nData	Base	Tools:	DBeaver,	MySQL,	Microsoft	SQL	Server	.,Google	Big	Query,	ElasticSearch	\nKnowledge	And	Worked	On:	API	Testing	with	POSTMAN,	API	Performance	Testing	with	JMeter	,ETL	Testing,	GCP,	AWS	EC2,	AWS	Lambda,	\nAWS	KINESIS,	Kafka,	Data	Streaming	Project,	API	Contract	Testing,	Docker	\nVersioning	Tool:	GIT	\nCertification:	GIT	(Udemy)	,AWS	API	GATEWAY(AWS),	GCP	KAFKA(GOOGLE),	Streaming	Pipeline	Using	Pyspark	and	Kakfa	\nAutomation	Framework	:BDD	-Cucumber,	TDD-	TestNG,	JavaScript	Mocha	\nAPI	Development	Framework	:Fast	API	Python	\nDeployment	Framework	:Zappa	\nAutomation	Tools:	Selenium	Web-driver,	Jenkins	,TestNG,	Cucumber	\nDeployment	Stack:	Kubernetes,	AWS	EKS	\nEmployment	Detail:	\nName	OfCompany	:Onclusive,	Mumbai	\nDesignation	:Senior	Software	Engineer	(Data	Engineer)	\nDuration	:19Oct	2022	ToCurrent	\nName	OfCompany	:TSYS	,Pune	\nDesignation	:Automation	Developer	\nDuration	:17May	2021	To	18Oct	2022	\nName	OfCompany	:Altimetrik,	Pune	\nDesignation	:Automation	Quality	Engineer	\nDuration	:18Jan	2021	To15May	2021	\nName	ofCompany	:Cognizant	Technology,	Pune	\nDesignation	:Test	Professional	\nDuration	:26June	2018	TO	15Jan	2021\n\nOnclusive	\nProject	1:	\nName	:Data	Platform	\nDesignation	:Senior	Software	Engineer	\nProject	Description	:Onclusive	isaMedia	Monitoring	Company.	Which,	monitors	the	Articles	,Content,	News,	Radio,	Youtube	and	also	TV	\nChannel.	Tofind	out	the	sentiment	for	the	particular	product	inmarket.	\nWhere	we	have	multiple	sources	who	pushes	Petabyte	ofdata	into	our	system	we	stream	that	into	MSK	Kafka	and	then	into	AWS	Kinesis	,using	\nData	Pipeline	asaconsumer	we	fetch	itand	process	ittoElastic	Search.(Elastic	stack)	\nAfterwards	this	used	for	sentiment	analysis	ofmarket	and	further,	using	API	this	Data	isfetch	and	given	toDown-Stream	Application	for	ML/AI	\npipeline.\nRole/Responsibility:	\n	ToDevelop	API	that	connects	with	Elastic-Search	and	fetch	out	data	with	relevant	query	that	we	build	run	time	.	\n	We	dohave	lots	ofAPI	that	exports	the	for	articles	based	onuser-query,	Iworked	onDeveloping	and	maintaining	API	\n	Todevelop	Data	Pipeline	Fetching	data	from	Apache	Kafka	and	AWS	Kinesis	then	transforming	and	Pushing	ittoStorage.(with	hosted	\nservice	onAWS	Lambda)	\n	Interm	tomodernize	these	pipeline	and	improving	the	performance	we	have	shifted	toApache	Flink	and	Apache	Beam	Pipeline	\no	Where	itfetch	data	from	Kafka,	using	UDF	we	modify	and	transform	this	data	and	push	itback	toElastic	Sink.	\no	Elastic	Sink	isself	managed	service	that	push	data	toElastic	Search	\n	Responsible	for	developing	and	deploying	the	API-P	oller	onAWS	ECS	tofetch	data	from	various	API	sources,	transform	it,and	store	it	\ninto	S3before	pushing	ittoKinesis	for	further	processing.	\nOther	Responsibilites	:	\n	Taking	part	inDesigning	Data	Pipeline	\n	Modernizing	Data	Pipelines	\no	Earlier	we	were	using	AWS	Kinesis	for	our	Data	Streaming,	now	we	have	designed	the	pipeline	touse	Kafka	which	has	good	\nRetention	period	and	also	tomaintain	the	AWS	Cost	itwill	becheaper	than	Kinesis.	\n	Adding	Layer	for	Open-Telemetry	intoServerless	AWS	Lambda	tocapture	telemetry	data	for	Failure	Analysis	\n	Deploying	StateFullset	ElasticSearch	InKubernetes	\n	Streaming	Data	Processing	On	Apache	Beam	Pipeline	\nProject	2:	\nName	:Data	Platform	\nDesignation	:Automation	Developer	\nProject	Description	:Onclusive	isaMedia	Monitoring	Company.	Which,	monitors	the	Articles	,Content,	News,	Radio,	Youtube	and	also	TV	\nChannel.	Tofind	out	the	sentiment	for	the	particular	product	inmarket.	\nWhere	we	have	multiple	sources	who	pushes	Petabyte	ofdata	into	our	system	we	stream	that	into	MSK	Kafka	and	then	into	AWS	Kinesis	,using	\nBroadcast	pipeline	asaconsumer	we	fetch	itand	process	ittoElasticSearch.	\nAfterwards	this	used	for	sentiment	analysis	ofmarket	and	further,	using	API	this	Data	isfetch	and	given	toDown-Stream	Application	for	ML/AI	\npipeline.\nRole/Responsibility:	Worked	asaAutomation	Architect	\n	ToDevelop	API	Automation	Framework	based	onNodeJS-JavaScript.	\n	Inclusion	ofBDD	inNode-JS	Framework.	\n	Maintaining	Automation	Framework	asaQA	Engineer	for	allthe	In-scope	API	\n	Completing	Testing	using	Manual	Testcases	and	Automation	\nOther	Responsibilites	:	\n	Taking	part	inDesigning	Data	Pipeline	\n	Modernizing	Data	Pipelines	\no	Earlier	we	were	using	AWS	Kinesis	for	our	Data	Streaming,	now	we	have	designed	the	pipeline	touse	Kafka	which	has	good	\nRetention	period	and	also	tomaintain	the	AWS	Cost	itwill	becheaper	than	Kinesis.	\n	Adding	Layer	for	Open-Telemetry	intoServerless	AWS	Lambda	tocapture	telemetry	data	for	Failure	Analysis\n\nTSYS	:Project	Worked	On	\nProject	1:	\nName	:UCP	-Global	Payments	\nDesignation	:Automation	Developer	\nProject	Description	:	\nAsaglobal	payments	we	wants	our	Merchants	has	full	capabilities	toselect	their	transaction	gateway	asper	their	own	\nconvenience	sothat	they	can	decide	their	security	level	and	transaction	changes	asper	area	they	are	serving	.Asaresult	we	have	created	aGlobal	\nPlatform	when	Global	Payment	will	board	Merchants	onUnified	Platform	(Unified	Commerce	Platform)	that	itwill	gives	right	toMerchants	toselect	\ngateway	without	any	code	changes.	\nHere	we	asaGlobal	Payments	will	take	care	ofinternal	transformation	and	Merchant	just	need	toplug	out	APIs	and	start	\nplaying	the	business	without	worrying	about	their	internal	transaction	transformation.	\nProject	2:	\nName	:Propay	Enterprise	Integration	\nDesignation	:Automation	Developer	\nProject	Description	:	\nAsTSYS,	AGlobal	Payments	Company,	we	act	asamediator	between	payment	gateways,	platform	and	Merchant.	\nMindBody	asaclient	comes	toGlobal	Payments	with	ask	that	they	want	tomigrate	their	allMerchant	toPROPAY	platform.	We	GPAPI	handles	their	\nTransaction,	Merchant	Boarding	Requirement	and	other	POS	devices	requirement	within	Single	Request.	\nArchitecture	works	like	take	abase	request	from	Merchant(Mindbody	Merchant)	segregate	and	convert	that	request	into	required	request	form	\nDownstream	I.ePROPAY,	TransIT,	SoundPayment,	PAX	Portal,	Express.	Receive	the	response	and	send	ittomerchant.	\nAsnumber	ofFinancial	entities	comes	into	picture	with	this	project,	ithas	avery	huge	scope.	Itincludes	payment	processing	and	merchant	\nprocessing.\nRole/Responsibility:	\n	Asbeing	aintegral	part	ofEnterprise	Integration	Team	my	responsibilities	were	related	togather	and	understand	the	latest	\nchanges/requirements	for	the	Gateway	Release	.	\n	Write	functional	and	regression	test	cases.	Used	POSTMAN	for	API	Testing	\n	Execute	manually	functional	and	regression	pack,	manage	test	cases	inRally	\n	Raise	defect	and	communicate	with	developers	toresolve	it.	\n	Reporting	Bugs,	verifying	logs,	verifying	server-side	services,	verifying	data,	generating	SQL	scripts	for	Database	changes.	\n	Verify	other	dependent	systems	are	receiving	proper	transaction	message	and	help	them	for	payments	booking	scenarios.	\n	Create	and	Execute	Automat	ion	Test	Scripts,	inNodeJS	based	framework	inJavaScript	.	\n	Verify	API-Integration	working	asexpected	\n	API	Performance	testing	with	JMete	r	\n	Generating	Sign-off	report	with	notifying	that	everything	isworking	fine	with	allnew	changes,	sothat	allnew	requirements	should	be	\nlive	inproduction	inupcoming	bi-weekly	release.	\n	Handling	multiple	developers	overseas.	\n	Communicating	with	Dev-ops	team	tocheck	new	build-changes,	DB-changes,	services	side	changes.	\n	Experience	inworking	with	Agile	and	CI/CD	testing	Models	.	\nAltimetrik	:Projet	Worked	On	:	\nProject	:	\nName	:CitiBank	-High	Value	Payments	\nDesignation	:Quality	Engineer	\nProject	Description	:	\nFew	High	Valued	Customers	are	tied	up	with	CitiBank,	they	transact	huge	amount	ofmoney	per	Business	Day.	We	have	\ncreated	DashBoards	tokeep	atrack	ontheir	transactions	and	check	and	observe	what	isthe	status	for	that	payment	and	transactions,	Inthe	form	\nonGraphs	and	Tabular	Data	we	are	displaying	data	.	\nRoles/Responsibility	:	\n	Write	Test	Cases	For	various	Dash-Board	showing	different	Types	ofData	Analysis	for	Payments.	\n	Analyse	Requirement	From	JIRA/BRD/FRD	\n	DB	Testing	with	high	number	ofHigh	Valued	Payment	with	Different	Types	OfMOP	(Mode	OfPayments)	\n	UITesting	-Verify	Data	Calculation	and	computation	for	the	Data	from	DB	iscorrect.	\n	Functional	And	Regression	Testing.	\n	Create	UIAutomation	Framework	Based	onJava	Selenium	BDD	-Cucumber.\n\nCognizant	:Project	Worked	On:	\nProject	1:	\nName	:Global	Markets	(Global	Securities	Lending)-	Trade	Execution	and	Management	(Short	&ndash;Selling)	\nClient:	Credit	Suisse	\nProject	Type	:Functional	And	Automation	Testing	\nDuration:	24Sept	2018	toJan	2021	\nProject	Description:	\nCredit	Suisse	uses	anapplication	toBook	trades	for	Short	Selling.	Where	Borrow,	Loan	and	Collateral	Trades	were	booked	\nevery	day,	this	isavery	heavy	application	asitisused	bynumber	ofusers	allover	the	Globe.	\nRole/Responsibility:	\n	Togather	and	understand	the	latest	changes/requirements	for	the	release	from	Business	Requirement	Documents.	\n	Write	functional	and	regression	test	cases.	\n	Execute	manually	functional	and	regression	pack,	manage	test	cases	inQuality	Centre	-HP	ALM	\n	Raise	defect	and	communicate	with	developers	toresolve	it.	\n	Reporting	Bugs,	verifying	logs,	verifying	server-side	services,	verifying	data,	generating	SQL	scripts	for	Database	changes.	\n	Verify	other	dependent	systems	are	receiving	proper	trade	message	and	help	them	for	trade	booking	scenarios.	\n	Create	and	Execute	Automated	Test	Scripts,	and	verifying	results.	\n	Verify	API-Integration	working	asexpected	\n	API	Performance	testing	with	JMete	r	\n	Generating	Sign-off	report	with	notifying	that	everything	isworking	fine	with	allnew	changes,	sothat	allnew	requirements	should	be	\nlive	inproduction	inupcoming	bi-weekly	release.	\n	Taken	initiative	toenhance	automation	ofWeb	Based	Application	using	Selenium	WebDriver	with	IDE	Eclipse	.		Handling	multiple	developers	overseas.	\n	Communicating	with	Dev-ops	team	tocheck	new	build-changes,	DB-changes,	services	side	changes.	\n	Experience	inworking	with	Agile	and	CI/CD	testing	Models	.	\nProject	2:	\nName	:Security	Financing	Transaction	Regulation	\nClient:	Credit	Suisse	\nProject	Type	:Functional	Testing	\nDuration:	Jan	2020	toJan	2021	\nProject	Description:	\nThis	isaglobal	change	where	every	Investment	Bank,	needs	toreport	their	allEurope	based	transaction,	tothe	certain	\nReporting	Entity.	\nRole/Responsibility:	\n	Togather	and	understand	the	change	from	Business	Requirement	Documents.	\n	Write	functional	and	regression	test	cases.	\n	Execute	manually	functional	and	regression	pack.	\n	Raise	defect	and	communicate	with	developers	toresolve	it.	\n	Verifying	logs,	verifying	server-side	services,	verifying	data,	generating	SQL	scripts	for	Database	testing.	\n	Verify	other	dependent	systems	are	receiving	proper	trade	message	and	help	them	for	trade	booking	scenarios.	\nProject	3:	\nName:	Fixed	Income	Securities	\nClient:	Credit	Suisse	\nProject	Type:	Functional	Testing/API	Testing	\nDuration:	March	2020	toMay	2020	\nProject	Description:	\nFixed	Income	securities	tobeimplemented	for	certain	Client/Counterparties	with	specified	entity	directions,	\nFor	that	combination	ofClient	and	Fixed	Income	Securities	system	calculating	rate	and	fetching	them	from	API	end	point.\n\nRole/Responsibility:	\n	Togather	and	understand	the	changes.	\n	Verify	API-Integration	working	asexpected.	\n	Write	and	execute	manual	and	regression	pack.	\n	Verify	logs,	DB	testing	reporting	defect	\n	Performance	testing	for	API	with	JMeter	.	\nAcademic	Details:	\nSr.No	Qualification	University/Board	Passing	Year	Percentage	\n1.	Executive	PDGM	MIT	SDE	2022	Grade	A	\n2.	Bachelor	inComputer	Application	Amravati	University	2017	68%	\n3.	HSC	Maharashtra	State	Board	2014	62.46%	\n4.	SSC	Maharashtra	State	Board	2012	82.55%	\nOther	Qualification	Details:	\nSerialNo.	Qualification	University	/Board	Passing	Year	Percentage	\n1.	Eng-Typing	30	Maharashtra	State	Council	ofExamination,	Pune	Dec-2012	65%	\n2.	Eng-Typing	40	Maharashtra	State	Council	ofExamination,	Pune	Dec-2012	51%	\n3.	MS-CIT	Maharashtra	State	Board	OfTechnical	Education,Mumbai	July-2010	92%	\nSelf-Learning	Project:\n	Project	1:Text	files	reader.	(Text	tospeech).	(Using	python	and	GTTS	library)		Project	2:QR	code	generator	(Using	Python)		Project	3:Speech	totext	(Using	Python	and	Google	Speech	Recognition	Library)	\nAchievement:	\n	Awarded	as&ldquo;Pillar	OfThe	Month	&ldquo;(Cognizant	May	2019)		Best	&ldquo;Student	ofYear	&rdquo;(CMCS	2017)	\nPersonal	Details:	\nName:	Bhushan	Ashokrao	Bende	Dob:	18/01/1996	Permanent	Address:	Old	Gilani	Nagar,	Yavatmal	445001	Maharashtra	Current	Address:	Venkat-Padmavati	PGbehind	Persistent,	Hinjewadi	,411057	Pune	Strength:	Good	Communication,	Quick	learner	Hobby:	Cooking,	Gardening	Languages	known:	English,	Marathi,	Hindi	\nMobile	+91	9405708908	\nEmail:	Primary:	bhushanyahoo@gmail.com	\nDeclaration:	Ihereby	declare	that	the	above	information	istrue	tothe	best	ofmy	knowledge	and	allnecessary	documents	will	beprovided	as&amp;	\nwhen	required.	\nSignature:	Bhushan	Ashokrao	Bende	\nDate:	Place:	Pune', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, '2024-07-22 04:53:18', '2024-07-19 04:53:18', 0, NULL, NULL, '2024-07-19 04:50:38', 0),
(411, 98, 1, 4, NULL, '1_98_3441068586699f950dcc08_Bhushan_Bende_Developer_Connected_Platform_(1).pdf', 'Bhushan Bende_Developer_Connected Platform (1).pdf', 'Bhushan	Bende	\nSoftware	Engineer	\nRoles	:Senior	Software	Engineer	\nE-mail:	bhushanyahoo@gmail.com	\nMobile:	9405708908	\nProfessional	Synopsis:	\n	Experience	inPython	Developer	,Building	APIand	Data	Pipeline	,with	PRDomain	\n	Experience	onworking/building	Python-Fast	API	hosted	onLambda	connected	with	Elastic	Search	\n	Building	ETL	&amp;ELT	Data	Pipeline	inPython	with	AWS	Managed	Streaming	Application	Flink,	Self	Managed	Flink	and	AWS	Lambda	\n	5years	ofFunctional	and	Automation	Testing	experience	inInvestment	Banking	Domain	,Payment	Domain	and	Media	Monitoring.	\n	Keen	understanding	onCapital	Market	and	Money	Market.	\n	Well	versed	knowledge	ofPayments	system	and	Gateway	transaction	\n	Well	versed	inallphases	ofSoftware	Development	Life	Cycle	(SDLC)	and	Software	Testing	Life	Cycle	(STLC).	\n	Experience	inTesting	Web	Based	Application,	Windows	Based	Application	,Web-Service	and	Database	.	\n	Extensive	Knowledge	inwriting	Functional	and	Regression	Test-cases	,maintaining	and	modifying	test	cases.	\n	Proficient	inautomation	using	Selenium	Web-driver	with	Java	programming	language	.	\n	Extensive	knowledge	ofwriting	scripts	using	Element	locators	,Web-driver	methods	and	Java	Programming	.	\n	Generating	defect	report	and	interacting	with	developers	toresolve	the	defects.	\n	Having	good	exposure	todefect	management,	raising	defect/bugs.	\n	Having	good	time	management	towork	ondifferent	types	ofreleases	simultaneously	(BAU/OOC/Strategic).	\n	Has	rigorously	worked	onAPI	Testing	and	API	Test	Automation	with	JavaScript	-Mocha	Framework	\n	Extensive	knowledge	onvarious	testing	methodologies	like	UAT,	SIT,	Regression	testing,	Sanity	testing,	Smoke	testing,	and	\nFunctional	testing	.	\n	Experience	inusing	Test	Management	tool	HP-ALM,	JIRA	,Rally	.	\n	Great	exposure	toMS-OFFICE	suite	,Google	Suite	.	\n	Worked	extensively	onautomating	BFS	applications	from	enhancing	the	Automation	framework	inEclipse	using	Maven	tocommitting	\nthe	code	toBitBucket	/GITHUB	and	storing	test	artefacts	inJIRA	after	every	sprint	completion	.	\n	Have	working	experience	inCI/CD	model.	\n	Has	Good	Understanding	onEvent	Driven	System,	that	takes	data	asevent	process	it.	\n	Worked	onsetting	upKAFKA	and	KINESIS	for	Data	Stream	Processing	\n	Worked	onBuilding	Data	Pipeline	inPython	and	Deploying	itonAWS	Lambda	\n	Has	good	interpersonal,	communication	and	organizational	skill	with	ability	tointeract	effectively	with	colleagues	atalllevel.	\nTech	Stack:\nLanguages:	Python,	Core	Java,	SQL	,Javascript-NodeJS	\nOperating	System:	Windows,	Linux	,MacOS	\nTest	Management	Tool:	HP-ALM,	JIRA	,Rally	\nData	Base	Tools:	DBeaver,	MySQL,	Microsoft	SQL	Server	.,Google	Big	Query,	ElasticSearch	\nKnowledge	And	Worked	On:	API	Testing	with	POSTMAN,	API	Performance	Testing	with	JMeter	,ETL	Testing,	GCP,	AWS	EC2,	AWS	Lambda,	\nAWS	KINESIS,	Kafka,	Data	Streaming	Project,	API	Contract	Testing,	Docker	\nVersioning	Tool:	GIT	\nCertification:	GIT	(Udemy)	,AWS	API	GATEWAY(AWS),	GCP	KAFKA(GOOGLE),	Streaming	Pipeline	Using	Pyspark	and	Kakfa	\nAutomation	Framework	:BDD	-Cucumber,	TDD-	TestNG,	JavaScript	Mocha	\nAPI	Development	Framework	:Fast	API	Python	\nDeployment	Framework	:Zappa	\nAutomation	Tools:	Selenium	Web-driver,	Jenkins	,TestNG,	Cucumber	\nDeployment	Stack:	Kubernetes,	AWS	EKS	\nEmployment	Detail:	\nName	OfCompany	:Onclusive,	Mumbai	\nDesignation	:Senior	Software	Engineer	(Data	Engineer)	\nDuration	:19Oct	2022	ToCurrent	\nName	OfCompany	:TSYS	,Pune	\nDesignation	:Automation	Developer	\nDuration	:17May	2021	To	18Oct	2022	\nName	OfCompany	:Altimetrik,	Pune	\nDesignation	:Automation	Quality	Engineer	\nDuration	:18Jan	2021	To15May	2021	\nName	ofCompany	:Cognizant	Technology,	Pune	\nDesignation	:Test	Professional	\nDuration	:26June	2018	TO	15Jan	2021\n\nOnclusive	\nProject	1:	\nName	:Data	Platform	\nDesignation	:Senior	Software	Engineer	\nProject	Description	:Onclusive	isaMedia	Monitoring	Company.	Which,	monitors	the	Articles	,Content,	News,	Radio,	Youtube	and	also	TV	\nChannel.	Tofind	out	the	sentiment	for	the	particular	product	inmarket.	\nWhere	we	have	multiple	sources	who	pushes	Petabyte	ofdata	into	our	system	we	stream	that	into	MSK	Kafka	and	then	into	AWS	Kinesis	,using	\nData	Pipeline	asaconsumer	we	fetch	itand	process	ittoElastic	Search.(Elastic	stack)	\nAfterwards	this	used	for	sentiment	analysis	ofmarket	and	further,	using	API	this	Data	isfetch	and	given	toDown-Stream	Application	for	ML/AI	\npipeline.\nRole/Responsibility:	\n	ToDevelop	API	that	connects	with	Elastic-Search	and	fetch	out	data	with	relevant	query	that	we	build	run	time	.	\n	We	dohave	lots	ofAPI	that	exports	the	for	articles	based	onuser-query,	Iworked	onDeveloping	and	maintaining	API	\n	Todevelop	Data	Pipeline	Fetching	data	from	Apache	Kafka	and	AWS	Kinesis	then	transforming	and	Pushing	ittoStorage.(with	hosted	\nservice	onAWS	Lambda)	\n	Interm	tomodernize	these	pipeline	and	improving	the	performance	we	have	shifted	toApache	Flink	and	Apache	Beam	Pipeline	\no	Where	itfetch	data	from	Kafka,	using	UDF	we	modify	and	transform	this	data	and	push	itback	toElastic	Sink.	\no	Elastic	Sink	isself	managed	service	that	push	data	toElastic	Search	\n	Responsible	for	developing	and	deploying	the	API-P	oller	onAWS	ECS	tofetch	data	from	various	API	sources,	transform	it,and	store	it	\ninto	S3before	pushing	ittoKinesis	for	further	processing.	\nOther	Responsibilites	:	\n	Taking	part	inDesigning	Data	Pipeline	\n	Modernizing	Data	Pipelines	\no	Earlier	we	were	using	AWS	Kinesis	for	our	Data	Streaming,	now	we	have	designed	the	pipeline	touse	Kafka	which	has	good	\nRetention	period	and	also	tomaintain	the	AWS	Cost	itwill	becheaper	than	Kinesis.	\n	Adding	Layer	for	Open-Telemetry	intoServerless	AWS	Lambda	tocapture	telemetry	data	for	Failure	Analysis	\n	Deploying	StateFullset	ElasticSearch	InKubernetes	\n	Streaming	Data	Processing	On	Apache	Beam	Pipeline	\nProject	2:	\nName	:Data	Platform	\nDesignation	:Automation	Developer	\nProject	Description	:Onclusive	isaMedia	Monitoring	Company.	Which,	monitors	the	Articles	,Content,	News,	Radio,	Youtube	and	also	TV	\nChannel.	Tofind	out	the	sentiment	for	the	particular	product	inmarket.	\nWhere	we	have	multiple	sources	who	pushes	Petabyte	ofdata	into	our	system	we	stream	that	into	MSK	Kafka	and	then	into	AWS	Kinesis	,using	\nBroadcast	pipeline	asaconsumer	we	fetch	itand	process	ittoElasticSearch.	\nAfterwards	this	used	for	sentiment	analysis	ofmarket	and	further,	using	API	this	Data	isfetch	and	given	toDown-Stream	Application	for	ML/AI	\npipeline.\nRole/Responsibility:	Worked	asaAutomation	Architect	\n	ToDevelop	API	Automation	Framework	based	onNodeJS-JavaScript.	\n	Inclusion	ofBDD	inNode-JS	Framework.	\n	Maintaining	Automation	Framework	asaQA	Engineer	for	allthe	In-scope	API	\n	Completing	Testing	using	Manual	Testcases	and	Automation	\nOther	Responsibilites	:	\n	Taking	part	inDesigning	Data	Pipeline	\n	Modernizing	Data	Pipelines	\no	Earlier	we	were	using	AWS	Kinesis	for	our	Data	Streaming,	now	we	have	designed	the	pipeline	touse	Kafka	which	has	good	\nRetention	period	and	also	tomaintain	the	AWS	Cost	itwill	becheaper	than	Kinesis.	\n	Adding	Layer	for	Open-Telemetry	intoServerless	AWS	Lambda	tocapture	telemetry	data	for	Failure	Analysis\n\nTSYS	:Project	Worked	On	\nProject	1:	\nName	:UCP	-Global	Payments	\nDesignation	:Automation	Developer	\nProject	Description	:	\nAsaglobal	payments	we	wants	our	Merchants	has	full	capabilities	toselect	their	transaction	gateway	asper	their	own	\nconvenience	sothat	they	can	decide	their	security	level	and	transaction	changes	asper	area	they	are	serving	.Asaresult	we	have	created	aGlobal	\nPlatform	when	Global	Payment	will	board	Merchants	onUnified	Platform	(Unified	Commerce	Platform)	that	itwill	gives	right	toMerchants	toselect	\ngateway	without	any	code	changes.	\nHere	we	asaGlobal	Payments	will	take	care	ofinternal	transformation	and	Merchant	just	need	toplug	out	APIs	and	start	\nplaying	the	business	without	worrying	about	their	internal	transaction	transformation.	\nProject	2:	\nName	:Propay	Enterprise	Integration	\nDesignation	:Automation	Developer	\nProject	Description	:	\nAsTSYS,	AGlobal	Payments	Company,	we	act	asamediator	between	payment	gateways,	platform	and	Merchant.	