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
(436, 103, 76, 47, NULL, '76_103_838322871669d5282a6f39_Resume_Rishav.pdf', 'Resume Rishav.pdf', 'Summary	 	\n&bull; 	Having 	5 years	 of  industry  experience  in	 Machine  Learning,  AI, 	Generative  AI,  and  data	 with  few  y	ears  of 	\nexperience in managing	 Data	 science	 and Machine learning	 projects	. Application to the disciplines of machine 	\nlearning  and  neural  networks  using  a  variety  of  systems  and  methods  in  trainin	g  algorithms  with  different 	\nclou	d platform	. 	\n&bull; 	Efficient in preprocessing	 data	 including	 Data	 cleaning, Correlation analysis, Imputation, 	Visualization, Feature 	\nScaling and Dimensionality Reduction techniques using Machine learning platforms like Python	 Data	 Science 	\nPackages (Scikit	-Learn, Pandas, NumPy).	  	\n&bull; 	Experience in 	building	 Natural Language Processing, Text Classification, Semantics and	 Sentiment Analysis	. 	\n&bull; 	Experience  in  Text  Analytics,  developing  different  Statistical  Machine  Learning,	 Data	 Mining  solutions  to 	\nvarious business problems and generat	ing	 data	 visualizations using	 Python.	  	\n&bull; 	Experience in	 data	 analysis, handling missing	 data, 	feature scaling, outlier analysis and 	unstructured data.	 	\n&bull; 	Experience in AI and Deep learnin	g platforms such as 	pytorch, 	TensorFlow 	and Keras.	  	\n&bull; 	Highly competent at researching, visualizing and analyzing raw	 data	 to 	identify recommendations for meeting 	\norganizational challenges.	  	\n&bull; 	Experience in 	EDA, 	building recommended systems	 and working on unstructured data	. 	\n&bull; 	Experience working with R	DBMS such as SQL Server, MySQL	, Oracle	. 	\n&bull; 	Experience in building large 	language model applications	 (LLMs)	 with LLAMA and GPT	, Claude	, and finetunning 	\nfor our own dataset with RAG	 framework	 and 	PEFT technique like 	LORA	. 	\n&bull; 	Experience in working on various vector databases ChromaDB, Pinecone and similarity search with FAISS	 	\nExperi	ence:	 	\nStatusNeo	 Technologies	, Gurugram	 	\nAI/ML Senior Consultant	  	\nDecember 2023	 to Present	  	\nResponsibilities: 	 	\n&bull; 	Responsible for developing chatbot using large language model that answers questions from the	 json 	files	, 	\nfor this	 use case	 we use	 Anthropic	 Claude 	model	 from AWS Bedrock and creating vectorstore wrapper to 	\nretrieve documents	. 	\n&bull; 	Developed	 large language model (LLM) application 	for Sentiment Analysis (3 categories) and Emotion 	\nExtraction (12 categories) to find the best suited sentiment and emotion of the 	complete text. For this use 	\ncase w	e use LLAMA2	-70B LLM model from AWS Bedrock.	 	\n \nBravura Solution	s,  Gurugram	 	\nMachine Learning Engineer 	 	\nSeptember 2022 to 	December 2023	  	\nResponsibilities: 	 	\n&bull; 	Responsible for developing chatbot	 using large language model	 that answers questions from the confluence 	\npages about the projects, for this we use llama	-2 13B model and finetune it with RAG and lora.	 	\n&bull; 	Developing large language 	model (LLM) application for writing SQL	 queries for	 our databases, train acco	rding 	\nto them 	using	 different version of	 llama models	. 	\n&bull; 	Responsible for creating dashboard on our databases insights after EDA and extracting required \ninformation&rsquo;s for our business need.	 	\n&bull; 	Responsible for applying torchs	erve on pytorch trained models which was previously 	with Flask, testing and 	\ndeployment of TorchServe	 on AWS cluster.	 	\n&bull; 	Develop and create	 python package for the product, building pipeline an	d publish own package.	 	\nRishav Kumar	 	\nEmail:	 rishav.adiran@gmail.com	 	\nMobile Number: 	8709145557/9457178931	 	\nlinkedin.com/in/rishav	-kumar	-98b04213b\n\nNCR Corporation	, Gurugram	 	\nData Scientist	 II 	\nMarch	 2021	 to September 2022	 	\nResponsiblities:	 	\n&bull; 	Responsible for building 	Deal Scoring Project	 where 	price range 	of a deal is calculated, it depends on type of 	\ndeal. 	We  are 	four	 people  team	 where	 my  role  here  is  to  write  logic,  API  code  for  FastApi,  connection  with 	\noracle and hive 	tables	 and deployment on 	Linux	 server	. 	