\nMindBody	asaclient	comes	toGlobal	Payments	with	ask	that	they	want	tomigrate	their	allMerchant	toPROPAY	platform.	We	GPAPI	handles	their	\nTransaction,	Merchant	Boarding	Requirement	and	other	POS	devices	requirement	within	Single	Request.	\nArchitecture	works	like	take	abase	request	from	Merchant(Mindbody	Merchant)	segregate	and	convert	that	request	into	required	request	form	\nDownstream	I.ePROPAY,	TransIT,	SoundPayment,	PAX	Portal,	Express.	Receive	the	response	and	send	ittomerchant.	\nAsnumber	ofFinancial	entities	comes	into	picture	with	this	project,	ithas	avery	huge	scope.	Itincludes	payment	processing	and	merchant	\nprocessing.\nRole/Responsibility:	\n	Asbeing	aintegral	part	ofEnterprise	Integration	Team	my	responsibilities	were	related	togather	and	understand	the	latest	\nchanges/requirements	for	the	Gateway	Release	.	\n	Write	functional	and	regression	test	cases.	Used	POSTMAN	for	API	Testing	\n	Execute	manually	functional	and	regression	pack,	manage	test	cases	inRally	\n	Raise	defect	and	communicate	with	developers	toresolve	it.	\n	Reporting	Bugs,	verifying	logs,	verifying	server-side	services,	verifying	data,	generating	SQL	scripts	for	Database	changes.	\n	Verify	other	dependent	systems	are	receiving	proper	transaction	message	and	help	them	for	payments	booking	scenarios.	\n	Create	and	Execute	Automat	ion	Test	Scripts,	inNodeJS	based	framework	inJavaScript	.	\n	Verify	API-Integration	working	asexpected	\n	API	Performance	testing	with	JMete	r	\n	Generating	Sign-off	report	with	notifying	that	everything	isworking	fine	with	allnew	changes,	sothat	allnew	requirements	should	be	\nlive	inproduction	inupcoming	bi-weekly	release.	\n	Handling	multiple	developers	overseas.	\n	Communicating	with	Dev-ops	team	tocheck	new	build-changes,	DB-changes,	services	side	changes.	\n	Experience	inworking	with	Agile	and	CI/CD	testing	Models	.	\nAltimetrik	:Projet	Worked	On	:	\nProject	:	\nName	:CitiBank	-High	Value	Payments	\nDesignation	:Quality	Engineer	\nProject	Description	:	\nFew	High	Valued	Customers	are	tied	up	with	CitiBank,	they	transact	huge	amount	ofmoney	per	Business	Day.	We	have	\ncreated	DashBoards	tokeep	atrack	ontheir	transactions	and	check	and	observe	what	isthe	status	for	that	payment	and	transactions,	Inthe	form	\nonGraphs	and	Tabular	Data	we	are	displaying	data	.	\nRoles/Responsibility	:	\n	Write	Test	Cases	For	various	Dash-Board	showing	different	Types	ofData	Analysis	for	Payments.	\n	Analyse	Requirement	From	JIRA/BRD/FRD	\n	DB	Testing	with	high	number	ofHigh	Valued	Payment	with	Different	Types	OfMOP	(Mode	OfPayments)	\n	UITesting	-Verify	Data	Calculation	and	computation	for	the	Data	from	DB	iscorrect.	\n	Functional	And	Regression	Testing.	\n	Create	UIAutomation	Framework	Based	onJava	Selenium	BDD	-Cucumber.\n\nCognizant	:Project	Worked	On:	\nProject	1:	\nName	:Global	Markets	(Global	Securities	Lending)-	Trade	Execution	and	Management	(Short	&ndash;Selling)	\nClient:	Credit	Suisse	\nProject	Type	:Functional	And	Automation	Testing	\nDuration:	24Sept	2018	toJan	2021	\nProject	Description:	\nCredit	Suisse	uses	anapplication	toBook	trades	for	Short	Selling.	Where	Borrow,	Loan	and	Collateral	Trades	were	booked	\nevery	day,	this	isavery	heavy	application	asitisused	bynumber	ofusers	allover	the	Globe.	\nRole/Responsibility:	\n	Togather	and	understand	the	latest	changes/requirements	for	the	release	from	Business	Requirement	Documents.	\n	Write	functional	and	regression	test	cases.	\n	Execute	manually	functional	and	regression	pack,	manage	test	cases	inQuality	Centre	-HP	ALM	\n	Raise	defect	and	communicate	with	developers	toresolve	it.	\n	Reporting	Bugs,	verifying	logs,	verifying	server-side	services,	verifying	data,	generating	SQL	scripts	for	Database	changes.	\n	Verify	other	dependent	systems	are	receiving	proper	trade	message	and	help	them	for	trade	booking	scenarios.	\n	Create	and	Execute	Automated	Test	Scripts,	and	verifying	results.	\n	Verify	API-Integration	working	asexpected	\n	API	Performance	testing	with	JMete	r	\n	Generating	Sign-off	report	with	notifying	that	everything	isworking	fine	with	allnew	changes,	sothat	allnew	requirements	should	be	\nlive	inproduction	inupcoming	bi-weekly	release.	\n	Taken	initiative	toenhance	automation	ofWeb	Based	Application	using	Selenium	WebDriver	with	IDE	Eclipse	.		Handling	multiple	developers	overseas.	\n	Communicating	with	Dev-ops	team	tocheck	new	build-changes,	DB-changes,	services	side	changes.	\n	Experience	inworking	with	Agile	and	CI/CD	testing	Models	.	\nProject	2:	\nName	:Security	Financing	Transaction	Regulation	\nClient:	Credit	Suisse	\nProject	Type	:Functional	Testing	\nDuration:	Jan	2020	toJan	2021	\nProject	Description:	\nThis	isaglobal	change	where	every	Investment	Bank,	needs	toreport	their	allEurope	based	transaction,	tothe	certain	\nReporting	Entity.	\nRole/Responsibility:	\n	Togather	and	understand	the	change	from	Business	Requirement	Documents.	\n	Write	functional	and	regression	test	cases.	\n	Execute	manually	functional	and	regression	pack.	\n	Raise	defect	and	communicate	with	developers	toresolve	it.	\n	Verifying	logs,	verifying	server-side	services,	verifying	data,	generating	SQL	scripts	for	Database	testing.	\n	Verify	other	dependent	systems	are	receiving	proper	trade	message	and	help	them	for	trade	booking	scenarios.	\nProject	3:	\nName:	Fixed	Income	Securities	\nClient:	Credit	Suisse	\nProject	Type:	Functional	Testing/API	Testing	\nDuration:	March	2020	toMay	2020	\nProject	Description:	\nFixed	Income	securities	tobeimplemented	for	certain	Client/Counterparties	with	specified	entity	directions,	\nFor	that	combination	ofClient	and	Fixed	Income	Securities	system	calculating	rate	and	fetching	them	from	API	end	point.\n\nRole/Responsibility:	\n	Togather	and	understand	the	changes.	\n	Verify	API-Integration	working	asexpected.	\n	Write	and	execute	manual	and	regression	pack.	\n	Verify	logs,	DB	testing	reporting	defect	\n	Performance	testing	for	API	with	JMeter	.	\nAcademic	Details:	\nSr.No	Qualification	University/Board	Passing	Year	Percentage	\n1.	Executive	PDGM	MIT	SDE	2022	Grade	A	\n2.	Bachelor	inComputer	Application	Amravati	University	2017	68%	\n3.	HSC	Maharashtra	State	Board	2014	62.46%	\n4.	SSC	Maharashtra	State	Board	2012	82.55%	\nOther	Qualification	Details:	\nSerialNo.	Qualification	University	/Board	Passing	Year	Percentage	\n1.	Eng-Typing	30	Maharashtra	State	Council	ofExamination,	Pune	Dec-2012	65%	\n2.	Eng-Typing	40	Maharashtra	State	Council	ofExamination,	Pune	Dec-2012	51%	\n3.	MS-CIT	Maharashtra	State	Board	OfTechnical	Education,Mumbai	July-2010	92%	\nSelf-Learning	Project:\n	Project	1:Text	files	reader.	(Text	tospeech).	(Using	python	and	GTTS	library)		Project	2:QR	code	generator	(Using	Python)		Project	3:Speech	totext	(Using	Python	and	Google	Speech	Recognition	Library)	\nAchievement:	\n	Awarded	as&ldquo;Pillar	OfThe	Month	&ldquo;(Cognizant	May	2019)		Best	&ldquo;Student	ofYear	&rdquo;(CMCS	2017)	\nPersonal	Details:	\nName:	Bhushan	Ashokrao	Bende	Dob:	18/01/1996	Permanent	Address:	Old	Gilani	Nagar,	Yavatmal	445001	Maharashtra	Current	Address:	Venkat-Padmavati	PGbehind	Persistent,	Hinjewadi	,411057	Pune	Strength:	Good	Communication,	Quick	learner	Hobby:	Cooking,	Gardening	Languages	known:	English,	Marathi,	Hindi	\nMobile	+91	9405708908	\nEmail:	Primary:	bhushanyahoo@gmail.com	\nDeclaration:	Ihereby	declare	that	the	above	information	istrue	tothe	best	ofmy	knowledge	and	allnecessary	documents	will	beprovided	as&amp;	\nwhen	required.	\nSignature:	Bhushan	Ashokrao	Bende	\nDate:	Place:	Pune', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-22 05:38:03', '2024-07-19 05:38:03', 0, NULL, NULL, '2024-07-19 05:27:44', 0);
INSERT INTO `resume` (`id`, `screeningId`, `adminId`, `candidateId`, `candidateDetailsId`, `resumeName`, `resumeOriginalName`, `resumeContent`, `isSkillScreened`, `isResumeScreened`, `isCron`, `isCandidate`, `candidateShortlist`, `enableInterviewReport`, `gptLanguageId`, `isInterviewAssign`, `interviewValidity`, `interviewAssignDate`, `isPsychoAssign`, `psychoValidity`, `psychoAssignDate`, `created`, `createdBy`) VALUES
(412, 99, 73, 45, NULL, '73_99_1603179284669a1cfada254_HMI_Developer-John_Stanish_Pandian.pdf', 'HMI Developer-John Stanish Pandian.pdf', 'Android Native Mobile App	lication	 	Developer	 	\n \nJOHN STANISH	 	\nChennai, Tamil Nadu	 	\n+91 8220004353	 	\ns	tan	y	john	9	3	@gmail.com	 	\n \nPROFILE &bull; ABOUT ME	 	\n \nA pioneering and security	-	oriented developer offering more than 	Eight	 	years&rsquo; experience designing, 	\nimplementing, integrating, testing and supporting impactful applications developed in diverse, collaborative \nenvironments for mobile devices on the Android platform	 	\n&bull;	 	Known for writing efficient, maintainable and reusable code that preserves privacy and security	 	\n&bull;	 	Expert in the interaction between various devices, screen sizes and different versions of Android	 	\n&bull;	 	Regarded as a self	-	motivated and well	-	organised team player	 	\n&bull;	 	Provided oversight and mentorship to a small team of developers	 	\n \nACADEMIC QUALIFICATION	 	\n 	\n&bull;	 	Completed B.E in the stream of Electronics and Communication in SRM Easwari Engineering \nCollege, Chennai with 8.02 CGPA, Year of completion 	-	 	2015.	 	\n&bull;	 	H.S.L.C in 	Start Matriculation Higher Secondary School, Tuticorin. Secured 93.75%. Year of 	\ncompletion 	-	 	2011.	 	\n&bull;	 	S.S.L.C in St. Joseph&rsquo;s Matriculation School, Tuticorin. Secured 89.5%. Year of completion 	-	 	2009.	 	\n \nWORK EXPERIENCE	 	\n 	\nRole &amp; Designation	 	Senior	 Analyst	 	&ndash;	 	Programmer	 	\nCompany	 	Ford Motor Company	 	\nDuration	 	Feb	 	2022	 	-	 	Present	 	\nLocation	 	CHENNAI, Tamil Nadu	 	\n \nTASKS AND RESPONSIBILITIES	 	\n&bull;	 	Develop native Android application using Kotlin in combi	nation with Jetpack Compose ensuring 	\nhigh	-	quality user experiences and seamless functionality	.	 	\n&bull;	 	Utilized Jira to effectively m	anage project tasks, track progress and facilitate efficient communication 	\namong team mem	bers	.	 	\n&bull;	 	Used Modern Android Development Libr	aries such as 	Jetpack Compose, Room	, Coroutines/Flow, 	\nDataStore	 	a	nd Da	gger	-	Hilt	 	\n&bull;	 	Authored J	u	nit 	tests using Mockito frameworks ensuring robust code quali	ty and minimizing 	\nregression issues.	 	\n&bull;	 	Applied design 	patterns such as MVVM to create scalable and mainta	ina	ble codebases 	improving 	\ncode organization and 	reusability.	 	\n \n 	\nC	oding	 	L	anguages	 	Java, Kotlin	 	\nD	atabase	 	SQLite, Room	 	\nVe r s i o n   C o n t r o l	 	GitHub	 	\nDevelopment T	ool	 	Android studio\n\nPROJECT EXPERIENCE	 	\n \nFordPass	 	&amp; 	Lincoln	 	Way	 	\n&bull;	 	Maintained, refined, and developed features for Ford&#039;s Ford	P	ass and 	Lincoln Way	 	automotive 	\napplications as part of a large team.	 	\n&bull;	 	Features I was responsible for include user vehicle authorization, 	A	dd vehicle, 	F	uel telemetry	, 	\nTPMS, 	Vehicle 	health, Vehicle Alerts, Vehicle Service related features, 	R	oad Side Assistance, 	\nCollision 	Assista	nce, 	Accounts which include	s 	Message 	centre	, Change 	Username	 	&amp; Password, 	\nVehicle feat	ure notifications, user 	information	, Delete Account	. 	 	\n&bull;	 	Rebuilt key features from a monolithic application to a modularized version that improved build \ntime.	 	\n&bull;	 	Utilized third party analytics to 	analyse	 	customer experience and track application stability.	 	\n&bull;	 	Work in an agile environment with a 	6	 	person android development feature team to consistently meet 	\ndeadlines for product deliverables while also providing support for existing features.	 	\n&bull;	 	Educated new hires about company best practices and paradigms to quickly develop the	 	necessary 	\nskills required to be a productive member of the team.	 	\n 	\nR	ole &amp; Designation	 	IT Analyst 	&ndash;	 Te a m  	Lead	 	\nCompany	 	TATA  C O N S U LTA N C Y  S E RV I C E S   LT D	 	\nDuration	 	Nov 2015 	&ndash;	 	Jan 2022	 	\nLocation	 	CHENNAI, Tamil Nadu	 	\n \nTASKS AND RESPONSIBILITIES	 	\n&bull;	 	C	onceptualised, designed, developed and deployed mobile applications for banking customers in 	\nGoogle play store and Apple store.	 	\n&bull;	 	Developed update patches, modules and components to mitigate security risks.	 	\n&bull;	 	L	ead	 	a team of 6, responsible for the development and maintenance of banking	 	applications in 	\nAndroid	.	 	\n \nSKILLS	 	\n&bull;	 	Expert at Android SDK design 	functionality, including the full activity lifecycle	.	 	\n&bull;	 	Clear and concise writer of communications and development documentation	.	 	\n&bull;	 	Strong Experience in OOPs Concepts, Exception handling	.	 	\n&bull;	 	Worked on Firebase Push Notifications, Crashlytics	 	and App distributions	.	 	\n&bull;	 	Well versed with Android Components like Services, Broadcast receivers, Fragments	 	and	 	a	ctivit	ies	.	 	\n&bull;	 	Worked on Location API, Geocoding	.	 	\n&bull;	 	Strong in web services using Retrofit library, performing fetch and sending data to server	.	 	\n&bull;	 	Knowledgeable about 	back	-	end development and documentation	.	 	\n&bull;	 	Worked on MVVM architecture, Offline storage (such as SQLite, Room)	.	 	\n&bull;	 	Having good knowledge of Android Jetpack Libraries (such as View Modal, Lifecycle, Live data	, 	\nData binding, Navigation, Fragments, Cards, Recycler view, Biomet	rics	)	, Kotlin Coroutines, RxJava, 	\nDependency injection using Dagger 2	.	 	\n 	\nC	oding	 	L	anguages	 	Java, Kotlin	 	\nD	atabase	 	SQLite, Room	 	\nVe r s i o n   C o n t r o l	 	GitHub	 	\nDevelopment T	ool	 	Android studio\n\nPROJECT EXPERIENCE	 	\n \nCUB mBank Plus (City Union Bank)	 	\n&bull;	 	Implemented push notifications using Firebase cloud messaging	 	 	\n&bull;	 	Redesigned the app with separate layouts and drawables to support multiple screen sizes and \ndensities	 	 	\n&bull;	 	Reduced application crashes by implementing Firebase Crashlytics, which helped in an increase in \nGoogle Play Store rating	 	\n&bull;	 	Enhanced the UI by using Google material design components	 	\n&bull;	 	Implemented OTP auto capture using 	SMS Retriever API	 	\n&bull;	 	Implemented Fingerprint based login authentication 	 	\n \nCUB BHIM UPI &amp; eWallet  (City Union Bank)	 	\n&bull;	 	Implemented QR Code Scanner	 	Using Camera and from Gallery using Google Zxing Library	 	\n&bull;	 	Experience in user specific QR Code generation 	for UPI payment	 	\n&bull;	 	Implemented User mobile number specific Device Binding.	 	\n&bull;	 	Integrated NPCI&rsquo;s UPI library for displaying 	payment 	authentication 	screen	 	\n&bull;	 	Experience in fetching the user location when they are using the application.	 	\n \nCUB Corporate Mobile (City Union Bank)	 	\n&bull;	 	Experience in password hashing using SHA1 &amp; SHA512	 	\n&bull;	 	Experience in request and response Encryption and decryption using AES algorithms 	 	\n&bull;	 	Implemented SSL Pinning for 	establishing a secure connection.	 	\n&bull;	 	Developed this app specifically for bank&rsquo;s corporate customers with maker &amp; checker login.	 	\n&bull;	 	Experience in 	publishing the app to Google Play store.	 	\n \n \nPERSONAL INFORMATION	 	\n 	\nDate of Birth	 	October 12, 1993	 	\nGender	 	Male	 	\nMarital Status	 	Married	 	\nNationality	 	India	 	\nLanguages Known	 	English, Tamil', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-22 08:46:28', '2024-07-19 08:46:28', 0, NULL, NULL, '2024-07-19 07:59:54', 0),
(413, 100, 73, 35, NULL, '73_100_2022332361669a303361016_Bhushan_Bende_Developer_Connected_Platform_(1).pdf', 'Bhushan Bende_Developer_Connected Platform (1).pdf', 'Bhushan	Bende	\nSoftware	Engineer	\nRoles	:Senior	Software	Engineer	\nE-mail:	bhushanyahoo@gmail.com	\nMobile:	9405708908	\nProfessional	Synopsis:	\n	Experience	inPython	Developer	,Building	APIand	Data	Pipeline	,with	PRDomain	\n	Experience	onworking/building	Python-Fast	API	hosted	onLambda	connected	with	Elastic	Search	\n	Building	ETL	&amp;ELT	Data	Pipeline	inPython	with	AWS	Managed	Streaming	Application	Flink,	Self	Managed	Flink	and	AWS	Lambda	\n	5years	ofFunctional	and	Automation	Testing	experience	inInvestment	Banking	Domain	,Payment	Domain	and	Media	Monitoring.	\n	Keen	understanding	onCapital	Market	and	Money	Market.	\n	Well	versed	knowledge	ofPayments	system	and	Gateway	transaction	\n	Well	versed	inallphases	ofSoftware	Development	Life	Cycle	(SDLC)	and	Software	Testing	Life	Cycle	(STLC).	\n	Experience	inTesting	Web	Based	Application,	Windows	Based	Application	,Web-Service	and	Database	.	\n	Extensive	Knowledge	inwriting	Functional	and	Regression	Test-cases	,maintaining	and	modifying	test	cases.	\n	Proficient	inautomation	using	Selenium	Web-driver	with	Java	programming	language	.	\n	Extensive	knowledge	ofwriting	scripts	using	Element	locators	,Web-driver	methods	and	Java	Programming	.	\n	Generating	defect	report	and	interacting	with	developers	toresolve	the	defects.	\n	Having	good	exposure	todefect	management,	raising	defect/bugs.	\n	Having	good	time	management	towork	ondifferent	types	ofreleases	simultaneously	(BAU/OOC/Strategic).	\n	Has	rigorously	worked	onAPI	Testing	and	API	Test	Automation	with	JavaScript	-Mocha	Framework	\n	Extensive	knowledge	onvarious	testing	methodologies	like	UAT,	SIT,	Regression	testing,	Sanity	testing,	Smoke	testing,	and	\nFunctional	testing	.	\n	Experience	inusing	Test	Management	tool	HP-ALM,	JIRA	,Rally	.	\n	Great	exposure	toMS-OFFICE	suite	,Google	Suite	.	\n	Worked	extensively	onautomating	BFS	applications	from	enhancing	the	Automation	framework	inEclipse	using	Maven	tocommitting	\nthe	code	toBitBucket	/GITHUB	and	storing	test	artefacts	inJIRA	after	every	sprint	completion	.	\n	Have	working	experience	inCI/CD	model.	\n	Has	Good	Understanding	onEvent	Driven	System,	that	takes	data	asevent	process	it.	\n	Worked	onsetting	upKAFKA	and	KINESIS	for	Data	Stream	Processing	\n	Worked	onBuilding	Data	Pipeline	inPython	and	Deploying	itonAWS	Lambda	\n	Has	good	interpersonal,	communication	and	organizational	skill	with	ability	tointeract	effectively	with	colleagues	atalllevel.	\nTech	Stack:\nLanguages:	Python,	Core	Java,	SQL	,Javascript-NodeJS	\nOperating	System:	Windows,	Linux	,MacOS	\nTest	Management	Tool:	HP-ALM,	JIRA	,Rally	\nData	Base	Tools:	DBeaver,	MySQL,	Microsoft	SQL	Server	.,Google	Big	Query,	ElasticSearch	\nKnowledge	And	Worked	On:	API	Testing	with	POSTMAN,	API	Performance	Testing	with	JMeter	,ETL	Testing,	GCP,	AWS	EC2,	AWS	Lambda,	\nAWS	KINESIS,	Kafka,	Data	Streaming	Project,	API	Contract	Testing,	Docker	\nVersioning	Tool:	GIT	\nCertification:	GIT	(Udemy)	,AWS	API	GATEWAY(AWS),	GCP	KAFKA(GOOGLE),	Streaming	Pipeline	Using	Pyspark	and	Kakfa	\nAutomation	Framework	:BDD	-Cucumber,	TDD-	TestNG,	JavaScript	Mocha	\nAPI	Development	Framework	:Fast	API	Python	\nDeployment	Framework	:Zappa	\nAutomation	Tools:	Selenium	Web-driver,	Jenkins	,TestNG,	Cucumber	\nDeployment	Stack:	Kubernetes,	AWS	EKS	\nEmployment	Detail:	\nName	OfCompany	:Onclusive,	Mumbai	\nDesignation	:Senior	Software	Engineer	(Data	Engineer)	\nDuration	:19Oct	2022	ToCurrent	\nName	OfCompany	:TSYS	,Pune	\nDesignation	:Automation	Developer	\nDuration	:17May	2021	To	18Oct	2022	\nName	OfCompany	:Altimetrik,	Pune	\nDesignation	:Automation	Quality	Engineer	\nDuration	:18Jan	2021	To15May	2021	\nName	ofCompany	:Cognizant	Technology,	Pune	\nDesignation	:Test	Professional	\nDuration	:26June	2018	TO	15Jan	2021\n\nOnclusive	\nProject	1:	\nName	:Data	Platform	\nDesignation	:Senior	Software	Engineer	\nProject	Description	:Onclusive	isaMedia	Monitoring	Company.	Which,	monitors	the	Articles	,Content,	News,	Radio,	Youtube	and	also	TV	\nChannel.	Tofind	out	the	sentiment	for	the	particular	product	inmarket.	\nWhere	we	have	multiple	sources	who	pushes	Petabyte	ofdata	into	our	system	we	stream	that	into	MSK	Kafka	and	then	into	AWS	Kinesis	,using	\nData	Pipeline	asaconsumer	we	fetch	itand	process	ittoElastic	Search.(Elastic	stack)	\nAfterwards	this	used	for	sentiment	analysis	ofmarket	and	further,	using	API	this	Data	isfetch	and	given	toDown-Stream	Application	for	ML/AI	\npipeline.\nRole/Responsibility:	\n	ToDevelop	API	that	connects	with	Elastic-Search	and	fetch	out	data	with	relevant	query	that	we	build	run	time	.	\n	We	dohave	lots	ofAPI	that	exports	the	for	articles	based	onuser-query,	Iworked	onDeveloping	and	maintaining	API	\n	Todevelop	Data	Pipeline	Fetching	data	from	Apache	Kafka	and	AWS	Kinesis	then	transforming	and	Pushing	ittoStorage.(with	hosted	\nservice	onAWS	Lambda)	\n	Interm	tomodernize	these	pipeline	and	improving	the	performance	we	have	shifted	toApache	Flink	and	Apache	Beam	Pipeline	\no	Where	itfetch	data	from	Kafka,	using	UDF	we	modify	and	transform	this	data	and	push	itback	toElastic	Sink.	\no	Elastic	Sink	isself	managed	service	that	push	data	toElastic	Search	\n	Responsible	for	developing	and	deploying	the	API-P	oller	onAWS	ECS	tofetch	data	from	various	API	sources,	transform	it,and	store	it	\ninto	S3before	pushing	ittoKinesis	for	further	processing.	\nOther	Responsibilites	:	\n	Taking	part	inDesigning	Data	Pipeline	\n	Modernizing	Data	Pipelines	\no	Earlier	we	were	using	AWS	Kinesis	for	our	Data	Streaming,	now	we	have	designed	the	pipeline	touse	Kafka	which	has	good	\nRetention	period	and	also	tomaintain	the	AWS	Cost	itwill	becheaper	than	Kinesis.	\n	Adding	Layer	for	Open-Telemetry	intoServerless	AWS	Lambda	tocapture	telemetry	data	for	Failure	Analysis	\n	Deploying	StateFullset	ElasticSearch	InKubernetes	\n	Streaming	Data	Processing	On	Apache	Beam	Pipeline	\nProject	2:	\nName	:Data	Platform	\nDesignation	:Automation	Developer	\nProject	Description	:Onclusive	isaMedia	Monitoring	Company.	Which,	monitors	the	Articles	,Content,	News,	Radio,	Youtube	and	also	TV	\nChannel.	Tofind	out	the	sentiment	for	the	particular	product	inmarket.	\nWhere	we	have	multiple	sources	who	pushes	Petabyte	ofdata	into	our	system	we	stream	that	into	MSK	Kafka	and	then	into	AWS	Kinesis	,using	\nBroadcast	pipeline	asaconsumer	we	fetch	itand	process	ittoElasticSearch.	\nAfterwards	this	used	for	sentiment	analysis	ofmarket	and	further,	using	API	this	Data	isfetch	and	given	toDown-Stream	Application	for	ML/AI	\npipeline.\nRole/Responsibility:	Worked	asaAutomation	Architect	\n	ToDevelop	API	Automation	Framework	based	onNodeJS-JavaScript.	\n	Inclusion	ofBDD	inNode-JS	Framework.	\n	Maintaining	Automation	Framework	asaQA	Engineer	for	allthe	In-scope	API	\n	Completing	Testing	using	Manual	Testcases	and	Automation	\nOther	Responsibilites	:	\n	Taking	part	inDesigning	Data	Pipeline	\n	Modernizing	Data	Pipelines	\no	Earlier	we	were	using	AWS	Kinesis	for	our	Data	Streaming,	now	we	have	designed	the	pipeline	touse	Kafka	which	has	good	\nRetention	period	and	also	tomaintain	the	AWS	Cost	itwill	becheaper	than	Kinesis.	\n	Adding	Layer	for	Open-Telemetry	intoServerless	AWS	Lambda	tocapture	telemetry	data	for	Failure	Analysis\n\nTSYS	:Project	Worked	On	\nProject	1:	\nName	:UCP	-Global	Payments	\nDesignation	:Automation	Developer	\nProject	Description	:	\nAsaglobal	payments	we	wants	our	Merchants	has	full	capabilities	toselect	their	transaction	gateway	asper	their	own	\nconvenience	sothat	they	can	decide	their	security	level	and	transaction	changes	asper	area	they	are	serving	.Asaresult	we	have	created	aGlobal	\nPlatform	when	Global	Payment	will	board	Merchants	onUnified	Platform	(Unified	Commerce	Platform)	that	itwill	gives	right	toMerchants	toselect	\ngateway	without	any	code	changes.	\nHere	we	asaGlobal	Payments	will	take	care	ofinternal	transformation	and	Merchant	just	need	toplug	out	APIs	and	start	\nplaying	the	business	without	worrying	about	their	internal	transaction	transformation.	\nProject	2:	\nName	:Propay	Enterprise	Integration	\nDesignation	:Automation	Developer	\nProject	Description	:	\nAsTSYS,	AGlobal	Payments	Company,	we	act	asamediator	between	payment	gateways,	platform	and	Merchant.	\nMindBody	asaclient	comes	toGlobal	Payments	with	ask	that	they	want	tomigrate	their	allMerchant	toPROPAY	platform.	We	GPAPI	handles	their	\nTransaction,	Merchant	Boarding	Requirement	and	other	POS	devices	requirement	within	Single	Request.	\nArchitecture	works	like	take	abase	request	from	Merchant(Mindbody	Merchant)	segregate	and	convert	that	request	into	required	request	form	\nDownstream	I.ePROPAY,	TransIT,	SoundPayment,	PAX	Portal,	Express.	Receive	the	response	and	send	ittomerchant.	\nAsnumber	ofFinancial	entities	comes	into	picture	with	this	project,	ithas	avery	huge	scope.	Itincludes	payment	processing	and	merchant	\nprocessing.\nRole/Responsibility:	\n	Asbeing	aintegral	part	ofEnterprise	Integration	Team	my	responsibilities	were	related	togather	and	understand	the	latest	\nchanges/requirements	for	the	Gateway	Release	.	\n	Write	functional	and	regression	test	cases.	Used	POSTMAN	for	API	Testing	\n	Execute	manually	functional	and	regression	pack,	manage	test	cases	inRally	\n	Raise	defect	and	communicate	with	developers	toresolve	it.	\n	Reporting	Bugs,	verifying	logs,	verifying	server-side	services,	verifying	data,	generating	SQL	scripts	for	Database	changes.	\n	Verify	other	dependent	systems	are	receiving	proper	transaction	message	and	help	them	for	payments	booking	scenarios.	\n	Create	and	Execute	Automat	ion	Test	Scripts,	inNodeJS	based	framework	inJavaScript	.	\n	Verify	API-Integration	working	asexpected	\n	API	Performance	testing	with	JMete	r	\n	Generating	Sign-off	report	with	notifying	that	everything	isworking	fine	with	allnew	changes,	sothat	allnew	requirements	should	be	\nlive	inproduction	inupcoming	bi-weekly	release.	\n	Handling	multiple	developers	overseas.	\n	Communicating	with	Dev-ops	team	tocheck	new	build-changes,	DB-changes,	services	side	changes.	\n	Experience	inworking	with	Agile	and	CI/CD	testing	Models	.	\nAltimetrik	:Projet	Worked	On	:	\nProject	:	\nName	:CitiBank	-High	Value	Payments	\nDesignation	:Quality	Engineer	\nProject	Description	:	\nFew	High	Valued	Customers	are	tied	up	with	CitiBank,	they	transact	huge	amount	ofmoney	per	Business	Day.	We	have	\ncreated	DashBoards	tokeep	atrack	ontheir	transactions	and	check	and	observe	what	isthe	status	for	that	payment	and	transactions,	Inthe	form	\nonGraphs	and	Tabular	Data	we	are	displaying	data	.	\nRoles/Responsibility	:	\n	Write	Test	Cases	For	various	Dash-Board	showing	different	Types	ofData	Analysis	for	Payments.	\n	Analyse	Requirement	From	JIRA/BRD/FRD	\n	DB	Testing	with	high	number	ofHigh	Valued	Payment	with	Different	Types	OfMOP	(Mode	OfPayments)	\n	UITesting	-Verify	Data	Calculation	and	computation	for	the	Data	from	DB	iscorrect.	\n	Functional	And	Regression	Testing.	\n	Create	UIAutomation	Framework	Based	onJava	Selenium	BDD	-Cucumber.\n\nCognizant	:Project	Worked	On:	\nProject	1:	\nName	:Global	Markets	(Global	Securities	Lending)-	Trade	Execution	and	Management	(Short	&ndash;Selling)	\nClient:	Credit	Suisse	\nProject	Type	:Functional	And	Automation	Testing	\nDuration:	24Sept	2018	toJan	2021	\nProject	Description:	\nCredit	Suisse	uses	anapplication	toBook	trades	for	Short	Selling.	Where	Borrow,	Loan	and	Collateral	Trades	were	booked	\nevery	day,	this	isavery	heavy	application	asitisused	bynumber	ofusers	allover	the	Globe.	\nRole/Responsibility:	\n	Togather	and	understand	the	latest	changes/requirements	for	the	release	from	Business	Requirement	Documents.	\n	Write	functional	and	regression	test	cases.	\n	Execute	manually	functional	and	regression	pack,	manage	test	cases	inQuality	Centre	-HP	ALM	\n	Raise	defect	and	communicate	with	developers	toresolve	it.	\n	Reporting	Bugs,	verifying	logs,	verifying	server-side	services,	verifying	data,	generating	SQL	scripts	for	Database	changes.	\n	Verify	other	dependent	systems	are	receiving	proper	trade	message	and	help	them	for	trade	booking	scenarios.	\n	Create	and	Execute	Automated	Test	Scripts,	and	verifying	results.	\n	Verify	API-Integration	working	asexpected	\n	API	Performance	testing	with	JMete	r	\n	Generating	Sign-off	report	with	notifying	that	everything	isworking	fine	with	allnew	changes,	sothat	allnew	requirements	should	be	\nlive	inproduction	inupcoming	bi-weekly	release.	\n	Taken	initiative	toenhance	automation	ofWeb	Based	Application	using	Selenium	WebDriver	with	IDE	Eclipse	.		Handling	multiple	developers	overseas.	\n	Communicating	with	Dev-ops	team	tocheck	new	build-changes,	DB-changes,	services	side	changes.	\n	Experience	inworking	with	Agile	and	CI/CD	testing	Models	.	\nProject	2:	\nName	:Security	Financing	Transaction	Regulation	\nClient:	Credit	Suisse	\nProject	Type	:Functional	Testing	\nDuration:	Jan	2020	toJan	2021	\nProject	Description:	\nThis	isaglobal	change	where	every	Investment	Bank,	needs	toreport	their	allEurope	based	transaction,	tothe	certain	\nReporting	Entity.	\nRole/Responsibility:	\n	Togather	and	understand	the	change	from	Business	Requirement	Documents.	\n	Write	functional	and	regression	test	cases.	\n	Execute	manually	functional	and	regression	pack.	\n	Raise	defect	and	communicate	with	developers	toresolve	it.	\n	Verifying	logs,	verifying	server-side	services,	verifying	data,	generating	SQL	scripts	for	Database	testing.	\n	Verify	other	dependent	systems	are	receiving	proper	trade	message	and	help	them	for	trade	booking	scenarios.	\nProject	3:	\nName:	Fixed	Income	Securities	\nClient:	Credit	Suisse	\nProject	Type:	Functional	Testing/API	Testing	\nDuration:	March	2020	toMay	2020	\nProject	Description:	\nFixed	Income	securities	tobeimplemented	for	certain	Client/Counterparties	with	specified	entity	directions,	\nFor	that	combination	ofClient	and	Fixed	Income	Securities	system	calculating	rate	and	fetching	them	from	API	end	point.\n\nRole/Responsibility:	\n	Togather	and	understand	the	changes.	\n	Verify	API-Integration	working	asexpected.	\n	Write	and	execute	manual	and	regression	pack.	\n	Verify	logs,	DB	testing	reporting	defect	\n	Performance	testing	for	API	with	JMeter	.	\nAcademic	Details:	\nSr.No	Qualification	University/Board	Passing	Year	Percentage	\n1.	Executive	PDGM	MIT	SDE	2022	Grade	A	\n2.	Bachelor	inComputer	Application	Amravati	University	2017	68%	\n3.	HSC	Maharashtra	State	Board	2014	62.46%	\n4.	SSC	Maharashtra	State	Board	2012	82.55%	\nOther	Qualification	Details:	\nSerialNo.	Qualification	University	/Board	Passing	Year	Percentage	\n1.	Eng-Typing	30	Maharashtra	State	Council	ofExamination,	Pune	Dec-2012	65%	\n2.	Eng-Typing	40	Maharashtra	State	Council	ofExamination,	Pune	Dec-2012	51%	\n3.	MS-CIT	Maharashtra	State	Board	OfTechnical	Education,Mumbai	July-2010	92%	\nSelf-Learning	Project:\n	Project	1:Text	files	reader.	(Text	tospeech).	(Using	python	and	GTTS	library)		Project	2:QR	code	generator	(Using	Python)		Project	3:Speech	totext	(Using	Python	and	Google	Speech	Recognition	Library)	\nAchievement:	\n	Awarded	as&ldquo;Pillar	OfThe	Month	&ldquo;(Cognizant	May	2019)		Best	&ldquo;Student	ofYear	&rdquo;(CMCS	2017)	\nPersonal	Details:	\nName:	Bhushan	Ashokrao	Bende	Dob:	18/01/1996	Permanent	Address:	Old	Gilani	Nagar,	Yavatmal	445001	Maharashtra	Current	Address:	Venkat-Padmavati	PGbehind	Persistent,	Hinjewadi	,411057	Pune	Strength:	Good	Communication,	Quick	learner	Hobby:	Cooking,	Gardening	Languages	known:	English,	Marathi,	Hindi	\nMobile	+91	9405708908	\nEmail:	Primary:	bhushanyahoo@gmail.com	\nDeclaration:	Ihereby	declare	that	the	above	information	istrue	tothe	best	ofmy	knowledge	and	allnecessary	documents	will	beprovided	as&amp;	\nwhen	required.	\nSignature:	Bhushan	Ashokrao	Bende	\nDate:	Place:	Pune', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-22 09:33:25', '2024-07-19 09:33:25', 0, NULL, NULL, '2024-07-19 09:21:55', 0),
(414, 101, 73, 38, NULL, '73_101_1436010278669b9464b85c2_HMI_Developer-Swapnil_Thamake.pdf', 'HMI Developer-Swapnil_Thamake.pdf', 'Sw ap nil  T h am ake  \nTe am  L e ad  \n                                             \nap plic a tio n i m pro ve m en ts . C urre n t p ro je ct w ork in g  o n F o rd  C re d it  ( ﬁ nte ch ) a n d  L a st p ro je ct w as w ork e d\n                                       \nsw ap 3848@ gm ail .c o m  \n\nPune, I n d ia  \nlin ke d in .c o m /in /s w ap nil - t h am ake -2 14314a0  \nWORK  E X PER IE N CE \nTe am  L e ad  \nTe ch  M ah in d ra  \n04/2 022 -  P re se n t\n, \n  Pun e \nFo rd  C re d it  A pplic a tio n : ( F in te ch ) \nLe ad in g  t o  m y 2  b ud dy&#039;s  a n d  d eve lo pin g  M obil e  A pplic a tio n\nis  b ase d  o n ﬁ nan cia l a n d  a cco unt m an ag em en t s e rv ic e s \nUse  s k il ls  C ode o ptim iz a tio n, A pplic a tio n s e cu rit y , d esig n\npatte rn s a n d  r e so lv e  l o w  p erfo rm an ce  i s su es. \n                 \n           \nAsso cia te  C onsu lt a n t \nCap gem in i I n d ia  \n02/2 020 -  0 4/2 022\n, \n  Pun e \nHSB C B an k I n dia  \nWork e d  o n F in an ce  D om ain  &amp;  B an kin g  d o m ain  a p plic a tio n.\nIm ple m en te d  s o rt in g , s e arc h in g  a lg o rit h m s a n d  d esig n\npatte rn s. \n                         \nQR c o de, T ra n sa ctio n h is to ry , R ais e  d is p ute . \nAnd ro id , K otlin , R xJav a , D ag ger 2 ,M VP, R etro ﬁ t, J e n kin s,\n                    \nConte xt, H ooks. \nApplic a tio n E ng in eer -  M obil e  A pplic a tio n\nDeve lo per \nRaw  E n g in eerin g  I n d . P vt. L td . \n08/2 018 -  0 1/2 020\n, \n  Vir a r -  M um bai \nIn  R aw  E ngin eerin g i  h ave  w ork e d  o n s p o rt s  d o m ain  p ro je cts  \n                   \n                             \nso rt in g  a n d  s e arc h in g  a lg o rit h m s. \n                 \nRetro ﬁ t, J e n kin s, G it , A W S, X M PP,F ir e b ase , C ra sh ly tic s \nMobil e  A pplic a tio n D eve lo per \nG.N .R eatil  S e rv ic e s P vt. L td .( Z ap m art .c o m ) \n05/2 016 -  0 7/2 018\n, \n  Mum bai \nZa p m art  i s  O nlin e G ro ce ry  P ro du ct B ase d  C om pan y \nReq uir e m en t &amp;  A naly sis , D esig n a n d  D eve lo p A pplic a tio ns,\nWrit e  A PI&#039;s , W ork  o n B ack -e n d  a n d  D B. \nWork e d  o n z a p m art  a p plic a tio n w hic h  b ase d  o n o nlin e\ngro ce ry  s to re . D eve lo ped  o rd er t ra ck in g  f u nctio nalit y  u sin g\nGoogle  M ap . \nAnd ro id , j a v a , V olle y, G it , B it b uck e t, S Q LLit e , F ir e b ase ,\nCra sh ly tic s. \nSK IL L S  \nAnd ro id  S D K \nJav a  \nGit h u b  \nSQ Lit e  \nRest A PI \nMyS Q L \nFir e b ase  \nRxJav a  \nSo narQ  \nAW S \nMVC \nMVVM  \nRO OM  \nJIR A  \nMock it o  \nSyste m  D esig n \nKotlin  \nMult iT h re ad in g  \nJe tp ack  \n \n    \nAlg o rit h m s \nRetro ﬁ t \nData  s tru ctu re  \nFir e b ase  \nRxJav a  \nLiv e d ata  \nReact N ativ e  \nTyp esc rip t \n    \n \n \n  \nPR O FE SSIO NAL P R O JE C TS \nFo rd  C re d it\n ( 0 4/2 022 -  P re se n t)\n \nHSB C b an kin g\n ( 0 3/2 020 -  0 4/2 022)\n \nHaw ks A re n a F a rm  S ta te  &amp;  S acra m en to  K in g &#039;s\n ( 0 1/2 019 -  0 1/2 020)\n \nJD  P ow er\n ( 0 8/2 018 -  1 2/2 018)\n \nMed ic a lw ale  D octo r A pp\n ( 0 3/2 018 -  0 7/2 018)\n \nza p m art .c o m\n ( 0 8/2 016 -  0 1/2 018)\n \nED UCATIO N \nMCA  ( M aste r i n  C om pute r A pplic a tio n) \nKIT &#039;S  I M ER  K olh ap ur \n07/2 013 -  0 6/2 016\n, \n  Kolh ap u r,M ah ara sh tra , I n dia  \nBCA  \nGopal K ris h n a G okh ale  C olle g e K olh ap ur \n06/2 009 -  0 4/2 012\n, \n  Kolh ap u r ,  M ah ara sh tra  ,  I n dia  \n12th  \nS.M .L o hia  C olle g e, K olh ap ur \n06/2 007 -  0 2/2 009\n, \n  Kolh ap u r \n10th  \nJyo tir lin g  v id ya m an d ir  V ad an ag e \n06/2 002 -  0 3/2 007\n, \n  Kolh ap u r \nIN TER EST S \nPho to gra p hy \nSin g in g  \nCric k e t \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s 	\nUnitTest	\nMVP\nAOSP	\nSplunk	CSS	  Jacoco	\n8369096660	\nMobile Application Developer with 8 years of experience in coding, team lead, architecture design and\non HSBC Bank on financial domain . I have also worked on Sports, Health Care, Automative and E-Commerce.	\nReact Native, Typescript, Android, Kotlin, MVVM,\nJWT, Jetpack, Coroutine, Git, Splunk\nDeveloped application with key features like money transfer,\nNexus, SonarQ, Git, SSL pinning, React Native,\nDeveloped application for NBA teams and Automative App\nLive score update with xmpp protocol. Used multithreading,\nAndroid, Java, Kotlin, RxJava, Dagger2, MVP, AOSP,', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-23 10:45:06', '2024-07-20 10:45:06', 0, NULL, NULL, '2024-07-20 10:41:40', 0),
(415, 102, 76, NULL, NULL, '76_102_175841139669d1c38ece8c_Aashi-Resume_(1).pdf', 'Aashi-Resume (1).pdf', 'OBJE C TIV ES	\nSkil le d  S o ft w are  D eve lo p er w it h  2 +ye a rs  o f\nh an d s-o n   exp erie n ce   in   ChatB ot\nD eve lo p m en t  .S eekin g a  c h alle n ge  ro le  to\na p ply  m y e xp ertis e  in  cre a tin g in nova tiv e\nso ft w are  s o lu tio n s a n d  c o lla b ora tin g w it h  a\nt a le n te d  d eve lo p m en t t e a m .	\nSK IL LS	\nP R O GRAM MIN G S K IL LS\nN od e J S  ,  M ic ro so ft  B ot F ra m ew ork  ,	 	\nJ a va S crip t\nTO OLS\nV is u al S tu d io  C od e ,  E m ula to r ,  M on go d b	 	\nC om pass	\nC ER TIF IC AT ES	\nKore .A I B ot b asic  a n d  a d va n ce d .\nO pen  A I A P I a n d  C H AT  G PT f o r d eve lo p ers	 	\nb y U dem y.	\nE D U CAT IO N	\nB.T e ch  	, E le ctr ic a l 	,  8 .0 1 	cg p a, 	\nM adha v 	In stit u te  	O f 	T e ch n olo g y 	&amp;  	Scie n ce	\n0 7/2 017 &ndash;  0 6/2 021	    	\nG w alio r, M ad hya  P ra d esh\n1 2th  	,8 3.8 % , 	N atio n a l 	C hil d re n  	H ig h 	\nSeco n d a ry  	S ch ool,B ada ga on	\n2017	 |  G w alio r, M ad hya  P ra d esh	\nP R O FE SS IO NAL E X P ER IE N CE	\nSYS T EM  	EN GIN EER  	, T AT A  	CO NSU LT A N CY 	\nS ER VIC ES (T C S )\n06/2 021 &ndash;  p re se n t	 |  D elh i,	 I n d ia	\n&bull;I  h ave  g a in ed  e xp erie n ce  i n  c h atb ot d eve lo p m en t	 	\nacro ss N LU  p la tfo rm s l ik e  M ic ro so ft  B ot F ra m ew ork	 	\ns d k f o r v a rio u s c h an nels  l ik e  m s t e a m s ,  d ir e ctlin e	 	\nusin g N od e j s  .\n&bull;P ro fic ie n t i n  b uil d in g R EST fu l A P Is  a n d  w ork in g w it h	 	\nM on go D B t o  m an age  a n d  q uery  d ata . A d ep t a t	 	\nco lla b ora tin g w it h  c ro ss -fu n ctio n al t e a m s t o  d eliv e r	 	\nh ig h -q ualit y  s o ft w are  s o lu tio n s u sin g N od e j s . I  h ave	 	\nw ork  w it h  d if fe re n t t e a m s t o  d eliv e r h ig h  q ualit y	 	\np ro je cts  a n d  c o n tr ib ute d  t o  a  p osit iv e  t e a m	 	\nen vir o n m en t b y p ro vid in g g u id an ce  a n d  s u p port t o	 	\nte a m  m em bers .\n&bull;U til iz e d  a n d  I n te g ra te d  Q nA M ake r/ L a n gu age  S tu d io	 	\ni n to  a  c u sto m  c h atb ot a p plic a tio n  t o  c re a te  a	 	\nK now le d ge  b ase  o f f r e q uen tly  a sk e d  q uestio n s,	 	\nim pro vin g r e sp on se  t im es ,  a cc u ra cy  a n d  e n ab lin g	 	\nnatu ra l l a n gu age  i n te ra ctio n s w it h  u se rs .\n&bull;In te g ra te d  t h e c h atb ot w it h  o th er s y ste m s, d ata b ase s	 	\na n d  A P Is  t o  a cce ss a n d  r e tr ie ve  r e le va n t i n fo rm atio n .\n&bull;In te g ra te d  L U IS /C LU  f o r i n te n t r e co gn it io n  a n d  e n tit y	 	\ne xtra ctio n  ,  e n han cin g t h e c h atb ot	 	\nu n d ers ta n d  a n d  u se r q uerie s.\n&bull;P ro fic ie n t i n  d esig n in g, i m ple m en tin g, a n d	 	\ncu sto m iz in g A d ap tiv e  C ard s f o r c h atb ot a p plic a tio n s.\n&bull;L e d  t h e i n te g ra tio n  a n d  c u sto m iz a tio n  o f M ic ro so ft	 	\nr e a l- t im e t ra n sla tio n  s e rv ic e s w it h in  c h atb ot t o	 	\nfa cil it a te  s e a m le ss m ult il in gu al c o m mun ic a tio n .\n&bull;In te g ra te d  G PT s e rv ic e  f o r m ult ip le  u se ca se s w it h  t h e	 	\nhelp  o f m ult ip le  a zu re  s e rv ic e s l ik e  a zu re  c o gn it iv e	 	\nse a rc h , a zu re  b lo b  s to ra ge  ,  a zu re  o p en  A I :	\na . T e xt m od el &ndash; G PT t u rb o 3 .5  ,\nb . E m bed din gs m od el - E m bed din gs a d a002.	\n&bull;I s u cce ssfu lly  l e d  t h e i m ple m en ta tio n  o f a  c u tt in g-e d ge	 	\np ro je ct l e ve ra gin g O pen AI t e ch n olo gie s, f o cu sin g o n	 	\ntw o k e y f u n ctio n alit ie s:	\na . F e tc h in g d ata  f r o m  d ocu m en ts .\nb . S u m mariz a tio n  o f u se r q uery .	\nR EW AR D S &amp;  R ECO GN IZ AT IO N	\nRece iv e d  	Xce le ra te  	W arrio r 	C ertif ic a te .	\nR ece iv e d  	Fe ed back  	En th usia st 	C ertif ic a te .	\nA ash i G upta\nD eve lo p er	\naash ig u pta 2300@ gm ail .c o m\n7000606303\nG w alio r\n23/1 0/2 000\nh tt p s:/ /w ww.l in ke d in .c o m /in /a ash i-\ng u pta -6 a 573619b', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(416, 102, 76, NULL, NULL, '76_102_599246470669d1c38ed432_Aashi-Resume.pdf', 'Aashi-Resume.pdf', 'OBJE C TIV ES	\nSkil le d  S o ft w are  D eve lo p er w it h  2 +ye a rs  o f\nh an d s-o n   exp erie n ce   in   ChatB ot\nD eve lo p m en t  .S eekin g a  c h alle n ge  ro le  to\na p ply  m y e xp ertis e  in  cre a tin g in nova tiv e\nso ft w are  s o lu tio n s a n d  c o lla b ora tin g w it h  a\nt a le n te d  d eve lo p m en t t e a m .	\nSK IL LS	\nP R O GRAM MIN G S K IL LS\nN od e J S  ,  M ic ro so ft  B ot F ra m ew ork  ,	 	\nJ a va S crip t\nTO OLS\nV is u al S tu d io  C od e ,  E m ula to r ,  M on go d b	 	\nC om pass	\nC ER TIF IC AT ES	\nKore .A I B ot b asic  a n d  a d va n ce d .\nO pen  A I A P I a n d  C H AT  G PT f o r d eve lo p ers	 	\nb y U dem y.	\nE D U CAT IO N	\nB.T e ch  	, E le ctr ic a l 	,  8 .0 1 	cg p a, 	\nM adha v 	In stit u te  	O f 	T e ch n olo g y 	&amp;  	Scie n ce	\n0 7/2 017 &ndash;  0 6/2 021	    	\nG w alio r, M ad hya  P ra d esh\n1 2th  	,8 3.8 % , 	N atio n a l 	C hil d re n  	H ig h 	\nSeco n d a ry  	S ch ool,B ada ga on	\n2017	 |  G w alio r, M ad hya  P ra d esh	\nP R O FE SS IO NAL E X P ER IE N CE	\nSYS T EM  	EN GIN EER  	, T AT A  	CO NSU LT A N CY 	\nS ER VIC ES (T C S )\n06/2 021 &ndash;  p re se n t	 |  D elh i,	 I n d ia	\n&bull;I  h ave  g a in ed  e xp erie n ce  i n  c h atb ot d eve lo p m en t	 	\nacro ss N LU  p la tfo rm s l ik e  M ic ro so ft  B ot F ra m ew ork	 	\ns d k f o r v a rio u s c h an nels  l ik e  m s t e a m s ,  d ir e ctlin e	 	\nusin g N od e j s  .\n&bull;P ro fic ie n t i n  b uil d in g R EST fu l A P Is  a n d  w ork in g w it h	 	\nM on go D B t o  m an age  a n d  q uery  d ata . A d ep t a t	 	\nco lla b ora tin g w it h  c ro ss -fu n ctio n al t e a m s t o  d eliv e r	 	\nh ig h -q ualit y  s o ft w are  s o lu tio n s u sin g N od e j s . I  h ave	 	\nw ork  w it h  d if fe re n t t e a m s t o  d eliv e r h ig h  q ualit y	 	\np ro je cts  a n d  c o n tr ib ute d  t o  a  p osit iv e  t e a m	 	\nen vir o n m en t b y p ro vid in g g u id an ce  a n d  s u p port t o	 	\nte a m  m em bers .\n&bull;U til iz e d  a n d  I n te g ra te d  Q nA M ake r/ L a n gu age  S tu d io	 	\ni n to  a  c u sto m  c h atb ot a p plic a tio n  t o  c re a te  a	 	\nK now le d ge  b ase  o f f r e q uen tly  a sk e d  q uestio n s,	 	\nim pro vin g r e sp on se  t im es ,  a cc u ra cy  a n d  e n ab lin g	 	\nnatu ra l l a n gu age  i n te ra ctio n s w it h  u se rs .\n&bull;In te g ra te d  t h e c h atb ot w it h  o th er s y ste m s, d ata b ase s	 	\na n d  A P Is  t o  a cce ss a n d  r e tr ie ve  r e le va n t i n fo rm atio n .