\n&bull; 	Developed 	Fraud Detection m	odel 	and fraud analysis of the data 	to find frauds happening in bank transactions 	\ntried several algorithms like	 Anomaly detection, C	lustering 	and Neural Network with feature 	engineering and	 	\nseveral pre	-processing steps	 in Jupyter Notebook through Azure Machine Learning Studio	 instance	  	\n&bull; 	Responsible  for  the  analysis  of 	unstructured 	data  for  Shipment  Consolidation  project  where  objective  is  to 	\nreduce cost of shipment, which is all over	 America	. There are 	two	 parts in this project, first is to how to fit all 	\nthe  packages  inside  a  container 	or  truck 	so  maxi	mum  packages  can  be  uploaded,  second  part  is  of  route 	\noptimization like if a truck is delive	ring several packages for different location. We are five people team where 	\nmy role is of route optimization and information of how packages are organized.	 	\nBeahead	 PVT LTD,	 Noida	 	\nMachine Learning Engineer	 	\nAugust	 201	9 to 	March 2021	 	\nResponsiblities:	 	\n&bull; 	Applied  various  machine  learning  algorithms	,  deep  learning  algorithms	 and  advanced	 statistical	 analysis	 like	 	\nclassification algorithms, regression models using sci	kit	-learn	, keras, tensorflow	 package in Python.	  	\n&bull; 	Build  various  scrapers  for  client  of  Instagram,  Facebook,  Twitter 	and  for  data  mining.  In  the  same  project 	\ngender classification and age group classification model has been build with deep learning algorithms like CNN \nand transfer lear	ning.	 	\n&bull; 	Engineered  seve	ral  models  have  been  built  like  Age  classification  (accuracy 	&ndash; 92%),  Gender  classification 	\n(accuracy 	&ndash; 94%),  Sentiment  analysis  (accuracy 	&ndash; 98%)  and  keep  improving  these  models  to  make  more 	\ninformed decision for the client to find the perfect influencers f	or their brands to advertise. 	 	\n&bull; 	Analysing  the  scraped  influencer  like  how  their  followers,  following,  posts  or  tweets  are  increasing  or \ndecreasing, what kind of posts they are posting, how it is effecting their reach and engagements.	 	\n&bull; 	Responsible for 	building sentiment analysis model	. 	\nTechnical Skills:	 	\nDatabase	: SQL	, MySQL	 	\nProgramming Languages:	 Python	 	\nMachine Learning:	 NLP,	 Regression, Clustering	, Classification	, Transformers, Seq2Seq, 	Dimensionality Reduction, 	\nNatural Language Processing, Topic 	Modelling, Q&amp;A System, Text Summarizer	, Computer vision	 etc	. 	\nGen AI	: , LLMs, Generative AI, ChatGPT, Prompt engineering, Langchain	, HuggingFace, LoRa, 	GPT models, LLAMA, 	\nCLAUDE, FAISS, RAG, Vector Databases, Pinecone, ChromaDB	 	\nTechnologies/Tools:	 Azure Mac	hine Learning	 Studio	, Tensor	flow	, T	orch, Keras	, openCV, 	OCR, pytesseract, 	NLTK, 	\nSpacy, R	egex, BeautifulSou	p, Statsmodel, TorchServe, AWS	 (Sagemaker, Bedrock, Athena, S3bucket)	, Docker, 	\nDatabricks	, Gitlab, GitHub 	etc	. 	\n \nEducation	: 	\nJP Institute of 	Engineering and Technology	 	\nBachelor of Science and Technology, 	 	\nComputer Science &amp; Engineering	 	\n2014 	&ndash; 2018', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-07-25 15:05:30', '2024-07-22 15:05:30', 0, NULL, NULL, '2024-07-21 18:25:06', 0),
(437, 103, 76, NULL, NULL, '76_103_29131285669d5282a7195_Resume_Ankit_w2_12th-June_(1).pdf', 'Resume_Ankit_w2_12th-June (1).pdf', 'Ankit \nChand	 	\n09438669636\nchand07ankit@gmail.com	 	\nhttps://www.linkedin.com/in/ankitchand007/	 	\nData Scientist with 	3 years	 of hands	-on experience in 	developing	 and 	deploying	 data	-driven solutions to solve complex business 	\nproblems. 	 	\n* Good experience in 	Python	 for 	data analysis, machine learning	, and 	automation	. Skilled in using 	libraries	 such as 	Pandas, 	\nNumPy, Scikit	-Learn, TensorFlow	, and 	PyTorch	. 	\n* Proficient in 	developing 	various types of 	models	, including 	regression, classification, clustering	, and 	deep learning models	.  	\n* Experienced in 	model selection	, hyperparameter tuning	, and 	performance evaluation	. 	\n* Expert in 	exploratory data analysis	 (EDA), feature engineering	, and 	data visualization	 techniques.	 	