\n&bull;In te g ra te d  L U IS /C LU  f o r i n te n t r e co gn it io n  a n d  e n tit y	 	\ne xtra ctio n  ,  e n han cin g t h e c h atb ot	 	\nu n d ers ta n d  a n d  u se r q uerie s.\n&bull;P ro fic ie n t i n  d esig n in g, i m ple m en tin g, a n d	 	\ncu sto m iz in g A d ap tiv e  C ard s f o r c h atb ot a p plic a tio n s.\n&bull;L e d  t h e i n te g ra tio n  a n d  c u sto m iz a tio n  o f M ic ro so ft	 	\nr e a l- t im e t ra n sla tio n  s e rv ic e s w it h in  c h atb ot t o	 	\nfa cil it a te  s e a m le ss m ult il in gu al c o m mun ic a tio n .\n&bull;In te g ra te d  G PT s e rv ic e  f o r m ult ip le  u se ca se s w it h  t h e	 	\nhelp  o f m ult ip le  a zu re  s e rv ic e s l ik e  a zu re  c o gn it iv e	 	\nse a rc h , a zu re  b lo b  s to ra ge  ,  a zu re  o p en  A I :	\na . T e xt m od el &ndash; G PT t u rb o 3 .5  ,\nb . E m bed din gs m od el - E m bed din gs a d a002.	\n&bull;I s u cce ssfu lly  l e d  t h e i m ple m en ta tio n  o f a  c u tt in g-e d ge	 	\np ro je ct l e ve ra gin g O pen AI t e ch n olo gie s, f o cu sin g o n	 	\ntw o k e y f u n ctio n alit ie s:	\na . F e tc h in g d ata  f r o m  d ocu m en ts .\nb . S u m mariz a tio n  o f u se r q uery .	\nR EW AR D S &amp;  R ECO GN IZ AT IO N	\nRece iv e d  	Xce le ra te  	W arrio r 	C ertif ic a te .	\nR ece iv e d  	Fe ed back  	En th usia st 	C ertif ic a te .	\nA ash i G upta\nD eve lo p er	\naash ig u pta 2300@ gm ail .c o m\n7000606303\nG w alio r\n23/1 0/2 000\nh tt p s:/ /w ww.l in ke d in .c o m /in /a ash i-\ng u pta -6 a 573619b', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(417, 102, 76, NULL, NULL, '76_102_1279076832669d1c38ed5d2_Abhishek_Ankush_Resume__3.pdf', 'Abhishek_Ankush_Resume_ 3.pdf', '', 2, 3, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(418, 102, 76, NULL, NULL, '76_102_1891804581669d1c38ed947_ABHISHEK_CV_(1).pdf', 'ABHISHEK_CV (1).pdf', 'Abhishek Chaturvedi\n+91-8962547434 |reach2abhishekchaturvedi@gmail.com |\nlinkedin.com/in/abhi0642/ |\nhttps://github.com/abhi0642 Technical Skills\nLanguages\n: Python, Core Java, JavaScript, SQL, HTML/CSS\nFrameworks : Django, Flask, Torch for NLP, AWS SDK\nLibraries : Langchain, Openai, HuggingFace, Sentence-transformers, FAISS\nDatabases : Mysql, Postgresql, Chromadb, pgvector, Elastic vector database\nDeveloper Tools : PyCharm, Git, Visual Studio, Postman, Jupyter-Notebook, Google Colab\nOther : AWS, Docker, Natural Language Processing, Generative AI\nExperience Senior Software Developer - Indegene\nAug 2023 &ndash; Present\nBengaluru\n&bull; Led a team to integrate a product recommendation system with customer feedback, leveraging the Langchain\nframework with databases such as ChromaDB and PGVector for optimal performance.\n&bull; Designed and enhanced a responsive chatbot using React, langchain, and OpenAI, achieving a 92 accuracy rate\nthrough iterative prompt training. This versatile chatbot handles diverse data inputs &ndash; documents, databases,\nURLs, presentations, and images &ndash; transforming customer engagement.\n&bull; Implemented a large-scale enterprise search solution using AWS Kendra, optimizing search capabilities across\n1,000+ PDFs for enhanced data retrieval and user experience.\n&bull; Tailored chatbot solutions to align with brand strategies, ensuring robust security and the highest standards of data\nprotection.\nSenior Software Engineer - Apisero Mar 2022 &ndash; July 2023\nBangalore\n&bull; Designed and deployed a serverless API on AWS Lambda, using python events for seamless event-driven\nfunctionality. Integrated with AWS gateway API to provide scalable and efficient endpoints, optimizing cloud\nresource usage.\n&bull; Successfully automated Salesforce, Guidewire, and Symbility integrations through the use of the MuleSoft API and\nachieved a 50% reduction in data updation time.\n&bull; Successfully implemented CI/CD processes using GitHub flows on the MuleSoft anypoint platform. This enabled\nstreamlined and automated code deployment workflows, enhancing development efficiency and improving pro ject\ndelivery.\n&bull; Collaborated with multiple stakeholders to gather their requirements, led the end-to-end design of the integration\narchitecture, and conducted thorough testing across various scenarios.\nSoftware Developer - ICICI Lombard GIC Ltd. Aug 2020 &ndash; Feb 2022\nMumbai\nProduct Prediction Model\n&bull; Developed and Trained Machine Learning generic model using Regression model Techniques.\n&bull; Determined optimal strategies to understand the customer behavior during product launch and facilitate the\ntargeted market campaigns.\n&bull; Worked on a targeted algorithm to acquire an increase in market share by developing a customer segmentation\nalgorithm.\nSMS Engine(Samadhaan)\n&bull; Developed and designed an engine from scratch for customer communication via applications and upgraded our\ncentralized ILESB services for hassle-free integration.\n&bull; Finalised business requirement and delivered the engine within the minimum time possible using technologies like\nDjango and PostgreSQL.\n&bull; The engine improved the overall performance ratio from 98.8% to 99.4% and also decreased the turnaround time for\nmessage delivery.\n\nEducation\nNational Institute Of Technology Karnataka\nSurathkal\nMaster of Computer Application. July,2017 &ndash; May 2020\nWelingkar Institute of Management Development and Research Mumbai\nPGDM (Finance) July,2020 &ndash; May 2022\nMahara ja Ranjit Singh Indore\nBachelor of Computer Application. July,2014 &ndash; May 2017\nCertifications 1. Certified ScrumMaster\n&reg;(ScrumAlliance) Feb,2020 &ndash; Feb,2024\nCertificate ID: 001046716\n2. Machine Learning (Coursera) https://www.coursera.org/account/accomplishments/certificate/RXZPRNTHBK9X\nAchievement and Extracurricular activities &lowast;\nSecured AIR-80 in NIMCET-2017.\n&lowast; Competed at the state level in Muay Thai martial arts, demonstrating discipline, resilience, and a commitment to\npersonal growth and physical fitness.\n&lowast; Management Team Head in IGNITE (2018) cultural fest.\n&lowast; Secured AIR-65 in BIT-2017 MCA Entrance exam.', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(419, 102, 76, NULL, NULL, '76_102_1493816248669d1c38edb57_Adhihariharan_Resume_.pdf', 'Adhihariharan Resume .pdf', 'The S park s F oundatio nD ata  S cie n ce a nd B usin ess A naly tic s I n te rn	C onducte d  a  P yth on-b ase d  d ata  a n aly sis  p ro je ct t o  p ro vid e v alu ab le  i n sig h ts  f or t arg ete d  a d vertis e m en ts  i n  t he I ndia n  P re m ie r L ea gu e\nto urn am en t. P re se n te d  f in din gs a n d r e co m men datio ns c o ncis e ly , 	e ffe ctiv ely	 c o m munic a tin g	 co m ple x	 d ata  f o r s ta k eh old er d ecis io n-m ak in g.	\nO DIN  A IJunio r A I E ngin eer	 	S pea rh ea d ed  t h e d ev elo pm en t o f 	R AG	 eva lu atio n	 e n dpoin ts  i n  	F astA PI	, l e v era gin g 	L angC hain	 t o  e n su re  r o bust m etr ic  e sta b lis h m en t f o r	\nev alu atin g t h e R AG  p ip elin e&#039;s  p erfo rm an ce. R esu lt in g i n  a  n ota b le  	2 8%  i n cre a se  i n  a nsw er c o rre ctn ess	 f o r m ult i- a gen t c h atb ots  i n te g ra te d	\nw it h  O D IN  A I&#039;s  p la tfo rm s.\nO rc h estr a te d  t h e i n te g ra tio n o f e n dpoin ts  w it h in  t h e 	F astA PI	 b ack en d t o  s e a m le ssly  a u to m ate  t a sk s a n d o ptim iz e w ork flo w  p ro cesse s a cro ss	\nR ea ctJ S , A ngula rJ S , a nd N ex t.js  	fr o nte n d f r a m ew ork s. T his  i n clu ded  d ev elo pin g a  L in ked In  a u to m atio n f ea tu re  c ap ab le  o f e x tr a ctin g	\npro sp ect d ata  b ase d  o n j o b r o le s o r e x p erie n ce, a m ong o th er f u nctio nalit ie s, a nd lev era g in g	 S erp A PI.	 W hic h  e n han ced  t h e	 H R t e a m &rsquo;s	\np ro ductiv it y  b y s tr e a m lin in g j o b p ro sp ect s e a rc h in g b y	 7 0% .	 	\nPla yed  a  p iv o ta l r o le  i n  o rc h estr a tin g t h e s e a m le ss 	m ig ra tio n	 o f O D IN  A I&#039;s  d ata b ase  f r o m  	Fir e b ase	 ( N oSQ L) t o  	S upabase	 ( P ostg re S Q L),	\nd ev is in g a n d e x ecu tin g a  s tr u ctu re d  m ig ra tio n p la n  e nco m passin g o ver 	1 00	 en dpoin ts	 a n d o ver 	1 0,0 00 d ocu m en ts	 w hile  l e v era gin g 	para lle l	\nco lle ctio n t r a n sfe r t e ch niq ues t o  e x p ed it e  m ig ra tio n s p eed  a n d m in im iz e d ow ntim e.\nP ro vid ed  e sse n tia l t e ch nic a l s u pport i n  r e so lv in g b ug f ix es a n d u se r i n quir ie s, c olla b ora tin g c lo se ly  w it h  t he s upport t ea m  to t ro uble sh oot\nis su es w it h in  t h e F astA PI b ack en d, u tiliz in g 	D ock er c o nta in ers, N ew R elic , a nd S en tr y .io	 e rro r m onit o rin g t o  p ro m ptly  a d dre ss a n d 	deb ug	\nte ch nic a l i s su es.\nC olla b ora te d  s e a m le ssly  w it h  f r o nt-e n d t e a m  m em bers t o  e n su re  c ohesiv e d ev elo pm en t a nd d eliv ery  o f r obust A I-d riv en  s olu tio ns, u tiliz in g\nA gile	 m eth odolo gie s	. S pea rh ea d ed  t h e i m ple m en ta tio n o f v ario us f e a tu re s i n clu din g 	a udio  t r a nsc rip tio n, c h at t it le  g en era tio n, a nd a n A I	\ncla ssif ic a tio n t o ol,	 a m ong o th er s ig n if ic a n t c o ntr ib utio ns.	\nO ct 2 023 -  P re se n t	A ug 2 021 -  S ep t 2 021	+91 9790850675 &middot; 	adhi15au@gmail.com	 &middot; Linkedin	 - Github	 - Website	\nA D HIH ARIH ARA N  A U	\nPR OFESSIO N AL E X PE R IE N CE	Glo sy s T ech nolo gy S olu tio ns P vt. L td .T ra in ee	C om ple te d  a  c o m pre h en siv e 	fo ur-m onth  D ata  s c ie n ce c o urse , g ain in g h ands-o n e x perie n ce 	a n d e x p ertis e  i n  v ario us a lg o rit h m s a n d c o ncep ts .	\nC olla b ora te d  w it h  m y m en to r t o  s o lv e r e a l- w orld  p ro ble m s b y e m plo yin g a dva n ced  P yth on l ib ra rie s a n d f ra m ew ork s.	\nJ une 2 019 -  S ep t 2 019	S in gapore  M anagem en t U niv ersit y , 	S in gap ore	\n0 8/2 022 -  0 8/2 023\nM S: C om putin g, D ata  S cie n ce &amp;  E ngin eerin g r e se a rc h  t ra ck	E D UCA TIO N	Sri V en k ate sw ara  C olle g e O f E ngin eerin g, 	T am il N ad u	\n04/2 018 -  0 6/2 022\nB E: 	C om pute r S cie n ce a n d E ngin eerin g	L EA D ER SH IP  E X PE R IE N CE	FO RU M  O F E C O NO M IC  S T U DIE S B Y  E N GIN EER S	V ic e P re sid en t	, F O RESE  ( A pril 2 021 -  A pril 2 022)	\nE xecu tiv e	 D ir e cto r	, F O RESE  ( A pril 2 020 -  A pril 2 021).	 	\nC onducte d  m ock  p la cem en ts  (  O N LIN E |  O FFLIN E )  f or\npre -fin al y ea r s tu den ts  i n vit in g o ver 	1 00 C om pany H Rs.	\nL ed  a  	te a m  o f o ver 8 0 m em bers	 i n  t h e c lu b.	\n IE EE S SC I 2 022	S tu den t H elp er, I E EE S SC I 2 022 ( D ec 2 022).\nH elp ed  o rg an is e  t h e I E EE S SC I c o nfe re n ce.	\nY O UTH  R ED  C RO SS	 M em ber, Y outh  R ed  C ro ss ( A pril 2 020 -  A ugu st 2 022).	P R OJE C TS	Dete ctio n o f M alic io usly  T am pere d  L ung C ancer C T sca n s u sin g A nom aly  D ete ctio n.	A  h ig h  r is k  o f m ed ic a l i m ages b ein g h ack ed  a n d t a m pere d  w it h  i s  p ro bab le . T his  c a n  p ose  a  t hre a t t o t h e p ublic  a nd t he m ed ic a l i n dustr y .\nT his  p ro je ct i d en tif ie s t h is  p ro ble m  a n d p ro vid es a  w ay t o d ete ct t a m pere d  m ed ic a l i m ag es u sin g a nom aly  d ete ctio n w it h  a n a ccu ra cy  o f\n92.1 2%\nE m plo yed  	G AN s	 t o  s im ula te  t a m pere d  m ed ic a l i m ages, e n han cin g a n om aly  d ete ctio n f or a ccu ra te  i d en tif ic a tio n. E xp ertis e  d em onstr a te d  in	\nin te g ra tin g 	G AN s	 w it h  	T en so rflo w	 a n d 	P yT orc h	 f o r r o bust t a m perin g d ete ctio n i n  m ed ic a l i m agery .	\nS m art T ra ffic  C ontr o l S yste m .	In  r e sp onse  t o  I n dia &#039;s  p erv asiv e t r a ffic  i s su es, I  s p ea rh ea d ed  a  p ro je ct f ocu se d  o n a ddre ssin g t ra ffic  c ongestio n t hro ugh  in novativ e t ech nolo gy\nso lu tio ns. L ev era gin g m y e x p ertis e  i n  	C om pute r V is io n a nd I m age P ro cessin g	, 	\nI l e d  t h e d ev elo pm en t o f a  d yn am ic  t r a ffic  l ig h t s y ste m . B y e m plo yin g a dva n ced  t ech niq ues s u ch  a s 	O pen C V a nd Y O LO v3	, w e a ch ie v ed  a	\nr e m ark ab le  	9 5%	 a ccu ra cy  i n  r e a l- tim e t r a ffic  d ete ctio n w it h in  s p ecif ic  l an es.	 	\nA ddit io nally , m y r o le  e n co m passe d  s ig n if ic a n t c o ntr ib utio ns t o  a lg o rit h m ic  r efin em en t, e nsu rin g t he s e a m le ss i n te g ra tio n o f m ach in e\nle a rn in g p rin cip le s i n to  o ur s o lu tio n, u lt im ate ly  e n han cin g t ra ffic  m an ag em en t a nd d aily  c om mutin g e xp erie n ces.	\nP yth on &bull;  J a va &bull;  H TM L a n d C SS	  S Q L &bull;  C ++	  	\n&bull;  R ea ctJ S	  &bull;  B ash  &bull;  L in ux	  	\nF astA PI &bull;  F ir e b ase  &bull;  T ab le a u	  P ow er B I &bull;	\nE xcel &bull;  S upab ase  &bull;  G it	 	\nT en so rflo w  &bull;  O pen C V &bull;  P yT orc h  s c ik it -le a rn  &bull;	\nL an gC hain  &bull;  L am aIn dex	S K IL LS', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0);
INSERT INTO `resume` (`id`, `screeningId`, `adminId`, `candidateId`, `candidateDetailsId`, `resumeName`, `resumeOriginalName`, `resumeContent`, `isSkillScreened`, `isResumeScreened`, `isCron`, `isCandidate`, `candidateShortlist`, `enableInterviewReport`, `gptLanguageId`, `isInterviewAssign`, `interviewValidity`, `interviewAssignDate`, `isPsychoAssign`, `psychoValidity`, `psychoAssignDate`, `created`, `createdBy`) VALUES
(420, 102, 76, NULL, NULL, '76_102_1000849870669d1c38edce9_AmanResume.pdf', 'AmanResume.pdf', 'SU M M AR Y	PR O FE SSIO NAL E X PE R IE N CEED U CAT IO NSK IL LSC ER T IF IC AT IO NS	li n ke d in .c o m /in / am an ja in 10 1	\nam an ja in 78 1@ gm ail.c o m	+9 1- 8 0 573 3339 3	\nA M AN  J A IN\nM ac h in e L earn in g E ngin eer	\nH ig h ly  m otiv a te d  a n d p ro fe ssio n al M ac h in e l e arn in g E ngin eer w it h  o ve r 4  y e ars  o f e xp erie n ce d  w it h  a\nd em on str a te d  h is to ry  o f w ork in g i n  t h e i n fo rm atio n  t e ch n olo gy a n d p ro d uct i n dustr y .  S kille d  i n  D ata	 	\nS cie n ce ,  C om pute r V is io n ,  P yth on ,  S ta ts ,  N LP ,  S Q L a n d G en era tiv e  A I.  S tr o n g e n gin eerin g p ro fe ssio n al	 	\nw it h  a  B ac h elo r o f T ech n olo gy-B T ech  f o cu se d  o n  C om pute r S cie n ce  &amp;  E ngin eerin g.	\nLok su n  T ech no lo g ie s,  B eng alu ru	 	\nM an ufa ctu rin g D efe cts  &amp;  Q A I n sp ectio n  w it h  S im il a rit y  b ase d\nalg orit h m .( P ate n t i n  p ro g re ss:  U S)\nD esig n ,  d eve lo p  a n d d ep lo ye d  A uto m ate  M eetin g c o n ve rs a tio n  f r o m\nsp eech  t o  t e x t u sin g S p eake r D ia riz a tio n  a n d t r a n sc rib e.\nD esig n ,  D eve lo p  a n d D ep lo ye d  C on ve rs a tio n  S u m mariz a tio n  u sin g	  	\nL Lam a-3  ( L LM ) a n d d ep lo ye d  o n  A W S.\n O bje ct D ete ctio n :  D ete ctio n  o f P PE e q u ip m en t f r o m  v id eo  a n d\npro vid in g d ata  w it h  a ll t h e A naly sis  u sin g Y olo .\nD esig n ,  d eve lo p  a n d I m ple m en t F ace  R eco g n it io n  u sin g M ob il e  F ace\nN et f o r e d ge d evic e s l ik e  m ob il e  P hon e e tc .\nD ata  s c ie n ce  m od el t o  p re d ic t c h an ce s o f w in nin g a  p arty  u sin g D ata\nA naly sis  a n d M ach in e l e arn in g.\nfin etu n ed  L arg e L an gu ag e M od els  o n  A W S c lo u d o n  c u sto m  D ata se t\nu sin g Q uan tiz a tio n  a n d f in etu n in g A lg orit h m s.\nL ead in g a  T eam  o f 1 0 p eo p le s i n clu din g M L e n gin eers  a n d F u ll s ta ck\nd eve lo p ers	\nG re enT ech  I T S  L LP,  D elh i	\nD esig n ,  d eve lo p  a n d d ep lo ye d  T ra ffic  f lo w  A naly sis :  B uil d  M ult ip le\nt r a ffic  a n aly sis  t o ols  f o r m ult ip le  s c e n ario  i n  t o ll m an ag em en t f r o m\nsc ra tc h .\nV id eo  I n cid en t D ete ctio n  S yste m :  D ete ct A ccid en ts ,  F ir e ,  s m oke ,\nW ro n g s id e v e h ic le s,  s to p  v e h ic le s e tc .\nW ork in g o n  C om pan y P ro d u ct r e la te d  t o  C om pute r v is io n  a n d\ndesig n in g a lg orit h m  a n d t r a in in g D eep  L earn in g m od els  a n d L LM s.\nC on du cte d  r e se arc h  a n d p re p are d  r e p orts  o n  v a rio u s t o p ic s r e la te d  t o\nth e c o m pan y&#039;s  o p era tio n s a n d i n du str y  t r e n ds i n  m ach in e l e arn in g\nD om ain  l ik e  O CR ,  P atte rn  R eco g n it io n .	\nI sh ir  T ech no lo g ie s,  N oid a	\nPart o f a  T eam  o f D ata  S cie n tis ts ,  w ork e d  o n  v a rio u s M L a n d\nC om pute r V is io n  A pplic a tio n s a n d W ork e d  o n  M ach in e L  e arn in g L if e\nC ycle  l ik e  D ata  G ath erin g,  D ata  p re p ara tio n ,  D ata  P re  p ro ce ssin g,\nExp lo ra to ry  D ata  A naly sis ,  M od e t r a in in g.\nM an ag e S erv e r D ata b ase s u sin g S Q L S erv e r M an ag em en t S yste m  a n d\nap ply  v a rio u s T ech niq u es l ik e  D ata  R ep lic a tio n ,  D ata  B ack u p ,  D ata\nC lu ste rin g.	\nB .  T ech  i n  C om pute r S cie n ce	                       	2 0 15 -2 0 19	\nC G PA	 :  7 .7 6 / 10	\nP yth on\nM ach in e L earn in g	 	\nD eep  L earn in g\nC om pu te r V is io n	 	\nP re d ic tiv e A naly tic s	 	\nN LP\nD ata  S cie n ce	 	\nA W S C lo u d	 	\nLarg e L an gu ag e m od el,  G en era tiv e A I\nSQ L ,N O S Q L,  P in e C on e,  c h ro m a\nLan g C hain ,  l la m a i n dex\nP yto rc h ,  T en so rflo w	  	\nJ a v aS crip t,  H TM L	 	\nPro m pt E n gin eerin g\nM ach in e l e arn in g O pera tio n s ( M LO ps)\nD ata  S cie n ce  W it h  P yth on  o n  S im pli le arn .\nB ig  D ata  H ad oop  a n d S p ark  d eve lo p er\ntr a in in g o n  S im pile arn .\n M aste rin g D ata  S tr u ctu re  a n d A lg o rit h m s\nusin g C  a n d C ++.	\nM ach in e L earn in g E n gin eerC om pu te r V is io n  E n gin eerD ata B ase  A dm in is tr a to r I n te rnT eerth an ker M ah av eer U niv ers it y	g it h ub.c o m /D ark aid o	M AY  2 0 22 -  P R ESE N TAU G  2 0 21 -  M AY  2 0 22	 	F E B  2 0 20  -  F E B  2 0 21', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(421, 102, 76, NULL, NULL, '76_102_1769407210669d1c38ede96_AM-Sai-Subhasish-Rout.pdf', 'AM-Sai-Subhasish-Rout.pdf', 'Sai S u bh asis h  R ou t	\nAI/M L E ngin eer	\nsa is u bh asis h ro u t7 77@ gm ail. c o m	 	+ 91 9 556 332 113	 	B an galo re , I n dia	 	\nw ww.li n ked in .c o m /in /s u bh asis h -s a i	 	h ttp s:/ /g it h u b.c o m /s a is u bh asis h	 	\nh ttp s:/ /m ed iu m .c o m /@ sa is u bh asis h ro u t7 77	 	\nS U M MARY\nExp erie n ce d  A I D eve lo p er 	h ig h ly  p ro fic ie n t i n  d eve lo p in g	 f u ll- s ta ck  p ro je cts  w it h  e ffic ie n t p ip eli n es. S tr o n g	\nback g ro u n d  in   m ath em atic s,  pro g ra m min g,  an d  data   m an ip u la tio n ,  tr a n sla tin g 	b u sin ess  go als	  in to	\nim pactfu l,  d ata -d riv e n  	so lu tio n s	. S pecia li z es i n  p re d ic tiv e  m od eli n g, s tr a te g ic  i m ple m en ta tio n  o f d ata -d riv e n	\na p pro ach es,  an d op tim iz in g  d ecis io n -m ak in g  p ro ce sse s.  Skille d  in  P ro m pt  E ngin eerin g  an d effe ctiv e ly\nc o m mun ic a te s  te ch n ic a l  co n ce p ts   to  n on -te ch n ic a l  sta k eh old ers.  C om mit te d  to  	co n tin uou s  le a rn in g	 a n d	\nsta yin g a b re a st o f i n du str y  t r e n ds t o  	in nova te  	w it h in  t h e d yn am ic  f ie ld  o f d ata  s c ie n ce	\nS K IL L S\nData b ase s\nM yS Q L, M on goD B\nDeep  L ea rn in g\nN LP, T ra n sfo rm ers, G en era tiv e  A I, P yT o rc h ,	 	\nTen so rflo w , P ro m pt E ngin eerin g\nD ata  A naly tic s\nP ow er B I\nM ach in e L ea rn in g\nScik it - le a rn\nV ersio n  C on tr o l\nG it h u b\nG it h u b a ctio n s C I- C D  A IO ps	\nP ro gra m min g L an gu ag e: P yth on\nFastA PI, P an das, N um py, S ele n iu m , L an gch ain ,	 	\nR eq u ests , B eu tif u ls o u p4, F la sk\nD ata  P ro ce ssin g\nPyS park , K afk a, A ir flo w , A pach e,\nC lo u d\nAW S S 3, A W S E C 2, A W S S Q S, A W S C lo u dw atc h\nD ata  M on it o rin g a n d G ove rn an ce\nD ata  d rif t\nC on ta in eriz a tio n  a n d O rc h estr a tio n\nD ock er	\nP R O FE SSIO N AL E X PE R IE N CE\nAI 	E ngin eer 	- S D E 	1	\nEnga gesp h ere  	T ech n olo g y 	P vt 	L td	\n&bull;D eve lo p  a n d m ain ta in  	A I s o lu tio n s	 t o  e n han ce  b u sin ess p ro ce sse s, 	a u to m ate	 	\nta sk s	, a n d d riv e  g ro w th .	\n05/2 0 24 &ndash;  p re se n t\nB en galu ru ,	 I n dia	\n&bull;D esig n  	m od el a rc h it e ctu re s	 f o r v a rio u s a p pli c a tio n s a n d s e le ct t h e a p pro p ria te	 	\nte ch n olo g y s ta ck s.\n&bull;D eve lo p  a n d 	op tim iz e  p ro m pts	 t o  e x tr a ct t h e r ig h t i n fo rm atio n  f r o m  l a n gu ag e	 	\nm od els .\n&bull;D esig n  a n d i m ple m en t 	A PIs  	fo r 	e ffic ie n t d ata  r e tr ie va l	, p ro ce ssin g, a n d s to ra g e.	\n&bull;C olla b ora te  w it h  f r o n t- e n d d eve lo p ers  t o  	in te g ra te  b ack -e n d	 s e rv ic e s w it h  f r o n t-	\ne n d c o m pon en ts .	\nA sso cia te  	D ata  	S cie n tis t	\niN eu ro n  	In te lli g en ce  	P vt.  	L td .	\n&bull;Im ple m en te d  A I- d riv e n  I n nova tio n s f o r E du ca tio n al P la tfo rm  E nhan ce m en t.	\n1 0 /2 0 23 &ndash;  0 3/2 0 24\nB an galo re ,	 I n dia	\n&bull;A ch ie ve d  a  s ig n if ic a n t 	4 5%  i m pro ve m en t	 i n  a d m in is tr a tiv e  e ffic ie n cy  t h ro u gh  q u iz	 	\na n d a ssig n m en t 	a u to m atio n  	in  t h e L ea rn in g M an ag em en t S yste m  ( L M S).	\n&bull;S tr e a m li n ed  t h e o ve ra ll u se r e x p erie n ce  w it h in  t h e L M S,r e su lt in g i n  a  	6 0 %	 	\nd ecre a se  i n  o ve ra ll c li c k s	.	\n&bull;E nhan ce d  c u sto m er s a tis fa ctio n  b y r e d u cin g r e sp on se  t im e t o  8 0 %  	th ro u gh  t h e	 	\nd eve lo p m en t o f a n  a u to m ate d  e m ail r e p ly  s y ste m .\n&bull;Engin eere d  a n  e ffic ie n t A I c h at s y ste m , 	o p tim iz in g t e a m  s iz e  b y 3 0 %	, a n d	 	\nre d u cin g c u sto m er q u ery  r e so lu tio n  t im e.\n&bull;L ed  t o  i m pro ve d  e ffic ie n cy  a n d r e so u rc e  u tili z a tio n	, s tr e a m li n in g o p era tio n s	 	\nacro ss d if fe re n t a sp ects  o f t h e e d u ca tio n al p la tfo rm .\n\nData  	S cie n ce  	T ech  	C on su lt a n t	\niN eu ro n  	In te lli g en ce  	P vt.  	L td .	\n&bull;D eve lo p ed  	w eb  c ra w le rs	, e x tr a ctin g d ata  f r o m  d iv e rs e  w eb sit e s.	\n0 8/2 0 23 &ndash;  1 0 /2 0 23\nB an galo re ,	 I n dia	\n&bull;E sta b li s h ed  a  	p ip eli n e f o r d ata  c le a n in g	 a n d s to ra g e i n  a  r e la tio n al d ata b ase .	\n&bull;S ch ed u le d  t h e r e fr e sh in g p ro ce ss e ve ry  t h re e d ays u sin g a  	cro n  j o b	 t o  m ain ta in	 	\nu pto -d ate  i n fo rm atio n .	\nA sso cia te  	Q A 	Engin eer	\nIn ov a are  	C lo u ds 	S oft w are  	S olu tio n s 	P vt.  	L td .	\n&bull;D eve lo p ed  a n d m ain ta in ed  	au to m atio n  t e st s c rip ts	 u sin g P yth on  f o r r e g re ssio n	 	\nte stin g.	\n12 /2 0 21 &ndash;  0 8/2 0 23	\nB hu ban esw ar,	 I n dia	\n&bull;P artic ip ate d  i n  d aily  	sc ru m  m eetin gs	, p ro vid in g s ta tu s u pd ate s o n  t e stin g	 	\npro g re ss.\n&bull;P erfo rm ed  r e g re ssio n  t e stin g a n d f u n ctio n al t e stin g o n  n ew  f e a tu re s a n d	 	\nen han ce m en ts .	\nG ra d u ate  	E ngin eer 	T ra in ee	\nS hah i 	E xp orts  	P vt.  	L td .	\n&bull;W ork ed  a s t r a in ee i n  I n du str ia l E ngin eerin g D ep artm en t.	\n1 0 /2 0 19  &ndash;  0 5/2 0 20	\nB hu ban esw ar,	 I n dia	\nP R O JE C TS\nAI-D riv e n  	C usto m er 	S u pport 	C hat 	S yste m	\nIn nov a tiv e 	C hat 	S upport 	S yste m :	\n&bull;Acco m pli s h ed  a  s ig n if ic a n t 	4 0 %  r e d u ctio n	 i n  r e sp on se  t im es, c o n tr ib u tin g t o	 	\no ve ra ll e ffic ie n cy  i n  r e so lv in g s tu den ts &#039;  q u erie s.	\n11/2 0 23 &ndash;  0 2/2 0 24	\n&bull;A ppli e d  d ata -d riv e n  i n sig h ts  t o  p ers o n ali z e i n te ra ctio n s b ase d  o n  	in div id u al	 	\np re fe re n ce s	.	\nA uto m ate d -E du ca tio n al 	A sse ssm en t 	S yste m	\n&bull;L eve ra g ed  L L M  m od el f o r 	a u to  	assig n m en t, q u iz  g en era tio n , a n d s tr e a m li n in g	 	\ngra d in g p ro ce sse s.	\n10 /2 0 23 &ndash;  1 1/2 0 23	\nP E R SO N AL P R O JE C TS\nThyro id  	D is e a se  	D ete ctio n	\n&bull;A ddre ssin g t h e p re va le n ce  o f t h yro id  d is e a se  a s a  c o m mon  e n docrin e d is o rd er, I	 	\nd eve lo p ed  a n  M L m od el t o  a ssis t h osp it a ls  i n  p re d ic tin g t h yro id  c o n dit io n s b ase d	 	\no n  p atie n t d ata .	\n0 1/2 0 23 &ndash;  0 3/2 0 23	\n&bull;T ech  S ta ck : P yth on , M L a lg orit h m s, D ock er, A W S, A ir flo w , M on goD B, F la sk , F ast	 	\nA PI, A W S, G it h u b-a ctio n s, M LO ps\n&bull;A tta in ed  a cc u ra cy  o f 9 9.8 5%	 u sin g X gB oost.	\nE D UCATIO N\nBach elo rs 	o f 	T ech n olo gy	\nIT E R , 	S O A 	U niv ersit y	\nM ech an ic a l E ngin eerin g	\n08/2 0 15  &ndash;  0 5/2 0 19	\nB hu ban esw ar,	 I n dia	\nC ER TIF IC ATE S	\nFu ll S ta ck  D ata  S cie n ce\nW hat i s  G en era tiv e  A I ?	\nT he D ata  S cie n ce  o f	 	\nH ea lt h ca re , M ed ic in e, a n d	 	\nP ubli c  H ea lt h\nP yth on  f o r D ata  S cie n ce	\nG en era tiv e  A I: W ork in g w it h	 	\nL arg e L an gu ag e M od els\nS ta tis tic s 1 0 1	\nA W AR D S\nBest 	v o lu n te er 	o f 	th e 	ye a r	\nA w ard ed  b y t h e N GO  &quot; T he H elp in g E ye&quot; i n  2 0 20 .', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(422, 102, 76, NULL, NULL, '76_102_1687535226669d1c38ee03c_Arifiya_Khan-Resume_(1).pdf', 'Arifiya Khan-Resume (1).pdf', 'Arifiya Khan\nEmail: arifiyakhan@gmail.com Linkedin : linkedin.com/in/arifiya-khan\nMobile: +91-8172993811 Location: Bangalore, Karnataka\nSkills Summary &bull;\nFrameworks : TensorFlow, PyTorch, Keras, Large Language Model (LLM)\n&bull; Libraries : Transformers, NumPy, Pandas, Scikit-learn, spaCy, NLTK\n&bull; NLP Tools : Topic Modeling, Named Entity Recognition (NER),Sentiment Analysis, Text Summarization, Natural\nLanguage Processing (NLP), Prompt Engineering, Retrieval-Augmented Generation (RAG)\n&bull; Platforms : AWS(Amazon Web Services), macOS, Windows\n&bull; Languages : Python, C++, SQL\n&bull; Soft Skills : Leadership, Writing, Public Speaking, Time Management\nExperience &bull;\nTata Consultancy Services\nBangalore,karnataka\nMachine Learning Developer (Ful l-time) Oct 2022 - Present\n◦Performed large-scale text analytics on 2 Mn+ agent-customer chat data for Apple(Client) at TCS, leveraging\nadvanced NLP techniques &ndash; Topic Modeling, Text Classification,Text Summarisation(BART),spaCy,\nNER, LLMs, and sentiment analysis .\n◦ Enabled data-driven service enhancement by identifying pain points &ndash; problematic product names through NER,\ngeographic issue hotspots through spatial mapping, and areas for improvement through insights from exhaustive\ndata cleaning, preprocessing, and text summarization.\n&bull; Eloquent Advisory Pvt. Ltd.\nRemote\nTest Automation Architect (Ful l-time) Sept 2021 - Sept 2022\n◦Spearheaded end-to-end manual and automated testing processes for Thinkly App, utilizing Jira,\nBrowserStack, and AccelQ. Transitioned from intern to full-time position, solely managing testing, coordinating\nwith developers, and driving 180% quality improvements . Recognized for adaptability, dedication, and\nexceptional testing oversight, consistently delivering high-quality results and earning performance- based\nincrements and commendations.\nProjects &bull;\nCab Fare Prediction - Numpy, Pandas, Scikit-learn, Linear Regression, Random Forest : Developed a Cab Fare\nPrediction system employing linear regression and random forest algorithms, achieving 90% accuracy in predicting fare\namounts for city cab rides.\n&bull; Face recognition model - Tensorflow, Keras, MobileNet, Convolutional Neural Networks (CNN), OpenCV :\nEngineered a Face Recognition model using MobileNet and CNN with TensorFlow and Keras, enhancing effectiveness and\nachieving an accuracy of 85% in identifying specific individuals, including family members.\nCertifications &amp; Trainings &bull;\nData Analyst, edWisor (March 2020-Aug 2020) : Mastered scientific algorithms to extract insights from unstructured\ndata using R and Python, enhancing analytical skills for data-driven decision-making.\n&bull; Hybrid Multi Cloud, LinuxWorld Informatics Pvt Ltd : Proficient in AWS, EKS and Terraform for hybrid multi-cloud\nenvironments and cloud infrastructure automation.\n&bull; Google Cloud Certified Associate Cloud Engineer : Certified Associate Cloud Engineer by GCP.Utilized Google Cloud\nservices such as Compute Engine, Kubernetes Engine, Cloud Storage, BigQuery and Cloud SQL\nEducation &bull;\nI.E.T.,Dr. Ram Manohar Lohia Avadh University\nFaizabad, India\nBachelor of Technology - Computer Science and Engineering(CSE); GPA: 82%, Rank:1July 2018 - June 2022\nCourses: Operating Systems, Data Structures, Analysis Of Algorithms, Machine Learning, Networking, Databases\n&bull; Nirmala Convent Sr. Sec. School\nRenukoot, India\nIntermediate &mdash; Science (PCM) July 2015 - June 2017\nCourses: Physics, Chemistry, Mathematics, Computer Science\nHonors and Awards &bull;\nBest Team Award - Awarded by Tata Consultancy Services Limited (TCS),2023\n&bull; Outstanding performer Prize,Web Development - Awarded by softpro India Computer Technologies (P) Ltd,2018', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(423, 102, 76, NULL, NULL, '76_102_1319945693669d1c38ee20b_chandra-GenairesumeV3.pdf', 'chandra-GenairesumeV3.pdf', 'CHANDRA MOULI	 	\nData Scientist / AI &amp; ML Engineer	 / GenAI 	Developer	 	\n \n \nDynamic and results	-driven Data Scientist with 	4+ years	 of extensive experience leveraging expertise in	 Generative AI,	 	\nArtificial	 Intelligence and Machine Learning. Targeting 	opportunities in Bangalore, Hyderabad, Remote, and Gulf Countries.	 	 	\n+91	-8309047501	 	  	\ntchandramouli8978@gmail.com	 	  	\nlinkedin.com/in/	chandra	-mouli07	/ 	\n 	\nCORE COMPETENCIES	 	  	\nGenerative AI &amp; LLMs	 	\n \n                           	Prompt Engineering	 	\n 	\n                     	AI/ML	 	\n 	\nDeep Learning	 	\n 	\nNatural Language Processing	 	\n 	\n  Computer Vision	 	\n 	\nPredictive Analytics      	 	\n 	\nMathematical/Statistical Concepts	 	\n 	\n          	 MLOps / LLMOps	 	\n 	\nData Analysis &amp; 	Visualization	 	\n \n \n \n 	\nSOFT SKILLS	 	  	\nAnalytical	 	  	\nInnovative &amp; Critical	 	 	Thinking	 	 	\nCommunication Time \nManagement Leadership \n&amp; Team Collab. \nPresentation	 	\n  	\nPERSONAL DETAILS	 	  \n&bull; 	Date of Birth:	 23	rd May	 1998	 	 &bull; 	Address:	 NR layout, Garvebhavipalya, 	\nBangalore 	-560068	 	 &bull; 	Languages Known:	 English	, Telugu, 	\nTamil &amp; Hindi	 	 	\n 	\nPROFILE SUMMARY	 	  &bull; 	Possess experience in 	Artificial Intelligence	 and 	Machine Learning	 across 	\nFinancial Services	 and BFSI industry	. 	 &bull; 	Spearheading  a  team at 	CAPCO Technologies	,  focusing  on developing cutting	-	\nedge  AI  solutions  such  as 	LLMs,  Generative  AI	 Chatbot  and  advanced  text 	\nclassification models, driving innovation and operational efficiency.	 	\n 	\n&bull; 	Proficient in	 Generative 	AI, LLMs,	 Prompt engineering	 and more.	 	 &bull; 	Proficient in 	Python	, API, Data Manipulation, Automation, 	SQL, NoSQL	, 	\nData Analysis, Data Wrangling	, and more.	 	 &bull; 	Acknowledged  for 	creating  innovative  AI  solutions	 that  revolutionized 	\nbanking  automation  and  provided  tailored  recommendations,  enhancing \noperational efficien	cy and customer satisfaction.	 	 &bull; 	Proficient  in  conducting 	Statistical  Analysis,	 developing 	Predictive  Models	, 	\nimplementing 	Time  Series  Forecasting	 techniques,  and  conducting 	A/B 	\nTesting	 to enhance decision	-making processes and drive business growth.	 	 \n&bull; 	Proven 	track record in 	strategic thinking, team leadership	, and 	data	-	\ndriven decision	-making	. 	 	\nEDUCATION	 	  	\nB.Tech. in 	Electronic and Communication Engineering	 from 	REVA 	\nUNIVERSITY	 | 20	19	 | 6.9	 GPA	 	 	HSC	 from Sri Chaitanya educational institutions | 2015 | 92.9%	 	\n 	\n CERTIFICATIONS	 	  \n&bull; 	Generative AI Fundamentals |Databricks | 2024	 	 &bull; 	Data Analysis and visualization Bootcamp | Udemy | 20	22	 	 &bull; 	Data science Foundation |IABAC| 2022	 	 &bull; 	Data Science Bootcamp | Data mites | 2022	 	\n 	\n \nIT SKILLS	 	  \n&bull; 	Development Tools / IDEs:	 PyCharm, Jupyter Notebook, Visual Studio Code	 	 &bull; 	Web Scraping:	 Beautiful soup	, Scrapy	 	 &bull; 	Web Framework:	 FastAPI	 	 &bull; 	Databases:	 MySQL, Microsoft	 SQL Server, Neo4j	 	 &bull; 	Data Analysis &amp; Visualization	: Pandas, Numpy, sciPy, Matplotlib, Seaborn, 	\nPlotly, PowerBI	 	 &bull; 	Generative  AI	: LangChain,  OpenAI  GPT  3,  GPT  4,  Llama2,  Mistral  LLM,  BERT, 	\nHugging  Face Transformers and  Embedding  Models, Tensorflow  Hub,  Facebook  AI \nSemantic Search, Pinecone VectorDB, Chroma DB, RAG	 &amp; Langchain agents	 	\n 	\n&bull; 	Prompt  Engineering	: Zero	-shot  prompting,  One	-shot  prompting,  Few  shot 	\nlearning, 	Step back prompting &amp; Prompt chaining.	 	 &bull; 	AI / ML:	 TensorFlow, Keras, PyTorch, Scikit	-learn, XGBoost, AWS 	\nSageMaker, Azure ML Studio	 	 &bull; 	Deep Learning:	 CUDA, Caffe	 	 &bull; 	NLP:	 BERT, GPT, NLTK, SpaCy	 	 &bull; 	Computer Vision:	 YOLO, OpenCV, Tesseract 	OCR,	 Scikit	-Image, GPT4 	\nVision	 	  &bull; 	Version Control &amp; DevOps / MLOps / LLMOps:	 Git, Bitbucket, Jira, 	\nDocker, Kubernetes, MLflow, Langsmith, CI/CD\n\nWORK EXPERIENCE	 	  \nData Science 	Consultant |	 CAPCO Technologies, Bengaluru | 	Jan	&rsquo;22-Present 	\nKey Result Areas:	 	 &bull; 	Leading a dynamic team consisting of a Data Analyst and a Junior Machine Learning Engineer, actively guiding project directio	n 	\nand ensuring seamless collaboration.	 	 &bull; 	Spearheading the development of cutting	-edge AI solutions, including a state	-of-the	-art Large Language Models, Generative AI 	\nChatbot, resulting in significant enhancements in client engagement and operational efficiency.	 	 &bull; 	Implementing AI	-driven models, 	particularly in text classification	, thereby automating intricate workflow and delivering 	\nsubstantial cost and time savings for clients.	 	\n  &bull; 	Pushing the boundaries in the application of AI within the banking sector, particularly in automating customer servic	e and 	\noffering personalized financial recommendations.	 	\n 	\n&bull; 	Implementing GenAI	-driven solutions specifically like Conversational 	Private kb&rsquo;s, Content 	Generation 	Automation, Content 	\ncomparison delivering automated customisa	ble	 solutions for clients.	 	\n 	\n&bull; 	Spearhead	ing the development of GenAI Conversation chatbots on Private Kb&rsquo;s on pr	ivate 	data	 sources	 leveraging RAG 	\n(Retrieval Augmented Generation).	 	\n 	\n&bull; 	Developed a Language summarization Agent by leveraging Lang chain map reduce chains and advance prompt engineering \nwhich can summarize complex docs like regulatory notices etc. &amp; extract insights, improving efficiency and accuracy of \nanalysis.	 	\n 	\n&bull; 	Implementing 	various range 	of 	advanced 	prompt engineering techniques like 	Zero	-shot, 	One	-shot 	 &amp; Few Shot 	learning to 	\nAutomate	 tailored C	ontent generation by reducing hallucination of the LLMs	 delivering optimised cost and time savings for 	\nclients.	 	\n 	\n&bull; 	Implemented advanced LLMs, including local and API	-based models, to solve complex problems and provide tailored solutions, 	\nsignificantly boosting client engagement.	 	\n 	\n&bull; 	Facilitating knowledge transfer and capacity building within the team by conducting training sessions on the latest AI \ntechnologies and methodologies.	 	\n 	\n 	\n \nData Science 	Trainee | Change	 Pond technologies	  , Chennai 	|Jan &lsquo;	20	-Jan&rsquo;2	2 	\nKey Result Areas:	 	\n  &bull; 	Contributed in development of machine learning model 	to enhance the quality and efficiency of business processes involving 	\nimage processing, OCR, text mining, and information extraction	. 	 &bull; 	Cleaned and pre	-processed the unstructured image data 	to detect tables and extract relevant information using advanced 	\nimage processing techniques.	 	\n 	\n&bull; 	Leveraged PyTesseract for 	OCR 	to accurately extract data from images, facilitating seamless integration with	 business 	\nworkflows.	 	\n 	\n&bull; 	Involved in streamlining the business processes by automating repetitive tasks 	through the application of machine learning 	\nand RPA, resulting in significant time and cost savings.\n\nANNEXURE	 	\n  \nProjects Undertaken 	at CAPCO Technologies	 	 Project 1:	 AI-Powered Custom Knowledge Base Chatbot for Enhanced Data Retrieval	 	 Initiated  the  development  of  a  cutting	- edge  AI	-powered  Chatbot  incorporating  Retrieval  Augmented  Generation,  aimed  at  transforming 	\ninformation retriev	al across varied data formats such as scanned PDFs, text documents, and databases. This endeavor entailed leveraging 	\nLangChain and Facebook AI Semantic Search for comprehensive comprehension and efficient querying, alongside advanced Large La	nguage 	\nModels 	(LLMs)  like  GPT	-3.5/4,  Mistral  LLM,  and  LLAMA2  for  contextually  relevant  responses.  Proficiently  integrated  Hugging  Face 	\nembedding  models,  employing  BERT  to  augment  language  modeling  capabilities.  The  application  of  Generative  AI  and  advanced  NLP	 	\ntechnique	s  facilitated  natural  language  queries	.Python  acted  as  the  primary  programming  language,  supported  by  FAISS  for  streamlined 	\nsimilarity search and Transformers for data manipulation, ensuring a seamless and precise knowledge retrieval experience.	 	  \nProject	 2: AI-Powered Language Summarization Agent	 	 Developed an advanced AI	-powered Language Summarization Agent, utilizing LangChain&#039;s map	-reduce techniques for summarizing 	\nsmall documents and KMeans clustering for large document summaries. This project focused	 on transforming the summarization of 	\ncomplex documents, such as regulatory notices, to extract critical insights and improve analysis efficiency. Applied advanced	 prompt 	\nengineering  techniques  to  ensure  high	-quality,  contextually  relevant  summaries.  Lever	aged  the  capabilities  of  advanced  large 	\nlanguage  models  (LLMs),  significantly  enhancing  the  accuracy  and  speed  of  data  processing.  Utilized  Python  as  the  primary \nprogramming language, ensuring seamless implementation	  and integration of the summarization a	gent into existing workflows.	 	  \nProject 3:	 AI-Powered 	Automated SAR Narrative Generation	 	\nDevelop	ed 	an  innovative  AI	-powered  solution  for  automating  Suspicious  Activity  Report  (SAR)  narrative  generation.  Leveraging 	\nadvanced  prompt  engineering  techniques, 	the  application  streamlines  the  otherwise  manual  and  tedious  process  of  writing  SAR 	\nreports based on input case details provided.	 	\nUtilizing 	Lang  Chain	 and  state	-of-the	-art  Large  Language  Models  (LLMs),  the  system  efficiently  generates  SAR  narratives  with 	\nunparalleled  accuracy  and  efficiency.  Advanced  prompting  techniques  were  instrumental  in  guiding  the  AI  model  to  produce \ncontextually relevant and lega	lly compliant reports.	 	\nBy automating SAR report writing, the application significantly reduces time and costs for clients, eliminating the need for 	manual 	-	\nintensive processes. This transformative solution not only enhances operational efficiency but also 	ensures consistency and accuracy 	\nin compliance documentation.	 	  \nProject 4:	 Automated Data Collection and Intelligent Text Classification for Enhanced Decision Support	 	 Championed the initiation of an advanced Automated Data Collection and Intelligent Clas	sification for Enhanced Decision Support 	\nsystem. Employed state	-of-the	-art Natural Language Processing (NLP) techniques and Machine Learning algorithms to automate the 	\nanalysis  and  categorization  of  regulatory  news  articles  from  over  1600  sources.  Achieved	 an  impressive  accuracy  rate  of  83% 	\nthrough  the  training  of a BERT model  on  extensive  datasets.  Engineered  a  FastAPI  application  to  seamlessly  incorporate  Machin	e 	\nLearning models, enabling smooth interaction with data acquired by RPA bots and APIs. Monthly	 model retraining initiatives were 	\nimplemented to uphold accuracy levels and ensure alignment with current trends and developments.	 	\n  Project 5	: A	I-Powered Credit 	Memo 	Narrative Generation	 	 Initiated the development of an AI	-powered solution tailored for 	the automated generation of Credit Memos, a pivotal component in 	\nthe credit assessment process. By harnessing LangChain, advanced Large Language Models (LLMs), and innovative prompt chaining	 	\ntechniques, the application revolutionizes the analysis of entity	 credit requests based on 10K reports and other pertinent data.	 	\nTraditionally a 	manual	-intensive task, the generation of Credit Memos typically involves multiple teams within financial institutions. 	\nHowever, 	this 	solution streamlines this process by automa	ting data analysis and narrative generation, providing loan officers with 	\ncomprehensive insights to facilitate informed decision	-making.	 	\nThe utilization of prompt chaining techniques orchestrates the integration of task	-specific prompts, enabling the model	 to synthesize 	\ninformation  from  diverse  sources  into  cohesive  narrative  formats.  By  amalgamating  insights gleaned  from  entity  10K  reports  an	d 	\ncredit  requests,  the  generated  Credit  Memos  offer  a  holistic  view  of  creditworthiness,  empowering  loan  officers  to	 make  well	-	\ninformed decisions efficiently.	 	\nThrough  the  amalgamation  of  LLMS,  LangChain,  and  prompt  chaining  techniques,  this  innovative  solution  optimizes  the  credit \nassessment process, enhancing operational efficiency and decision	-making accuracy within f	inancial institutions.	 	  \nProject 6:	 AI 	-Powered Content Comparison Agent	 	\nDeveloped an AI	-powered agent for seamless comparison of content across images, text, and hybrid formats. Integrated LangChain, 	\nGPT	-4  Vision,  and  GPT	-3.5  with  advanced  prompt 	techniques  for  precise  analysis.  Enhances  efficiency  and  accuracy  in  content 	\ncomparisons for informed decision	-making.', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(424, 102, 76, NULL, NULL, '76_102_1456298731669d1c38ee54c_Chinmay_Deshmukh_resume.pdf', 'Chinmay_Deshmukh_resume.pdf', 'Domain Specific Chatbot	\nLe ve ra ge d  t h e R asa  f r a m ew ork  t o  a ch ie ve  a  9 9%  a ccu ra cy  r a te  i n  c la ssif y in g 2 6  d is tin ct i n te n ts .