\n* Excellent 	communication skills	 for collaborating with cross	-functional teams and presenting results to stakeholders.	 	\nProfessional 	Experience	 	\n09	/202	2 &ndash; present	 	\nRetisio India Pvt Ltd	, 	\nBengaluru, IN 	 	\n \n 	\nData Scientist	 	\nClient: 	AllenBrothers	 - Designed and implemented a 	Recommendation Engine	 (RxE	) to	 recommend 	\nmost relevant items to particular user based on their interests in E	-commerce	 	\n* Analysed	 historical sales data, customer reviews, and ratings to identify trends and opportunities for 	\nimprovement.	 	\n* Incorporated 	features	 such as product ID, category, brand, price, description, and technical 	\nspecifications to enrich product listings.	 	\n* Implemented a 	recommendation engine	 leveraging anonymized customer purchase history and 	\nbrowsing behaviour. 	 	\n* Utilized data on product returns and 	exchanges to identify potential quality issues and optimize 	\ninventory management.	 	\n \nRETISIO Intelligent Search 	- To build a product that will identify and provide relevant search results	 	\n* Developed to 	automate	 the updating catalogue specific keywords and entity of ner dictionary.	 	\n* Developed 	search intent identification	 for price, product, type, and category.	 	\n* Integrated	 script for 	multitency support	 (as site1 and site2)	 	\n \nLearning to Rank for E	-Commerce Search 	- Developed Python script for managing features (likely 	 	\nsearch queries) in an Elasticsearch index.	 	\n- Load features as a feature set into an 	Elasticsearch index	. 	\n* Forged the 	Data preparation	 and 	preprocessing	 for model training	 	\n* Developed 	&amp; trained	 the model with 	fine	-tuned hyper parameters	 	\n \nData Scientist	 	\nClient: BrandsMart	 USA 	- Designed and implemented a Search Intelligence Tool (SIT) to improve search 	 	\nrelevancy for an e	-commerce website	 	\n* SIT employs 	machine learning models	, specifically a 	Conditional Random Field (CRF) model	, to 	 	\nidentify entities (brands, categories, subcategories) within a user&#039;s search query.	 	\n* The model undergoes two critical phases: 	training 	and 	inference	. During training, the model learns 	 	\nfrom 	labeled data	 to improve its prediction accuracy. The inference phase utilizes the trained model to 	 	\nanalyze 	user queries and assign relevant labels	. 	\nEnhancement	: Identified 	missing data points	 in NER dictionary and unigram.txt. Developed a process 	\nto update missing display names, brand names, model codes, and SKU codes.	 	\n* Maintained 	data quality	 by filtering noisy data (e.g., &quot;808&quot; in brand names). Addressed model code 	 	\nauto	-correction issues by manually editing unigram and skipping for symspell files.	 	\n* Implemented a recurring update process (every 2	-3 months) to ensure data freshness.	 	\n* Streamlined data comparison	 by sorting model codes based on length and filtering numeric/float 	 	\ndata.	 	\n* Optimized 	SymSpell usage by balancing number of edits and frequency for better auto	-correction.	 	\n \n 	\nProfile Summary	 	\n 	\n  \n  	\n 	\n09/2021 	&ndash; 09/2022	 	\nAIE Software	 India Pvt 	\nLtd	, Bengaluru, IN\n\nSkills       	 	\nLanguage 	- Python, SQL, PySpark	 	\nFrameworks &amp; Databases 	- Flask, PostgreSQL, MySQL	 	\nDevelopment Tools and Services 	- Gitlab, Jupyter Notebook, PyCharm, Visual studio, Postman	 	\nCloud Platforms 	- GCP [ Big Query, Dataproc, Google App Engine, Google Cloud Storage, Cloud Composer 	\n(Airflow) and Logging]	 	\nEducation	 	\nPost Graduate Diploma in Data Science	 	\n03/2020 	- 04/2021 &bull; IIIT Bangalore &amp; upGrad	 	\nI have learned Statistics, Machine Learning, and Deep Learning, and Many other aspects of Data Science which \nare required to grow as an expert in this field. Secured 2.96 / 4.00	 	\n \nB. Tech Mechanical Engineering	 	\n08/2013	-07/2017 &bull; Lovely Professional University	 	\nJalandhar, Punjab	 	\nI have done my Majors in Mechanics such as Dynamics of Machines and Mechanisms. I have done my Minors \nin Reading of Contemporary Fiction which included Social, Love, and Life Moral Values. Secured 61.83%.	 	\nI Participated in International Go	-kart Championship (IGC) in LPU and secured Forth Place. LPU always gave a 	\ncompetitive spirit of participating in events.	 	\nLanguages	 	 	English,	 Hindi	 and 	Odia', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 18:25:06', 0),