\nD esig n ed  t h e c h atb ot t o  e n ab le  d ir e ct i n te ra ctio n  b etw een  u se rs  a n d  t h e d ata b ase , f a cil it a tin g s e am le ss\nre tr ie val o r u p d atin g o f v alid ate d  u se r d ata .	\nDeepstream Auto Annotation Tool	\nR ed uce d  a b out 7 0 %  o f t im e i n  M ach in e L e arn in g c y cle  b y a u to m atic a lly  a n nota tin g i m age s.\nC ours e ra  S p ecia liz a tio n s ( D ata  S cie n ce / M L /  D L /  A I)	 	\nD ata b ric ks C ertif ie d  A sso cia te  D eve lo p er f o r A pach e S p ark  3 .0\nG oogle  C lo ud  Q w ik la b s\nD ata ca m p C ertif ic a tio n s ( D ata\nS cie n ce  /  D evo p s /  L LM s)	C hin m ay  D esh m ukh\nData  S cie n tis t	  |  D ata  E n gin eer |  M en to r |  D eve lo p er	\nW ork  E xp erie n ce\nData Scientist, 	LTIMindtree	                                                                                                  	Aug 2022 - Present	\nDep lo ye d  a  L arg e  L an gu age  M od el ( L LM ) \nc u ttin g G PU  c o sts . W ork e d  o n  M is tr a l, Q w en , L LaM A, e tc .\nD esig n ed  a  p ip elin e t o  d ete ct a re as o f i n te re st i n  i m age s a n d  e xtr a ct t e xt f o r a n aly sis .\nM ech an iz e d  a n  u n m an ned  s c rip t t h at c re ate s a  c o m pute  i n  A zu re  w hen  u se r r e q uests .\nIm pro ve d  p re -e xis tin g c o d e, r e su lt in g i n  7 5 %  r e d uctio n  o f e xe cu tio n  t im e.\nLe ve ra ge d  A zu re  M ach in e L e arn in g ( A zu re  M L) f o r b uil d in g, t r a in in g, a n d  d ep lo yin g m ach in e l e arn in g m od els .\nE m plo ye d  A zu re  C osm osD B w it h  P ostg re S Q L t o  s to re  e m bed din gs a s a  v e cto r d ata b ase , o p tim iz in g d ata\nr e tr ie val a n d  s to ra ge  f o r m ach in e l e arn in g a p plic a tio n s.\nW ork e d  w it h  L an gC hain  t o  c re ate  s o p his tic a te d  p ro m pts  a n d  a ge n tic  f lo w s, e n ab lin g p re cis e  a n d  e ffic ie n t\noutp uts  f r o m  g iv e n  i n p uts .\nM an age d  c u sto m  e n vir o n m en ts  w it h  D ocke r f o r c o n sis te n t a n d  e ffic ie n t d ep lo ym en t.\nD eve lo p ed  b acke n d  A PIs  a n d  w ork flo w s u sin g D ja n go  t o  i n te ra ct w it h  A zu re  M L a n d  c re ate  e n d poin ts .	\nMentor,	  Coursera	                                                                                                                  	Aug 2021 - May 2022	\nM en to r f o r d eep le arn in g.a i c o urs e s a v ail a b le  o n  C ours e ra .	\n+9 1 8 36 956 686 7bhagy e sh .d esh m ukh 29 @ gm ail .c o mIn d ir a n aga r, B an ga lo re ,	 I n d ia , 5 6 0 008.	Data Scientist, Ease my AI	                                                                                                  	Sep 2021 - Dec 2021	\nA uto m ate d  r e cu rrin g t a sk s, r e d uce d  2 0 %  t im e r e q uir e d  f o r d eve lo p in g c o m pute r v is io n  s o lu tio n s.\nD eve lo p ed  a  c o d e t o  e n ab le  r a p id  l iv e  s tr e am in g f r o m  m ult ip le  c a m era s w hil e  m in im iz in g t h e u til iz a tio n  o f\nre so urc e s.	 	\nB uil t  a  p yth on  p acka ge  t h at a u to m ate s c o m pute r v is io n  t a sk s.	\nE d uca tio n\nBachelor&rsquo;s in Computer Engineering, University of Mumbai	                               	Jun 2018 - Aug 2022	\nCG PA : 	9 .1 5 /1 0 .0 0	\nhttp s:/ /c h in m ay -d .n etlif y .a p p\nP ro je cts\nITSM Webapp	\nW ork e d  o n  b acke n d , f r o n te n d  a n d  c o n ta in eriz a tio n  p art o f I T S M  w eb ap p b ase d  o n  I T IL  v 3 .	\nPythonC++JavascriptHTMLCSSMySQLPostgreSQLGCPAzureKubernetesDockerLinuxTensorflowNLPMachine LearningRasaDeeplearningPytorchDjangoReactMLOpsGen AIDSARAGTerraformApache Spark\nA cco m plis h m en ts	\nIn d ustr y  A dvis o r	 a t 	S -V YA SA  U niv e rs it y	 f o r U G , P G  a n d  f a cu lt y  o f D ata  S cie n ce .	\nR an ke d  i n  t h e 	to p  1 0  o ut o f 4 0 0 t e am s 	in  a  g lo b al h acka th on  ( L T IM in d tr e e S o lv ath on  2 0 23 ).	 	\nG uid ed  1 0 0&#039;s  o f s tu d en ts	 i n to  M L, D L. I n vit e d  b y D Y P atil  U niv e rs it y  a s a  w ork sh op  s p eake r.	\nC ertif ic a tio n s\nCil c k t h e i c o n s t o\nv ie w  m y p ro fil e s', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(425, 102, 76, NULL, NULL, '76_102_1271150398669d1c38ee6f4_Hiten-Jain-Job-Resume.pdf', 'Hiten-Jain-Job-Resume.pdf', 'Hiten Jain\n+91-7424855035 &bull; hitenjain0509@gmail.com &bull; linkedin.com/in/hiten-jain-b44846210\nGenerative AI Engineer\nEnthusiastic AI graduate with a strong foundation in Natural Language Processing (NLP), Generative AI, and lar\ngelanguage models. Eager to leverage expertise from Deep Learning, NLP\n, and Machine Learning certifications to contribute tocutting-edge developments in the field. Passionate about the transformative potential of AI and NLP\n.SKILLS\nWORK EXPERIENCE\nNimbusnext &bull; Princeton, New Jersey\n, United States &middot; Remote &bull; 1\n1/2023 - Pr esent Junior Softwar\ne AssociateRenix Informatics &bull; Remote &bull; 09/2023 - 1\n1/2023 AI Resear\nch Intern EDUCA\nTION Bachelor of T\nechnology - BT ech in Electrical, Electr\nonics and Communications EngineeringSwami Keshvanand Institute of T\nechnology, Jaipur &bull; 01/2019\nPROJECTS\nChat W\nith multiple PDF&#039;s &bull; 07/2023 - 08/2023\nThis project built a conversational interface for searching through multiple PDFs. It utilized Langchain for the framework,\nHuggingface for text embeddings, and Faiss-CPU for ef\nficient text storage and retrieval. To generate context-aware responsesto user queries, it implemented lar\nge language models like google/flan-t5-xxl, GPT4All, and Lamini. Finally , a memoryfeature was incorporated to enable natural and coherent interactions across user queries.\nBoolean Question Answering System &bull; 03/2022 - 04/2022\nAI model for answering yes-or\n-no questions. The model is trained using an encoder -decoder architecture with LSTM layers.It learns from a collection of questions and their corresponding &quot;yes&quot; or &quot;no&quot; answers. The text is first prepared and turned\ninto numerical representations, then these are used to train the model to predict answers for future yes-no questions. Azure Openai\n&bull;\nDeep Learning\n&bull;\nDjango\n&bull; Langchain\n&bull;\nLar\nge Language Models (LLM) &bull;\nLlamaindex\n&bull; Machine Learning\n&bull;\nNatural Language Processing (NLP)\n&bull;\nPython\n&bull;\nImplemented retrieval-based techniques like RAG, resulting in a 25% increase in information retrieval ef\nficiency andultimately enhancing productivity for the team.&bull;\nDesigned and implemented generative AI applications leveraging cloud platforms like Azure and web frameworks like\nDjango.&bull;\nCustomized LLMs to meet project-specific requirements, enhancing the overall quality and functionality of software\nproducts.&bull;\nPrepared POCs, finetuned GPT\n, and used other various techniques like RAG.&bull;\nGained experience in all aspects of AI research, from data collection and preparation to model development and\nevaluation.&bull;\nCollaborated with a team of experienced researchers to solve complex AI problems.\n&bull;', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(426, 102, 76, NULL, NULL, '76_102_781536741669d1c38ee83e_jasllm.pdf', 'jasllm.pdf', 'J	ASRAJ 	P	ATIL	 	\n7020453107	 | jasrajpatil2@gmail.com	 | www.linkedin.com/in/jasraj	-patil/	 | https://github.com/jasrajpatil	 	  \nEnergetic  and  innovative  Generative  AI  Engineer  eager  to  leverage  a  profound  background  in  AI, \nspecializing  in  vector  databases,  LLM  frameworks,  and  cloud  deployments.  Aims  to  apply  technical \nskills  and  creativity  in  developing  state	-of	-the	-art  AI  solutions  within  a  dynamic  team  setting.	 Also 	\nhaving 	experienced 	Data 	Analyst	 creating reports and visu	alizations with Power BI and handling data 	\nwith Python and SQL. 	 	\nSKILLS &amp; OTHER	 	\n&bull; 	Programming Languages	: Python, SQL	 	\n&bull; 	Frameworks &amp; Tools	: Pytorch, LangChain, LlamaIndex, Streamlit.	 	\n&bull; 	Generative AI Technologies	: Open	-source and paid LLM models (Llama2, 	Mistral, OpenAI, Gemma)	 	\n&bull; 	Vector Databases	: ChromaDB, Pinecone	 	\n&bull; 	Deployment Platforms	: AWS Bedrock, Hugging Face Spaces	 	\n&bull; 	AI/ML Techniques	: Fine	-tuning with custom data, vector embedding, NLP, neural network 	\noptimization, RAG.	 	\n&bull; 	Soft Skills	: Analytical thinking, p	roblem	-solving, teamwork, effective communication	 	\n \n PROFESSIONAL EXPERIENCE	 	\n \nInfocept	s, Nagpur	                                                                                                                             	                           	APR 	202	2 &ndash; May 2023	 	\nAssociate Data Analyst	 	\n&bull; 	Worked as Power BI Developer, on the Power BI environment Mig	ration project.	 	\n&bull; 	Created data models to support decision	-making processes.	 	\n&bull; 	Identified patterns and trends in large data sets and provided actionable insights.	 	\n&bull; 	Generated standard and custom reports to provide insights into business performance.	 	\n&bull; 	Designed and 	developed data pipelines to acquire, clean and process data.	 	\n&bull; 	Developed customized reports, summarizing and presenting data in visually appealing format.	 	\n&bull; 	Handled scripting tasks for extract, clean, and analyze data to derive actionable insights using Python	 	\n&bull; 	Provided technical support for troubleshooting analytics and reporting issues.	 	\n&bull; 	Participated in requirements meetings and data mapping sessions to understand business needs.	 	\n&bull; 	Developed and maintained courteous and effective working relationships.	 	\n 	\nESDS Soft	ware Solution	, Nashik	  	NOV 	202	1 &ndash;Apr 2022	 	\nTrainee	 	\n&bull; 	Built relationships with coworkers and team members to increase work productivity.	 	\n&bull; 	Gained experience in problem solving and troubleshooting issues for customers.	 	\n&bull; 	Checked client&rsquo;s requests and issues 	regarding the cloud environment.	 	\n&bull; 	Fulfilled the client&#039;s request and resolve the problems while interacting with clients and other internal \ndepartment.	 	\n \nQuest Integr	ity 	Services	, Pune	 	FEB 	202	1 &ndash;Oct 2022	 	\nAssociate System Engineer	 	\n&bull;  Collaborated with 	cross	-functional teams to support troubleshooting and minimize service	 	\ninterruptions.	 	\n&bull; Monitored and documented daily standard service requests for future analysis.\n\n&bull; Created flowcharts, diagrams and other documentation.	 	\nDelivered helpdesk service and support	 to customers.	 	\nProposed technical feasibility solutions for new system designs and suggested options for	 	\n&bull; performance improvement of technical components.	 	\n&bull; Monitored, tracked and prioritized new work requests at Help Desk within set response times.	 	\n \n EDUCATI	ON	 	\n \nNorth Maharashtra University	 	         	2019	 	\nCourse:	 Computer Engineering	, GPA	: 7.42	 	\n \nProject	 	\nAdvanced Q&amp;A Chatbots with DataStax Databases and Vector Embedding	 	\n&bull; 	Overview	: Engineered chatbots that provide accurate, context	-aware answers by 	integrating DataStax 	\ndatabases with vector embedding techniques.	 	\n&bull; 	Technologies	: DataStax Databases, vector embedding algorithms, Hugging Face Spaces.	 	\n&bull; 	Outcome	: Achieved a 40% reduction in the need for human intervention in customer service inquiries, 	\nimprovi	ng response accuracy and user satisfaction.	 	\n 	\nCERTIFI	CATIONS	 	\n \n&bull; 	Google&rsquo;s Data Analyst Professional Certificate.	                                                                                                      	2021	 	\n&bull; 	Azur Data Fundamentals                                                                                                       	                        	             	20	21', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(427, 102, 76, NULL, NULL, '76_102_700108048669d1c38ee9d6_Lochan_Raj_T_DResume.pdf', 'Lochan_Raj_T_DResume.pdf', 'Lo ch an  R aj T  D  \nData  S cie n tis t \nData  S cie n tis t  w it h  3 + ye ars   o f  stro ng  e xp erie n ce  d eliv e rin g  h ig h-q ualit y   B 2B  a n d  B 2C  M L m odels .\nExp erie n ce  in  d eve lo pin g  m ach in e le arn in g  m odels  a n d  c o m pute r  v is io n a p plic a tio ns a n d  s o lu tio ns to\nso lv e  r e al- w orld  b usin ess p ro ble m s \nlo ch an d eva ra ja 0 817@ gm ail .c o m  \n8150888972 \nBen g alu ru  \nlin ke d in .c o m /in /lo ch an ra jt d  \nWORK  E X PER IE N CE \nData  S cie n tis t \nHew le tt-P ack ard  E n te rp ris e  \n12/2 022 -  P re se n t\n, \n  Ben galu ru  \nEn han ce d  a ir p o rt  s e cu rit y  a n d  p asse n g er s c re en in g  a ccu ra cy\nby 9 9%  u sin g  a  Y O LO v7 -b ase d  co lo r  d ete ctio n m odel  fo r\neﬃ cie n t  to p  an d   bo tto m  clo th in g   dete ctio n,  k-m ean s\nclu ste rin g   fo r  do m in an t  co lo r  id en tiﬁ ca tio n,  an d   th e\ndelt a _e _cm c m eth o d f o r p re cis e  c o lo r d ete ctio n.  In te g ra te d\nwit h  t h e S A FR  p la tfo rm  f o r c o m pre h en siv e  p eo ple -t ra ck in g  \nPart n ere d  w it h  c ro ss-f u nctio nal  t e am s ( R eg io n a n d  P ro duct)\nto  d eﬁ ne c lie n t r e q uir e m en ts  a n d  d eve lo p P O Cs le ve ra g in g\nMach in e L e arn in g  m odels   a n d  te ch n iq ues  to  a d dre ss  th eir\nbusin ess c h alle n g es \nLe d   th e  deve lo pm en t  an d   im ple m en ta tio n  of  a  m ed ic a l\ndo m ain   PO C  fo r  tu m or  cla ssiﬁ ca tio n.  A ch ie ve d   a  99.8 %\naccu ra cy   ra te  w it h  a  n ove l  im ag e p ro ce ssin g  m odel  b uil t\nusin g  V is io n T ra n sfo rm ers  \nSp earh ead ed  a  P O C fo r  fra u d  tra n sa ctio n d ete ctio n at  a\nle ad in g  In d o nesia n  b an k.  L e ve ra g ed  O CR  to ols   lik e  T a b ula\nan d   PyP D F2   to   extra ct  stru ctu re d   data   fro m  acco unt\nsta te m en ts , e n ab lin g  r e al- t im e f ra u d  i d en tiﬁ ca tio n \nExp erie n ce   in   m odel  m onit o rin g ,  tra ck in g ,  an d   sto rin g\ndiﬀ ere n t  model  mult ip le -r u n  re su lt s   wit h   diﬀ ere n t\npara m ete rs  o n t h e G CP c lo ud  u sin g  M LF lo w  \nSo ft w are  E ng in eer-L 2  \nPace  W is d o m  S o lu tio ns P vt L td  \n03/2 020 -  1 1/2 022\n, \n  Ben galu ru  \nConstru cte d  a  t a rg ete d  c u sto m er c la ssiﬁ ca tio n m odel  u sin g\nXG Boost  to   pro vid e  actio nab le   busin ess  in sig hts   to   th e\nsta ke h o ld ers  f o r m ark e tin g  a n d  p ro m otin g  t h eir  m utu al f u nd\nan d  i n su ra n ce  p la tfo rm  \nDeve lo ped  a  P O C f o r a  t o uris m -s m art  it in era ry  t o  o ne o f t h e\nto p  10  re n te d   bik e   co m pan ie s  usin g   Fo liu m  to   cre ate\nin te ra ctiv e  g eo gra p hic  v is u aliz a tio ns \nVis u aliz in g   th e  cu sto m er  po rt fo lio   pag e  w it h   diﬀ ere n t\ngra p hs a n d  c h art s  u sin g  S e ab o rn  a n d  M atp lo tlib  \nED UCATIO N \nPost G ra d uatio n D ip lo m a i n  D ata  S cie n ce  \nIIIT -B an g alo re  \n12/2 020 -  0 1/2 022\n, \n  Ben galu ru  \nDeep  L e arn in g  \nBE i n  E le ctro nic s a n d  I n stru m en ta tio n \nMaln ad  C ollg e o f E n g in eerin g  \n2015 -  2 019\n, \n  SK IL L S  \nPyth o n \nMach in e L e arn in g  A lg o rit h m s \nArt iﬁ cia l I n te llig en ce  \nCom pute r V is io n \nDeep  L e arn in g  \nIm ag e P ro ce ssin g  \nSQ L \nKera s \nED A \nOpen C V  \nScik it -L e arn  \nTe n so rF lo w  \nGCP \nMLF lo w  \nDock e r \nNLP  \nData  V is u aliz a tio n -  S e ab o rn , M atp lo tL ib  \nDeb ug gin g  \nDecis io n-M akin g  \nPER SO NAL P R O JE C TS \nMRI I M AG E P R O CESSIN G\n ( 1 2/2 021 -  0 2/2 022)\n \nBuil t  G AN  m odel u sin g  G en era to rs  a n d  D is c rim in ato rs  f o r e xtra ctin g\nmult ip le  i m ag es f ro m  t h e o rig in al M RI i m ag e \nPro je ct  c y cle  in clu d es  D ata  P ro ce ssin g ,  M odel  B uil d in g ,  H an d lin g\nLo ss a n d  M odel T ra in in g  \nACH IE V EM EN TS \nBest P ro je ct A w ard  \nHPE. &bull;  F o r b uil d in g C om pu te r V is io n b ase d  m odel \nSta r P erfo rm er O f T h e Q uart e r \nPace  W is d o m  S o lu tio ns P vt L td  &bull;  2 021-2 022 \nLA N GUAG ES \nEn g lis h  \nFu ll P ro fe ssio nal P ro ﬁ cie n cy  \nKan nad a \nNativ e  o r B il in gual P ro ﬁ cie n cy  \nIN TER EST S \nTe ach in g  \nPho to gra p hy \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s \nCours e s', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(428, 102, 76, NULL, NULL, '76_102_403970737669d1c38eeb89_Lokesh_Jaiswal_AI_(1).pdf', 'Lokesh_Jaiswal_AI (1).pdf', '', 2, 3, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0);
INSERT INTO `resume` (`id`, `screeningId`, `adminId`, `candidateId`, `candidateDetailsId`, `resumeName`, `resumeOriginalName`, `resumeContent`, `isSkillScreened`, `isResumeScreened`, `isCron`, `isCandidate`, `candidateShortlist`, `enableInterviewReport`, `gptLanguageId`, `isInterviewAssign`, `interviewValidity`, `interviewAssignDate`, `isPsychoAssign`, `psychoValidity`, `psychoAssignDate`, `created`, `createdBy`) VALUES
(429, 102, 76, NULL, NULL, '76_102_774637102669d1c38eed5e_Manjunatha_A_Resume_(1).pdf', 'Manjunatha A Resume (1).pdf', 'Man ju n ath a A   	A I S o ft w are  E n gin eer	\nBen ga lu ru , 5 60029,	 	m an ju n ath an air m an ju @ gm ail .c o m	 	\n8317321587	 	13/1 1/1 996	 	Lin ke d In	 	G it h ub	 	\nC AR EER  O BJE C TIV E\nI  p osse s 3  y e a rs  in  D ata  S cie n ce ,  I  h ave  d eliv e re d  e n d -t o -e n d  s o lu tio n s in  G en -A I,  M ach in e L e a rn in g,  a n d\nC om pute r V is io n /N LP  p ip elin es.  M y h an d s-o n  e xp ertis e  in  d eve lo p in g a n d  d ep lo yin g a d va n ce d  m od els  d riv e s\nin nova tio n  a n d  i m pactfu l o u tc o m es, o ptim iz in g b usin ess p ro ce sse s w it h  c u tt in g-e d ge  t e ch n olo gie s.\nE d uca tio n\n06/2 018 &ndash;  0 5/2 021\nK alb urg i,	 I n d ia	\nM CA, 	C en tr a l 	U niv e rs it y  	o f 	K arn a ta ka	\nM CA w as c o m ple te d  w it h  a  f ir s t-p la ce  f in is h  a n d  a  g o ld  m ed al, w it h  a n  o ve ra ll s c o re	 	\no f 9 0.9 3% .	\n06/2 015 &ndash;  0 5/2 018\nS h iv a m ogga ,	 I n d ia	\nB CA, 	S a hya dri 	S cie n ce  	C olle g e	\nB CA w as c o m ple te d  w it h  t h e f if t h  r a n k w it h  a n  o ve ra ll s c o re  o f 7 8.1 7%	\nP ro fe ssio n al E x p erie n ce\n08/2 022 &ndash;  p re se n t\nC hen nai,	 I n d ia	\nA I 	S oft w are  	E n gin eer, 	D ete ct 	T e ch n olo g ie s 	P vt 	L td	\n&bull;F o cu se d  o n  e n han cin g w ork sp ace  s a fe ty  i n  c h alle n gin g e n vir o n m en ts .\n&bull;S p ecia liz in g i n  i n te llig e n t v id eo  a n aly tic s, e m plo yin g P yth on , D ock e r, a n d	 	\nFFm peg .\n&bull;Exp ertis e  i n  v id eo /im age  p ro ce ssin g, d ete ctio n , c la ssif ic a tio n , a n d  c o n fin ed  s p ace	 	\nm on it o rin g.	\n09/2 021 &ndash;  0 8/2 022\nB en ga lu ru ,	 I n d ia	\nJ r.D ata S cie n tis t, 	iN eu ro n	\n&bull;W ork e d  o n  c o lle ctin g, c le a n in g, a n d  p re p ro ce ssin g d ata  t o  e n su re  i t s  q ualit y  a n d	 	\nsu it a b il it y  f o r a n aly sis .\n&bull;D eve lo p ed  a n d  i m ple m en te d  m ach in e l e a rn in g m od els  u sin g M L a n d  D L	 	\nalg o rit h m s. T h is  m ay i n clu d e t a sk s s u ch  a s f e a tu re  e n gin eerin g, m od el t ra in in g,	 	\nan d  m od el e va lu atio n .	\n01/2 021 &ndash;  0 6/2 021\nM um bai,	 I n d ia	\nD ata  	S cie n tis t 	In te rn , 	D eve le a rn	\nW ork e d  o n  a  r e a l- t im e f a ce  a tt e n d an ce  s y ste m  p ro je ct. T h e m ain  p urp ose  o f t h e	 	\nR ea l- T im e f a ce  r e co gn it io n  a tt e n d an ce  s y ste m  i s  t o  m ake  t h e a tt e n d an ce  s y ste m	 	\na u to m ate  a n d  e n han ce  t h e q ualit y  o f t h e c u rre n t a tt e n d an ce  s y ste m . I n  o u r s y ste m ,	 	\nwe a re  p ro p ose d  a  m od el w hic h  i s  o n e o f t h e b est l ig h tw eig h t a lg o rit h m s f o r f a ce	 	\nre co gn it io n  w it h  l e ss t im e c o m ple xit y .	\nS kil ls\nM ach in e L e a rn in g	 &mdash;  	Reg re ssio n , C la ssif ic a tio n  a n d  C lu ste rin g	P yth on	D eep  L e a rn in g	 &mdash;  	Com pute r	\nV is io n  a n d  N LP	C om pute r V is io n	 &mdash;  	Im age  a n aly sis  a n d  e n han ce m en t, T ra n sfo rm atio n s, F il t e rin g, F e a tu re	\ne xtra ctio n , a n d  P o se  E stim atio n	W eb App D ev e lo p m en t	 &mdash;  	Fla sk  a n d  D ja n go	C  a n d  C ++	\nTe n so rflo w	P yTo rc h	D ata b ase	 &mdash;  	MyS Q L,P o stg re S Q L a n d  M on go D B	D ock er a n d  G it\n\nPro je cts\n0 3/2 024 &ndash;  p re se n t	S afe S ig h t: 	I n d ustr ia l 	H elm et 	a n d  	P PE 	C om plia n ce  	w it h  	G en  	A I	\nI u n d erto ok a  p ro je ct u til iz in g v is io n -b ase d  l a rg e  l a n gu age  m od els , i n clu d in g G PT-\n4 o , L L A VA , L L A VA N ext, a n d  i D EFIC S. B y t e stin g t h ese  m od els  o n  d iv e rs e  s e ts  o f	 	\nin d ustr ia l i m age s, I  i m pro ve d  p ro m pt a cc u ra cy  t o  a ro u n d  9 5%  f o r d ete ctin g h elm et	 	\na n d  P PE s u it  c o m plia n ce  a n d  v io la tio n s. A d dit io n all y , I  d eve lo p ed  a n  A P I u sin g A W S	 	\nAP I G ate w ay a n d  A W S L a m bd a t o  a u th en tic a te  o b se rv a tio n s b ase d  o n  p ro m pt	 	\nen gin eerin g s ta n d ard s w it h  O pen AI.\nT e ch sta ck	 :  P ro m pt e n gin eerin g,G PT-4 o , L L A VA , L L A VA N ext, i D EFIC S ,  A W S L a m bd a.	\n04/2 023 &ndash;  0 2/2 024	V ig il a n t 	E ye : 	A I- P ow ere d  	W ork p la ce  	S afe ty	\nT h is  p ro je ct e m plo ys f a cia l r e co gn it io n  t e ch n olo gy f o r w ork e r a u th oriz a tio n ,	 	\nm on it o rin g t h e e n vir o n m en t f o r s a fe ty  v io la tio n s l ik e  h elm et o r P PE s u it  a b se n ce s. I t	 	\na ls o  p ro vid es p ers o n aliz e d  w ate r b re a k r e m in d ers , r e a l- t im e a le rts  f o r u n au th oriz e d	 	\nen tr y /e xit , g a s l e ve l/ te m pera tu re  m on it o rin g, e m erg e n cy  a le rts , a n d  c o n tin uou s	 	\nactiv it y  t ra ck in g.\nTe ch  s ta ck	: P yth on , Y o lo , P yT o rc h , d ete ctio n , c la ssif ic a tio n , A m azo n  R eko gn it io n ,	 	\nD ock e r.	\n0 9/2 022 &ndash;  0 4/2 023	C on ta in er 	V ertic a l 	T e xt 	D ete cto r	\nD ete ctin g v e rtic a l t e xt o n  t h e t ra in  c o n ta in er P O C. I  c re a te d  a  w eb ap p u sin g F la sk ,	 	\nexp lo re d  v a rio u s c o m pute r v is io n  l ib ra rie s,, a n d  c re a te d  c u sto m  C N N a n d  L S T M	 	\nm od el t o  d ete ct v e rtic a l t e xt. D ep lo ye d  o n  A W S c lo u d  u sin g E C 2 i n sta n ce .	 	\nC on tin uou s m on it o rin g o f t h e p ro je ct u sin g d ash b oard  o n  A W S a n d  a ls o  o n  A W S	 	\nEC S.\nTe ch  s ta ck	: T e n so rF lo w , P yT o rc h , P an d as, S Q L, L S T M , a n d  D eep  L e a rn in g	\n11/2 021 &ndash;  0 6/2 022	Fa ce  	R eco gn it io n  	B ase d  	Su rv e il la n ce  	S yste m	\nT h e m ain  t a sk  o f t h is  p ro je ct i s  t o  d ep lo y t h e m od el o n  e n d  d evic e s l ik e  t h e J e ts o n	 	\nN an o, J e ts o n  X a vie r, a n d  R asp berr y  P i.  E xp lo re d  v a rio u s q uan tiz a tio n  t e ch n iq ues	 	\nlik e  T FLit e , T a o  C on ve rte r, , P yto rc h  t o  T Flit e . D ep lo ye d  o n  e n d  d evic e s l ik e  J e ts o n	 	\nN an o a n d  J e ts o n  X a vio r\nTe ch  S ta ck	: M TC N N, P o stg re S Q L, c u sto m  d ata	\nA w ard s a n d  A ch ie v e m en ts\n0 8/0 1/2 019	A ce  	o f 	In nova tio n  	Sw arn a 	(Y o u n g 	S cie n tis t) 	a w ard -2 019, 	\nS u vid ha  	In nova tio n  	Tru st	\nS u vid ha I n nova tio n  T ru st h as g iv e n  m e t h e A ce  o f I n nova tio n  a w ard  f o r m y r e se a rc h	 	\nw ork  i n  r o b otic s, m ach in e l e a rn in g, a n d  d eep  l e a rn in g.	\n03/0 8/2 020	S m art 	In d ia  	H ack ath on  	2020 	Fin alis t, 	M HRD	\nPartic ip ate d  i n  t h e 3 D  m od el- b ase d  s y n th esis  r e co gn it io n  o f p en cil  s k e tc h -b ase d	 	\nfa cia l i m age s a n d  s e cu re d  s ix th  p la ce .	\n1 5/0 4/2 019	P re se n te d  	a 	p ap er 	o n  	 &ldquo;V is io n  	base d  	poth ole  	d ete ctio n&rdquo;, 	\nN IT  	W ara ng a l 	a sso cia te d  	by 	TS S C	\nP re se n te d  a  p ap er i n  N IT  W ara n ga l a sso cia te d  b y T S S C  o n  t h e t o p ic  &ldquo; V is io n  b ase d	 	\np oth ole  d ete ctio n&rdquo;	\n22/0 5/2 022	P re se n te d  	a 	p ap er 	o n  	&quot;R ea l-T im e 	Fa ce  	R eco gn it io n  	fo r 	O rg a n iz a tio n al 	\nA tt e n d an ce  	S yste m s&quot;  	 re se a rc h  	pap er 	o n  	R TIP 2R  	co n fe re n ce  	p ub lis h ed  	in  	\nSp rin ge r, 	S p rin g er 	p ub lic a tio n	\nIt  i s  a n  i n te rn atio n al c o n fe re n ce  o n  p att e rn  r e co gn it io n  a n d  i m age  p ro ce ssin g.', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(430, 102, 76, NULL, NULL, '76_102_1434326025669d1c38eef15_Manjunatha_A_Resume.pdf', 'Manjunatha A Resume.pdf', 'Man ju n ath a A   	A I S o ft w are  E n gin eer	\nBen ga lu ru , 5 60029,	 	m an ju n ath an air m an ju @ gm ail .c o m	 	\n8317321587	 	13/1 1/1 996	 	Lin ke d In	 	G it h ub	 	\nC AR EER  O BJE C TIV E\nI  p osse s 3  y e a rs  in  D ata  S cie n ce ,  I  h ave  d eliv e re d  e n d -t o -e n d  s o lu tio n s in  G en -A I,  M ach in e L e a rn in g,  a n d\nC om pute r V is io n /N LP  p ip elin es.  M y h an d s-o n  e xp ertis e  in  d eve lo p in g a n d  d ep lo yin g a d va n ce d  m od els  d riv e s\nin nova tio n  a n d  i m pactfu l o u tc o m es, o ptim iz in g b usin ess p ro ce sse s w it h  c u tt in g-e d ge  t e ch n olo gie s.\nE d uca tio n\n06/2 018 &ndash;  0 5/2 021\nK alb urg i,	 I n d ia	\nM CA, 	C en tr a l 	U niv e rs it y  	o f 	K arn a ta ka	\nM CA w as c o m ple te d  w it h  a  f ir s t-p la ce  f in is h  a n d  a  g o ld  m ed al, w it h  a n  o ve ra ll s c o re	 	\no f 9 0.9 3% .	\n06/2 015 &ndash;  0 5/2 018\nS h iv a m ogga ,	 I n d ia	\nB CA, 	S a hya dri 	S cie n ce  	C olle g e	\nB CA w as c o m ple te d  w it h  t h e f if t h  r a n k w it h  a n  o ve ra ll s c o re  o f 7 8.1 7%	\nP ro fe ssio n al E x p erie n ce\n08/2 022 &ndash;  p re se n t\nC hen nai,	 I n d ia	\nA I 	S oft w are  	E n gin eer, 	D ete ct 	T e ch n olo g ie s 	P vt 	L td	\n&bull;F o cu se d  o n  e n han cin g w ork sp ace  s a fe ty  i n  c h alle n gin g e n vir o n m en ts .\n&bull;S p ecia liz in g i n  i n te llig e n t v id eo  a n aly tic s, e m plo yin g P yth on , D ock e r, a n d	 	\nFFm peg .\n&bull;Exp ertis e  i n  v id eo /im age  p ro ce ssin g, d ete ctio n , c la ssif ic a tio n , a n d  c o n fin ed  s p ace	 	\nm on it o rin g.	\n09/2 021 &ndash;  0 8/2 022\nB en ga lu ru ,	 I n d ia	\nJ r.D ata S cie n tis t, 	iN eu ro n	\n&bull;W ork e d  o n  c o lle ctin g, c le a n in g, a n d  p re p ro ce ssin g d ata  t o  e n su re  i t s  q ualit y  a n d	 	\nsu it a b il it y  f o r a n aly sis .\n&bull;D eve lo p ed  a n d  i m ple m en te d  m ach in e l e a rn in g m od els  u sin g M L a n d  D L	 	\nalg o rit h m s. T h is  m ay i n clu d e t a sk s s u ch  a s f e a tu re  e n gin eerin g, m od el t ra in in g,	 	\nan d  m od el e va lu atio n .	\n01/2 021 &ndash;  0 6/2 021\nM um bai,	 I n d ia	\nD ata  	S cie n tis t 	In te rn , 	D eve le a rn	\nW ork e d  o n  a  r e a l- t im e f a ce  a tt e n d an ce  s y ste m  p ro je ct. T h e m ain  p urp ose  o f t h e	 	\nR ea l- T im e f a ce  r e co gn it io n  a tt e n d an ce  s y ste m  i s  t o  m ake  t h e a tt e n d an ce  s y ste m	 	\na u to m ate  a n d  e n han ce  t h e q ualit y  o f t h e c u rre n t a tt e n d an ce  s y ste m . I n  o u r s y ste m ,	 	\nwe a re  p ro p ose d  a  m od el w hic h  i s  o n e o f t h e b est l ig h tw eig h t a lg o rit h m s f o r f a ce	 	\nre co gn it io n  w it h  l e ss t im e c o m ple xit y .	\nS kil ls\nM ach in e L e a rn in g	 &mdash;  	Reg re ssio n , C la ssif ic a tio n  a n d  C lu ste rin g	P yth on	D eep  L e a rn in g	 &mdash;  	Com pute r	\nV is io n  a n d  N LP	C om pute r V is io n	 &mdash;  	Im age  a n aly sis  a n d  e n han ce m en t, T ra n sfo rm atio n s, F il t e rin g, F e a tu re	\ne xtra ctio n , a n d  P o se  E stim atio n	W eb App D ev e lo p m en t	 &mdash;  	Fla sk  a n d  D ja n go	C  a n d  C ++	\nTe n so rflo w	P yTo rc h	D ata b ase	 &mdash;  	MyS Q L,P o stg re S Q L a n d  M on go D B	D ock er a n d  G it\n\nPro je cts\n0 3/2 024 &ndash;  p re se n t	S afe S ig h t: 	I n d ustr ia l 	H elm et 	a n d  	P PE 	C om plia n ce  	w it h  	G en  	A I	\nI u n d erto ok a  p ro je ct u til iz in g v is io n -b ase d  l a rg e  l a n gu age  m od els , i n clu d in g G PT-\n4 o , L L A VA , L L A VA N ext, a n d  i D EFIC S. B y t e stin g t h ese  m od els  o n  d iv e rs e  s e ts  o f	 	\nin d ustr ia l i m age s, I  i m pro ve d  p ro m pt a cc u ra cy  t o  a ro u n d  9 5%  f o r d ete ctin g h elm et	 	\na n d  P PE s u it  c o m plia n ce  a n d  v io la tio n s. A d dit io n all y , I  d eve lo p ed  a n  A P I u sin g A W S	 	\nAP I G ate w ay a n d  A W S L a m bd a t o  a u th en tic a te  o b se rv a tio n s b ase d  o n  p ro m pt	 	\nen gin eerin g s ta n d ard s w it h  O pen AI.\nT e ch sta ck	 :  P ro m pt e n gin eerin g,G PT-4 o , L L A VA , L L A VA N ext, i D EFIC S ,  A W S L a m bd a.	\n04/2 023 &ndash;  0 2/2 024	V ig il a n t 	E ye : 	A I- P ow ere d  	W ork p la ce  	S afe ty	\nT h is  p ro je ct e m plo ys f a cia l r e co gn it io n  t e ch n olo gy f o r w ork e r a u th oriz a tio n ,	 	\nm on it o rin g t h e e n vir o n m en t f o r s a fe ty  v io la tio n s l ik e  h elm et o r P PE s u it  a b se n ce s. I t	 	\na ls o  p ro vid es p ers o n aliz e d  w ate r b re a k r e m in d ers , r e a l- t im e a le rts  f o r u n au th oriz e d	 	\nen tr y /e xit , g a s l e ve l/ te m pera tu re  m on it o rin g, e m erg e n cy  a le rts , a n d  c o n tin uou s	 	\nactiv it y  t ra ck in g.\nTe ch  s ta ck	: P yth on , Y o lo , P yT o rc h , d ete ctio n , c la ssif ic a tio n , A m azo n  R eko gn it io n ,	 	\nD ock e r.	\n0 9/2 022 &ndash;  0 4/2 023	C on ta in er 	V ertic a l 	T e xt 	D ete cto r	\nD ete ctin g v e rtic a l t e xt o n  t h e t ra in  c o n ta in er P O C. I  c re a te d  a  w eb ap p u sin g F la sk ,	 	\nexp lo re d  v a rio u s c o m pute r v is io n  l ib ra rie s,, a n d  c re a te d  c u sto m  C N N a n d  L S T M	 	\nm od el t o  d ete ct v e rtic a l t e xt. D ep lo ye d  o n  A W S c lo u d  u sin g E C 2 i n sta n ce .	 	\nC on tin uou s m on it o rin g o f t h e p ro je ct u sin g d ash b oard  o n  A W S a n d  a ls o  o n  A W S	 	\nEC S.\nTe ch  s ta ck	: T e n so rF lo w , P yT o rc h , P an d as, S Q L, L S T M , a n d  D eep  L e a rn in g	\n11/2 021 &ndash;  0 6/2 022	Fa ce  	R eco gn it io n  	B ase d  	Su rv e il la n ce  	S yste m	\nT h e m ain  t a sk  o f t h is  p ro je ct i s  t o  d ep lo y t h e m od el o n  e n d  d evic e s l ik e  t h e J e ts o n	 	\nN an o, J e ts o n  X a vie r, a n d  R asp berr y  P i.  E xp lo re d  v a rio u s q uan tiz a tio n  t e ch n iq ues	 	\nlik e  T FLit e , T a o  C on ve rte r, , P yto rc h  t o  T Flit e . D ep lo ye d  o n  e n d  d evic e s l ik e  J e ts o n	 	\nN an o a n d  J e ts o n  X a vio r\nTe ch  S ta ck	: M TC N N, P o stg re S Q L, c u sto m  d ata	\nA w ard s a n d  A ch ie v e m en ts\n0 8/0 1/2 019	A ce  	o f 	In nova tio n  	Sw arn a 	(Y o u n g 	S cie n tis t) 	a w ard -2 019, 	\nS u vid ha  	In nova tio n  	Tru st	\nS u vid ha I n nova tio n  T ru st h as g iv e n  m e t h e A ce  o f I n nova tio n  a w ard  f o r m y r e se a rc h	 	\nw ork  i n  r o b otic s, m ach in e l e a rn in g, a n d  d eep  l e a rn in g.	\n03/0 8/2 020	S m art 	In d ia  	H ack ath on  	2020 	Fin alis t, 	M HRD	\nPartic ip ate d  i n  t h e 3 D  m od el- b ase d  s y n th esis  r e co gn it io n  o f p en cil  s k e tc h -b ase d	 	\nfa cia l i m age s a n d  s e cu re d  s ix th  p la ce .	\n1 5/0 4/2 019	P re se n te d  	a 	p ap er 	o n  	 &ldquo;V is io n  	base d  	poth ole  	d ete ctio n&rdquo;, 	\nN IT  	W ara ng a l 	a sso cia te d  	by 	TS S C	\nP re se n te d  a  p ap er i n  N IT  W ara n ga l a sso cia te d  b y T S S C  o n  t h e t o p ic  &ldquo; V is io n  b ase d	 	\np oth ole  d ete ctio n&rdquo;	\n22/0 5/2 022	P re se n te d  	a 	p ap er 	o n  	&quot;R ea l-T im e 	Fa ce  	R eco gn it io n  	fo r 	O rg a n iz a tio n al 	\nA tt e n d an ce  	S yste m s&quot;  	 re se a rc h  	pap er 	o n  	R TIP 2R  	co n fe re n ce  	p ub lis h ed  	in  	\nSp rin ge r, 	S p rin g er 	p ub lic a tio n	\nIt  i s  a n  i n te rn atio n al c o n fe re n ce  o n  p att e rn  r e co gn it io n  a n d  i m age  p ro ce ssin g.', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(431, 102, 76, NULL, NULL, '76_102_1689089613669d1c38ef0c1_neel_mishra_resume.pdf', 'neel_mishra_resume.pdf', 'Neel Mishra\n+91-9723095555 |GitHub |\nmishraneel99@gmail.com |\nLinkedIn |\nLeetcode |\nExperience Tekion\nBangalore, Karnataka\nData Scientist July 2023 - Present\n&bull; Finetuned open-source LLM models tinyLlama, Llama2, and Zephyr for next email generation, reducing\nexecution time by 98.08% using paged attention and post-training quantization.\n&bull; Validated superior performance of fine-tuned LLMs by conducting advance statistical analysis; achieved21%\nhigher similarity and35% increased relevance in generated emails\n&bull; Constructed a robust RAG question-answering chatbot for vehicular marketing, processing data for 800+ cars\nusing Langchain and advanced features.\n&bull; Streamlined a pipeline to categorize and clean a 16K email dataset, cutting down execution time by 91.7%\nusing multithreading, clustering, and semantic similarities.\n&bull; Engineered a RASAintent classification bot, curating a dataset of 170,000 data points and achieving 96.5%\nvalidation accuracy .\nIIIT Hyderabad Hyderabad, Telangana\nThesis - Applied Numerical Optimization in Deep Learning August 2020 - November 2023 &bull;Collaborated with Principal Applied Scientists fromMicrosoft India on developing a minimax optimizer for\nGANs, achieving top inception scores and cutting execution time to 0.184 seconds .\n&bull; Implemented GPU-compatible PyTorch solvers for Conjugate and BI-Conjugate Gradient methods, achieving over\n96% runtime reduction compared to numpy&rsquo;s standard implementations.\n&bull; Designed a classical minimization solver, enhancing accuracy by up to 2%compared to benchmarks like SGD,\nAdam, and RMSProp on models like Resnet 50, DLA, and VGG.\nEducation International Institute of Information Technology\nHyderabad, Telangana\nMaster of Science by Research in Computer Science, 9.00/10August 2020 - November 2023\nGujarat Technological University Ahmedabad, Gujarat\nBachelor of Engineering in Computer Science, 9.11/10.0 June 2016 - May 2020\nPublications Angle based learning rate for gradient descent\n,Neel Mishra , Pawan Kumar, International Joint Conference on\nNeural Networks (IJCNN 2023, Rank A)link A Gauss-Newton Approach for Min-Max Optimization in GANs\n,Neel Mishra , Pawan Kumar, Bamdev Mishra,\nPratik Jawanapuria, World Congress on Computational Intel ligence (WCCI 2024, Rank A)\nProjects &bull;\nLed a team of four to implement MAP approach for motion deblurring. Utilized gradient descent for blur filter\nestimation and patch stitching for complete ob ject images.[ Link ]\n&bull; Developed a recommendation system using matrix factorization, custom loss formulation for latent factor estimation,\nand L2 regularization to counter overfitting.[ Link ]\nResearch Grants Awards &bull;\nMicrosoft Academic Partnership Grant (MAPG).\n&bull; IIIT &rsquo;s Innovation Hub for Data Banks, Data Services, and Data Analytics (IHub-Data)research grant.\nTechnical Skills Statistical Methods\n: Inferential Statistics, Probability Distributions, Confidence Intervals, p-value Analysis,\nHypothesis testing, Regression Analysis, Correlation Analysis\nMachine Learning : Linear/Logistics Regression, Random Forests, Gradient Boosting, XGBoost, Bagging, SVM, Lasso\nand Ridge and other regularization, Clustering\nLLM : Finetuning, Quantization, Evaluation, Deployment\nRAG : Langchain, LlamaIndex, RASA\nData Analytics : Data Mining, Data Integration, Web Scraping, SQL\nLanguages and tools : Python, Git, Linux, VS Code\nLibraries and Frameworks : PyTorch, TensorFlow, langchain, llama-index, scikit-learn, pandas, numpy', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(432, 102, 76, NULL, NULL, '76_102_1376279461669d1c38ef2a2_new_2_years_Data_Scientist_Sayali-1_(1).pdf', 'new_2_years_Data_Scientist_Sayali-1 (1).pdf', 'SAYALI	 SALUNKHE	 	\nMob:+91	-7769974729	 | Email:	 sayali.sk333@gmail.com	 | Linkedin	 | Github	| Pune,	 India,	 411020	 	\nEXPERIENCE	 SUMMARY	 	 	\n&bull; 	COEP,  Postgraduate 	Data  Scientist  with 	2+  years 	of  overall  experience  focused  expertise  in  the  dynamic  realms  of  Data 	\nScience, specializing in Natural Language Processing (NLP) within the broader spectrum of Machine Learning	 	\n&bull; 	Skilled	 in python	 packages	 like 	Scikit	-learn,	 Numpy,	 Pandas,	 Tensorflow,	 Keras,	 Hugging	 Face,	 NLTK,	 Spacy,	 Gensim, 	\nMatplotlib, Streamlit, Flask.	 	\n&bull; 	Worked  in  projects  involving 	classification,  clustering  and  regression  algorithms  like  KNN,  Decision  trees,  Random 	\nforest, XGBoost, SVM, K	-Means, LSTMs 	and also have	 an understanding of	 CNN&rsquo;s, Embeddings, Prompt Engineering, 	\nWord2Vec,Encoders	-Decoders,Seq2Seq,Attentions,Transformers(BERT),Generative	 AI	 ,ChatGPT,Open	 AI	 API	 with 	\ndeployment in various platforms like AWS (EC2) Sagemaker, GCP	 	\n&bull; 	Comfortable with end to end machine learning lifecycle, starting with	 data collection,	 EDA, feature engineering, feature scaling, 	\nmodel creation, hyperparameter tuning, deployment in production, and retraining the model	. 	\nEDUCATION	 	\nCollege	 of Engineering	 Pune,	 COEP	 Pune	 	July	 2015	 - July	 2017	 	\n&bull; 	Master of Technology: Electronics 	Engineering	 	 CGPA	: 8.96/10 	\nPune Institute of Computer Technology, PICT Pune	 	July	 2010 	- July	 2014	 	\n&bull; 	Bachelor of Engineering: Electronics and Telecommunication	 	 Distinction: 71.6 % 	\nMSBSHSE Board, KTHM College, Nashik	 	July	 2008	 - May	 2010	 	\n&bull; 	HSC	 - Science	 	86.70%	 	\nWORK	 EXPERIENCE	 	\nGenerative	 AI	 Engineer,	 Datamorphosis	 Pvt.Ltd	 	Mar	 24	-May	&rsquo;24	 	\n&bull; 	Collaborated	 with	 the	 backend	 AI	 team	 to develop	 doubt	 clustering,	 question	 answering,	 and	 generative	 AI	 modules.	 	\n&bull; 	Implemented	 NLP	 techniques,	 leveraging	 transformers	 and	 LLMs	 for	 enhanced	 performance	 	\nData	 Scientist,	 Freelancer	 	Sept	 22	-Jan	 24	 	\n&bull; 	Assist	 in the	 design	 and	 development	 of AI	 models.	 	\n&bull; 	Engage	 in data	 analysis	 and	 preprocessing	 for	 machine	 learning.	 	\n&bull; 	Collaborate	 closely	 with	 the	 AI	 team to	 optimize	 algorithms	 and	 augment	 existing	 models.	 	\n&bull; 	Present	 research	 findings	 and	 actively	 contribute	 to team	 meetings.	 	\n&bull; 	Developed	 extractive	 and	 abstractive	 summarization	 using	 advanced	 NLP	 techniques.	 	\n&bull; 	Enhanced	 NLP,	 Python,	 and	 ML	 skills;	 deployed	 Transformer	 models	 (e.g.,	 BERT,	 GPT	-4).	 	\n&bull; 	Used	 metrics	 like	 ROUGE,	 BLEU	 to measure	 and	 refine	 summarization	 quality.	 	\n&bull; 	Teamed	 up with	 cross	-functional	 colleagues,	 shared	 insights,	 and	 findings.	 	\n&bull; 	Enhanced	 summarization	 model,	 presented	 results,	 and	 expanded	 NLP	 expertise.	 	\n&bull; 	Worked	 on	 NLP,	 Computer	 Vision	 and	 Machine	 Learning	 based	 Projects.	 	\nData	 Science	 Intern,	 iNeuron.ai	| Remote	 	Sept	 19	 - Sept	 20	 	\n&bull; 	Requirement	 Gathering	 &amp; Translation:	 Gathering	 data	 from	 various	 sources,	 collecting	 our	 customer&#039;s	 data,	 and	 translating	 it 	\ninto use cases to solve real	-world problems.	 	\n&bull; 	Data Cleansing, Statistical &amp; Data Analysis: Clean, transform &amp; extract insights and provide sentiment analysis using the	 	\nfeedback from the courses for providing data	-driven recommendations.	 	\n&bull; 	Training &amp; Implementation: Developing content	-based course recommendation systems and an automated chat system for 	\nquestions and answers. Creating machine learning models as well for various use cases supplied by the clients	 	\n&bull; 	Knowledge	 in building	 applications	 with	 Artificial	 Intelligence,	 Machine	 Learning,	 Deep	 Learning,	 Recurrent	 Neural 	\nNetwork, Computer vision, NLP and Python.	 	\n&bull; 	Worked on Deployment and optimization of various projects computer vision, Machine learning and NLP solution on web	- 	\nbased application, Azure platform, AWS, GCP.	 	\nMachine	 Learning	 Engineer,	 Cognizant	 Technology	 Solutions	 | Pune,	 India	 	Feb	 18	 - Aug	 19	 	\n&bull; 	Data	 Analytics	 and	 Reporting:	 	\n- Explore	 and	 examine	 data	 from	 multiple	 disparate	 sources.	 Prepare	 a data collection	 plan	 from	 both	 structured	 and 	\nunstructured sources Collaborate and co	-ordinate with Technology and Business teams for all data needs.	 	\n- Perform	 exploratory	 data	 analysis	 and	 generate	 insights	 Validate	 hypothesis	 developed	 during	 exploration	 phase	 Present 	\ninitial results to business stakeholders and identify the next steps.	 	\n&bull; 	Create	 models	 using	 Python	 which	 involve	 Classification,	 Clustering.	 	\n&bull; 	Deriving	 insights	 and	 recommendations	 from	 the	 models.	 Performing	 data	 visualization	 and	 presentation	 to clients.\n\n&bull; 	Document	 all modeling	 steps	 in a systematic	 way	 including	 modeling	 process,	 insights	 generated ,	 presentations	 , model 	\nvalidation results and checklists built in the project.	 	\n \nTECHNICAL	 SKILLS	 	\nProgramming	 Languages	: (Python)	 | Frameworks	 (Tensorflow	 | PyTorch)	 | Rest	 API	 (Flask	 | FastAPI)	 	\nNatural	 Language	 Processing	 (RNN	 | Text	 Preprocessing	 | Transformers	 | BERT	 | Encoder	-Decoder	 | NER	 | Spacy	 | NLTK)	 	\nDatabase	 (MySql	 | MongoDb	 ) 	\nCloud	 (AWS,	 AZURE)	 | MLOps	 (Git	 | Docker	 | Github	 Actions)	 	\nMachine	 Learning	 Algorithms	 (Linear	 Regression	 | Logistic	 Regression	 | Decision	 Tree	 | Random	 Forest	 | Xg	 Boost) 	Feature 	\nEngineering 	(Pandas | Numpy)	 	\nLarge	 Language	 Models	 (Prompt	 Engineering	 | LangChain	 | Vector	 DB	 | OpenAI	 | LLM)	 	\nPROJECTS	 	\nChatbot	 Answering	 from	 Your	 Own	 Knowledge	 Base:	 Langchain,	 ChatGPT,	 Pinecone	 and	 Streamlit	 	\n&bull; 	Developed	 a chatbot	 that	 leverages	 the	 power	 of Langchain,	 OpenAI&#039;s	 ChatGPT,	 Pinecone,	 and	 Streamlit	 Chat.	 	\n&bull; 	Developed	 chatbot	 not	 only	 responds	 to user	 queries	 but	 also	 refines	 queries	 and	 pulls	 information	 from	 its own	 document 	\nindex, making it efficient and capable of answering in	-depth questions.	 	\nAutomated	 Document	 Summarization	 using	 NLP	 	\n&bull; 	Developed	 a document	 summarization	 parser	 using	 TensorFlow	 and	 T5	-small	 HuggingFace	 pre	-trained	 model.	 	\n&bull; 	Text	 data	 from	 PDF	 is extracted	 using	 the	 PyPdf	 library.	 	\n&bull; 	Evaluated	 the	 performance	 of the	 summarization	 algorithm	 using	 metrics	 such	 as ROUGE	 and	 BLEU	 scores.	 	\n&bull; 	Conducted	 A/B	 testing	 to evaluate	 the	 performance	 of the	 algorithm	 against	 other	 state	-of-the	-art	 summarization	 techniques.	 	\n&bull; 	Utilized	 AWS	 cloud	 for	 project	 implementation	 and	 EC2	 instance	 for	 model	 deployment.	 	\n&bull; 	Implemented	 CI/CD	 using	 Github	 actions.	 	\nVideo	-Document	 based	 Conversational	 AI	 system	 using	 LLM	 and	 LangChain	 	\n&bull; 	Built	 a conversational	 AI	 system	 utilizing	 LangChain	 and	 LLM	 to extract	 key	 information	 from	 video	 transcripts	 or 	\ndocuments.	 	\n&bull; 	Whisper	 Base	 7b	 is used	 for	 audio	 transcription.	 	\n&bull; 	Used	 OpenAI	 embeddings	 class	 for	 generating	 the	 embeddings.	 	\n&bull; 	Used	 Chroma	 DB	 to save	 the	 embeddings	 and	 cosine	 similarity	 is used	 to find	 out	 the	 similar	 chunks	 of documents.	 	\n&bull; 	A group	 of tasks	 including	 video	 summarisation,	 and	 chat	-with	-video/documents	 are	 obtained	 using	 text	-davinci	-003	 LLM 	\nmodel	 	\nFine	-Tune	 a Generative	 AI	 Model	 for	 Dialogue	 Summarization	 	\n&bull; 	Fine	-tune	 an existing	 LLM	 from	 Hugging	 Face	 for	 enhanced	 dialogue	 summarization	 	\n&bull; 	Set	 the	 FLAN	-T5	 model,	 which	 provides	 a high	-quality	 instruction	 tuned	 model	 and	 can	 summarize	 text	 out	 of the	 box.	 	\n&bull; 	Perform	 Parameter	 Efficient	 Fine	-Tuning	 (PEFT	), evaluate	 the	 resulting	 model	 and	 see	 that	 the	 benefits	 of PEFT	 outweigh 	\nthe slightly	-lower performance metrics.	 	\nTRAINING	 AND	 CERTIFICATIONS	 	\n&bull; 	Certified	 Data	 Science	 Professional,	 OdinSchool	 Certificate	 ID	-O4gQIBA4O0	  	Feb	 2023	-Sept	 2023	 	\n&bull; 	Generative	 AI	 with	 LLM	 	\n&bull; 	Microsoft	 Azure	 for	 Data	 Engineering	 	\n&bull; 	5 star	 Hacker	 Rank	 Profile	 	\n&bull; 	Testdome	 Python	 and	 SQL	 skill	 test	 certifications	 	\n&bull; 	Google	 Generative	 AI	 Learning	 Path	 	\n&bull; 	Graduate	 Level	 course	 from	 Stanford	 cs224n	: Natural	 Language	 Processing	 	\n&bull; 	GATE	 2015	 Qualified', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(433, 102, 76, NULL, NULL, '76_102_757172224669d1c38ef49b_Ranjith_Kumar_KN_2024_(2).pdf', 'Ranjith_Kumar_KN_2024 (2).pdf', 'R	a n j i t h   K u m a r	 K.	N	. 	\n  Bengaluru	, Karnataka	, Indi	a         	 LinkedIn/Ra	njith	-Kumar	   	  GitHub/R	anjith	-Kumar	          	 +91	 90087	69944	 	   ranjith.go226	0@gmail.com	 	\nE x p e r i e n c e	 	\nData Engineer	 | Pravaig 	Dynamics |	 Bengaluru, 	Karnataka,	 India	                                                                       	          	February 202	3 - Prese	nt      	                                       	\n&bull; 	Spearheaded  data  engineering  initiatives  within  the  Electric  Vehicle  Research  &amp;  Development  team	 and 	ensure  seamless  integration  of  data  engineering 	\nsolutions with EV R&amp;	D, enabling informed decision	-making based on data insights.	 	\n&bull; 	Developed and put into use data pipelines for vehicle data collecting that make effective use of technologies such as Kafka.	 	\n&bull; 	Integrat	ion of CAN	-BUS, Radar,	 GPS and camera data into the data processing workflow, optimizing data ingestion and analysis	. 	\n&bull; 	Leveraged ROS2 framework for processi	ng IMU data, ensuring seamless integration and compatibility within the data ecosystem.	 	\n&bull; 	Implemen	ted and maintained automated data processing workflows using Jenkins, enhancing overall efficiency and reducing processing ti	mes.	 	\n&bull; 	Managed AWS infrastr	ucture  to support scalable data storage and  computation needs for EV data analytics.	 Developed and maintained an  in	-house data 	\nwarehouse to centralize and optimize data storage, retrieval, and analysis.	 	\n \nBig Data	 Engineer (	Apprenticeship)	 | T	ata	 Consultancy	 Services	 |Bengaluru, 	Karnataka,	 India	            	                  	April	 2022 	&ndash; October 	2022	 	\n 	\n&bull; 	Developed  and  maintained  scalable  data  pipelines  using  Hadoop,  Spark,  and  oth	er  Big  Data  technologies  to  process  large  volumes  of  data,  resulting  in 	increased  efficiency  by  30%.	 Conducted  data  analys	is  and  visualization  to  extract  actionable  insights,  aiding  stakeholders  in  making  informed  business 	decisions.	 	 	\nResearch Scholar 	- Data Scienc	e | MENMOZHI 	TECHNOLOGIE	S |Bengaluru	, Karnataka,	 India	             	                 	 February	 2022 	&ndash; May	 2022	 	\n 	\n&bull; 	Experience  in  the  space  of  Software  Development  in  Computer  Vision	 utilizing  a  m	ix  of  customary  Image  Processing  based  and  current	 Machine 	Learning/Deep Learning	-based methods.	 	 	\n Skills	 \n&bull; 	Programming	 Skills	: Python	 (Pandas,	 NumPy,	 Matplotlib	), Machine	 Leaning	, Deep	 Leaning	 (CNN),	 Tensor	Flow, PyTorch	, Deep Leaning, Scala,	 	\nR Langua	ge. 	\n&bull; 	 	o	 	 HTML, REAC	T, CSS, DJANGO, FLASK, FAST 	API.	  	\n&bull; 	Database	 Skill	s: SQL,	 MongoDB,	 Redis	, Hadoop	, Hive	, NoSQL.	 	\n&bull; 	Miscellaneous	 Skills	: Git,	 Docker	, Applied	 Statistics,	 Power	 BI, Jenkins	,  Circle  CI	, Rabbi	tMQ	, Kafka, Ansi	ble	, Airflo	w, ML	-flow, 	AWS	, Azure, 	\nMu	ltiprocessing, Statistical Modeling, Hypothesis Testing	, Clustering	, ETL, 	Object Detection, NLP, NMT	. 	\n&bull; 	 	Time 	Ma	nagement, Teamwork, Proble	m-solving, Docum	entation, Scum	, Meeting and Engaging Presentation. 	\nE d u c a t i o n	 	\nSt. Joseph&#039;s	 University	, Bengaluru	                                                                              	                            	Sheshadripuram	 Collage	, Bengaluru	 	MSc,	 Big Data	 Analytics	, 2020	 &ndash; 2022	       	                                                                                              	Bachelor	 of Computer	 Applications	, 2016	 &ndash; 2019	 	\nP r o j	e c t s	 	\nA study on dog emotion recognition using deep learning tec	hniques	 (AIP (American Institute of Physics)	 Recognized):	 	\nThe purpose of this research was to determine if a deep learning system can 	classify	 various	 facial emotion classes in dogs, such as happiness,	 	sadness, anger, and neutral. For	 this, we proposed three different convolutional net	works. The findings prove that, when	 compared to the other models, the suggested 	\nmodel MBCC	-CNN outperforms in terms of	 facial expression recognition in dogs	. Link	 to paper	:  AIP	 Paper	 link	 	\n \nNeural	-Machine	-Translation: Models: Transformers, Bert, SMT, Seq2Seq	: 	\n \nNatural machine translation refers to the process of using computational algorithms and artificial intelligence to translate	. I have used 	BERT, Seq2Seq, and Transformers	 	models	 which	 all are 	significant models in the field of natural language processing (NLP), particularly in machine translation.	 In practice, these models can be combin	ed 	\nor used in different parts of a machine translation system	.  Project	 link	:  NMT	 Proj. link	 	\n C e r t i f i c a t e s	 	\n&bull; Python Data Structures Coursera 	-- Sept 2021: 	 Link                                            	           	 &bull;  Data Analytics Virtual Experience Program	: Link	 	\n&bull; The Sparks Foundation Virtual Internship 	-- October 2021:	  Link                      	           	  &bull;  Data Science	 using	 R: Link', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(434, 102, 76, NULL, NULL, '76_102_720473241669d1c38ef681_Resume_(7).pdf', 'Resume (7).pdf', 'Priya Gupta\n� +91 9455905525\n#priyag239@gmail.com �\nLinkedIn Ob jective\n&bull;\nExperienced data scientist adept at utilizing a diverse skill set encompassing programming languages, tools, and\nmethodologies to drive data-driven solutions. Seeking an opportunity with a progressive organization where I can\ncontribute my expertise in areas such as machine learning, data analysis, and software development to address complex\nchallenges and drive business success\nWork Experience Sravathi AI Pvt Ltd\nMarch 23 &ndash;Present\nData Scientist Bangalore\n&bull; Performed an exhaustive Exploratory Data Analysis (EDA) to meticulously uncover the dataset&rsquo;s underlying\ncharacteristics and patterns. Utilized a combination of advanced visualization tools and robust statistical methodologies\nto unveil significant trends, correlations, and anomalies, thereby establishing a robust framework for subsequent\nanalytical endeavors.\n&bull; Applied advanced feature engineering techniques to preprocess data, refining it for modeling purposes and amplifying\nthe predictive prowess of the models. Leveraged specialized chemistry-related libraries to extract domain-specific\ninsights, ensuring robustness in predicting both reaction outcomes and impurity formation.\n&bull; Utilized Deep Learning methodologies to craft predictive models customized to the dataset, enabling accurate\nforecasting of reaction outcomes. Executed rigorous model training protocols to enhance performance and precision.\nIncorporated considerations for product form variations during reactions and impurity levels to ensure comprehensive\npredictive capabilities\nSravathi AI Pvt Ltd March 22 &ndash; March23\nData Scientist Bangalore\n&bull; Conducted thorough Exploratory Data Analysis (EDA) to gain comprehensive insights into the dataset&rsquo;s characteristics\nand patterns. Leveraged visualization and statistical techniques to uncover key trends, relationships, and outliers, laying\na solid foundation for subsequent analytical tasks\n&bull; Performed feature engineering techniques to prepare data for modeling, enhancing the predictive capabilities of the\nmodels. This strategic approach facilitated\n&bull; Designed and developed predictive models tailored to the dataset to forecast yield outcomes. Implemented model\ntraining processes to optimize performance and accuracy. These efforts streamlined decision-making processes and\ncontributed to increased efficiency in research and development initiatives\n&bull; Visualizing and analyzing data enables inference generation, empowering chemists working in labs to guide their research\nand development efforts more efficiently, thereby saving valuable time\nRBG Labs IIT-Madras Oct2020 - Aug2021\nData Science Research Intern IIT-Madras\n&bull; Conducted statistical analysis to understand data patterns and relationships; identified trends and insights.\n&bull; Developed and implemented deep learning models optimized models for accuracy and performance through\nhyperparameter tuning and validation techniques.\n&bull; Spatial Analysis using the R, python and Deep Learning.\n&bull; Collaborated with research scientists, engineers, and other team members to achieve pro ject goals and reviewed latest\nresearch in data science and machine learning; experimented with new algorithms and methodologies to enhance existing\nprocesses\n&bull; Used: Ob ject Detection Algorithm, Image Analysis,Computer Vision To detect Traffic Rules Violation\n(Overloading),Python and R\n\nAcademic pro ject\nSentiment Analysis\nWeather Forecasting in Time Series Analysis\nDetection of road boundary of curved and muddy road Using Image Processing\nMedical Domain(Covid 19) question answering system Using NLP\nEye gaze estimation using CNN\nCovid-19 analysis in different States or Union Territory using SVM\nLand cover classification using meta learning techniques\nLoan Approval prediction using Logistics Regression\nPredicting Pulsar Star Using Deep Learning\nSpace Exploration Using Reinforcement Learning\nHybrid Approach For Traffic Rules Violations Detection\nUSA Crimedata Analysis using hadoop map-reduce framework\nTechnical Skills Languages\n: Python, R\nLibraries : Numpy, Pandas, Scikit-Learn, Statsmodels, Pytorch, Keras,\nTensorflow,Bert,Biobert,Gensim,Spacy,NLTK,Opencv,Matplotlib,Beautiful Soup,Seaborn\nAlgorithms : Data Visualization, Machine Learning, Deep Learning, Time Series, Computer vision, Image Processing,\nOb ject Detection, YOLO, Text Analytics\nDatabases : Apache Pig,Apache,Hive,Hadoop SQL\nTools : weka, Data Preparator,Labelimg,Eclipse,matlab,Netbeans\nEducation Amrita Vishwa Vidyapeetham M.Tech Data Science\nGrade : First Class\nDr APJ Abdul Kalam University Former UPTU B.Tech in IT\nGrade : First Class\nPublications and Conferences &bull;\nICCNCT-2022\nCertificates and Training &bull;\nC.NET Web Development from Microsoft Training Associate\n&bull; Advanced Java from NIIT AWS Webinar on &rdquo;Insights into AI and ML&rdquo; Workshop on Android and Ethical Hacking\n&bull; Coursera Deep Learning', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 14:33:28', 0),
(435, 103, 76, NULL, NULL, '76_103_1547583597669d5282a68de_Devops_Resume_(1).docx', 'Devops Resume (1).docx', '\r\nRESUME\r\nN.B.M.Sai Kishore\r\nContact no:7702806342\r\nEmail Id: ksai93654@gmail.com\r\n Professional Summary:\r\nOver all 2 years of experience as a DevOps Engineer, Extensively hands-on technical experience in the design and creation of large scale distributed and fully automated Continuous Integration and Build &amp;amp; Deployment processes for numerous Agile projects, spanning many different technologies and platforms.\r\nSummary of Experience:\r\n\r\nExperienced in Build, Release, and SCM and Deployment activities.\r\nWorked on Hudson, Jenkins for continuous integration and for End to End automation for all build and deployments.\r\nExtensive experience using MAVEN as build tools for the building of deployable artifacts (jar, war ) from source code.\r\nBuild, Configure, Manage and Coordinate all Build and Release Management activities.\r\nTroubleshooting and problem solving of Linux/UNIX servers, debugging OS failure.\r\nExperience in working on source control tools like Tortoise, Git lab .\r\nHands on working experience in Unix/Linux and Windows Environments.\r\nExpert in deploying the code through web application servers like Apache Tomcat.\r\nAbility in development and execution of Groovy Script.\r\nHaving strong Automation skills with respect to Build/Deploy process.\r\nExperience in working with Tracking Tools JIRA.\r\nExperience on Subversion- Created branches, tagging providing access Permissions over the Branches.\r\nPrepared deployment plans for each deployment of the product.\r\nMaintaining Repository and New user creation/user deletion and set up archive with groups and roles.\r\nExperience in JENKINS to schedule a job as per the requirement, report monitoring and notification functionality to report success or failure.\r\nAbility in managing all aspects of the software configuration management process including code compilation, packaging / deployment / release methodology, and application configurations.\r\nExposure in Agile Methodology Architecture using Java and Oracle as backend Work with Development Teams and Testing Team to establish a build schedule, Execute the builds\r\nProfessional Experience\r\n\r\nWorking as a Devops Infra Engineer in Oracle(OFSS)  June 2022 to Till Date\r\nSkill Set\r\n\r\nOperating Systems Windows, Linux\r\nBuild tools Maven\r\nCI Tools Jenkins, Hudson\r\nApplication Server Weblogic, Apache http\r\nSCM Tools GIT, Bit bucket\r\nCode Quality Analysis SonarQube.\r\nBug/ Project Tracking Tools Jira\r\nCloud Platform AWS\r\nScripting Groovy\r\nContainerization Tool Docker\r\nConfiguration management Tool Ansible\r\nIAAC(Infrastructure as a code) Terraform\r\nArti factory Jfrog, Nexus\r\nProjects:\r\n\r\n              Project 1\r\n   Designation: Devops Infra Engineer\r\n   Environment: Git, GitHub,Tortoise SVN, Jenkins, Apache, Weblogic, Oracle DB, Docker.\r\nDescription\r\n                 Oracle Banking Payments (OBPM) serves as an enterprise payment solution, acting as a centralized\r\n              processor for both Corporate and Consumer payments within Banks. In the back-office, it functions\r\n              as a single-point connection to Payment Clearing Networks that Banks participate in. With built-in \r\n              support for processing Cross-border SWIFT, SEPA, and other Payment Networks in the US, India, \r\n              China, OBPM is equipped to handle diverse international transactions. In the front office, a well-\r\n              integrated DX layer, meeting modern digital banking requirements seamlessly, complements it. \r\n              Designed as a multi-country solution, OBPM can integrate with multiple DDA systems in a single\r\n              instance. Additionally, to fulfil the demands of a payment-processing hub, it can integrate with \r\n             various systems including Sanctions screening, AML, Treasury, Pricing, and Accounting. Upstream \r\n             integration is also possible with channels and other product processors at Banks. SEPA messages\r\n             migrated to the ISO 2019 version to enhance interoperability, standardization, and efficiency within \r\n             the Single Euro Payments Area (SEPA), aligning with global standards to improve communication \r\n             and transaction processing across financial institutions, ultimately boosting the reliability and \r\n             effectiveness of cross-border payments within the Eurozone.\r\nRoles and Responsibilities\r\nResponsible for creating repositories, teams, add members to teams and also providing access to repositories in Git Hub.\r\nSupport the code builds by integrating with continuous integration  tool(Jenkins).\r\nSupporting different environments like Prod, Dev and Staging.\r\nManaging Continuous Integration and Continuous Delivery (CI/CD) using Jenkins.\r\nWorking closely with dev team to manage CI environment using Jenkins, Code Commit.\r\nAutomating Build related tasks using scripting language like Shell.\r\nInvolved in Build and Deployment activities.\r\nInvolved in the release process and deployed applications (WAR and JAR) to the Tomcat.\r\nWork closely with Development team on Build and Deployment issues\r\nUser &amp;amp; Group administration and resolving user related problems.\r\nCreating and monitoring various Jenkins job.\r\nCreating and maintaining state less and state full applications using Docker.\r\nInstalling packages using RPMs &amp;amp; YUM Installation.\r\nConfigure SSH (Secure Shell) and Creating YUM Repository.\r\nAutomation of jobs through Crontab.\r\nMonitoring System components such as CPU, Disk and SWAP space.\r\nConfigured NFS file systems and share them to clients.\r\nConfiguring FTP Server to maintain the shared folders within the Organization.\r\nExperienced with working in Production, Development and Testing environment.\r\nHelp Development teams automate the environment setup using tools like Ansible. \r\nMaintained Playbooks and Inventory for Configuration Management using Ansible.\r\nKnowledge on shell scripting\r\nKnowledge on java \r\nDeploying and monitoring Kubernetes pods and debugging various issues.\r\nKnowledge on Amazon Web Services (AWS), Creating EC2 Instances and configuring all\r\nnecessary services.\r\nDesign and implemented Security using VPC, IAM, Security Groups etc...\r\nInvolved in designing and deploying a multiple application almost all of the AWS stack like EC2, \r\nEBS, S3, RDS, SNS, VPC, IAM, etc. focusing on high-availability, Disaster recovery\r\nConfigured Connection Pool and Data Source Object for Database Connectivity.\r\nCreated and configured the Data sources for database connectivity\r\nConfigured JVM arguments, JMS/JDBC adapters, MQ, RAC data sources, user authentication and troubleshot issues with process deployments.\r\nConfigured Node Manager in a clustered environment &amp;amp; assigning the node manager to various WebLogic server components for remote administration.\r\nConfigure node manager, associating managed servers to a machine to control/monitor managed servers on various physical boxes.\r\nAutomated WebLogic domain configuration and services configuration using Unix Shell scripts.\r\nEnabled session sharing and management across different web applications, domains and heterogeneous application servers using Oracle Coherence.\r\nExperience on PowerShell scripting.\r\nExperience on Oracle db\r\nManage and building Data Guard Standby databases and manage/monitor database backup/recovery and creation/maintenance of development, system test and production database.\r\nPerformed installation and configuration of Database software, Listener, and Database creation in development, staging and production environment.\r\nEducation\r\n\r\nB.Tech in Mechanical Engineering, Passed with 62.2% from Srinivasa Institute of Engineering and Technology.\r\nIntermediate, Passed with 79% from State Board from Narayana junior college.\r\n10th standard, Passed with 75% from State Board.\r\nAcknowledgement\r\n\r\nI hear by declare that all the details furnished above are true to the best of my knowledge.\r\nPlace: Bangalore\r\nDate:\r\n                                                                                                                                                          ----------------------------\r\n', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 18:25:06', 0);