(438, 103, 76, NULL, NULL, '76_103_856725183669d5282a73ca_Rithiks_Resume.pdf', 'Rithik\'s Resume.pdf', 'Rithik Mathur	 	\nConatct No: 9462437371, 	8740880055	 Email Id	: rithikmathur97@gmail.com	 	\nGithub Id: 	https://github.com/Rithikmathur	 	\nExperience	 	\n \nPiSquare	 	 	 	 	 	 	 	 	Bengaluru, Karnataka, India	 	\nMachine Learning 	Engineer	 	 	 	 	 	 	01/2022	-presen	t 	\n 	HR Management System	 	\nI have designed and created a 	system	 which	 uses machine learni	ng algorithms for the	 probability	 	\nprediction	 of  a  person  to  stay  in  a  company,  predicting  is  sur	vival  probabilities	 and  graph	 based 	\non their fe	atures such as location, region, achievements, hikes, etc. for different companies.	 	\n 	Research	 	\nI am  also  re	searching  some  Gen  AI  models  for  different  application  purposes	, models  s	uch  as 	\nGPT	-4, and as latest as 	Llama 2	. 	\nAvinex Softwares Pvt. L	td.                                                              	                       	Jaipur, India	 	\nData Scientist	                                                                           	                              	03/2020	-05/2021                    	 	\n 	Ridge Regression	 	\nI  have  done 	Outlier  Detection  using  Statistical  Methods 	and 	PYOD	 Library	 and  sklearn  Library 	\nand after cleanup imputation is done using libraries such as sklearn, fancy impute, auto impute in \nthe dataset and then perform a ridge regressio	n on this model.	 	\n 	Document Extraction	 	\nI have extracted m	ultiple documents for different formats such as PDFs, Eml, Xlsx, Xlsm, Docx, 	\netc. Extracted from the 500,000 emails.	 	\n 	Content Extraction	 	\nIt  was  We	b  Scrapping  process  to  execute	 NLP(Natural  Language  Proc	essing)  Pipeline.  I  have 	\ndone  content  extraction  from  the  Wikipedia  using  Wikipedia  Library  and  clean  it  up  using 	nltk 	\nand regex and then create	 solr core for it.	 	\nAxis India Machine Learning Lab	 	Jaipur, India	 	\nMachine Learning Intern	 	05/2019	-01/2020	 	\nAIML is a leading institution for artificial intelligence &amp; machine learning mentor 	by Mr Jaskirat Singh	 	\n 	Learning  and  working  with  Probability  and  Statistics,  Linear  Algebra,  Convex  Optimization, \nMachine  Learning  and  Deep  Learning  algorithms.  Developed  sev	eral  algorithms  from  scratch 	\nwith deep understanding of the math behind.	 	\nEducation	 	  \nJECRC University 	(Bachelor of Technology in Computer Science)	                      	           	CGPA 8.10/10	 	\n \nSkills	 	\n \nPROGRAMMING LANGUAGES: 	Python	 	\nSOFTWARE: 	Jupyter	 Notebook, Microsoft Office	, Visual	 Studio	 Code	, Pycharm	 	\nSKILLS:	- Machine 	Learning	(Supervised  Learning,  Unsupervised  Learning)	,  Deep  Learning,  NLP, 	\nTransformers, Attention Mechanism, BERT, LLMs, Docker, Git, T	ensorflow, Keras, Pytorch, Kedro, DVC	, 	\nLlama Index, RAG	 	\n \nProjects	 	  	 	\n 	Blog Generation Using LLM Llama 2	 	\n 	Question Answering System	 	\n 	Multivariate	 Na&iuml;ve 	Bayes	 Classifier	 on	 Devanagari	 Dataset	 from	 Scratch	 	\n 	For more, kindly visit my github id.', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 18:25:06', 0),
(439, 103, 76, NULL, NULL, '76_103_1108534484669d5282a75b0_Roshan_AI3.pdf', 'Roshan_AI3.pdf', 'Rosh an	\nAI/M L E ngin eer	\nro sh an .y a d av2 8 12 97@ gm ail. c o m	 	96 430 37 771	 	G uru gra m , I n dia	 	\nh ttp s:/ /w ww.li n ked in .c o m /in /r o sh an -y a d av/	 	\nP R O FIL E\nAI/M L E ngin eer w it h  3  y e a rs  o f e x p erie n ce  i n  i n te rp re tin g a n d a n aly z in g d ata  t o  f u el c o rp ora te  g ro w th .	 	\nP ro fic ie n t i n  b u ild in g r o b u st m ach in e l e a rn in g m od els  t h at p ro vid e v a lu ab le  i n sig h ts  e n ab li n g d ata -d riv e n	 	\nd ecis io n -m ak in g.\nP R O FE SSIO N AL E X PE R IE N CE\nAI/M L 	E ngin eer	\niO PE X  	Tech n olo g ie s 	P riv a te  	L im it e d	\n&bull;P erfo rm ed  D ata  V is u ali z a tio n , e x p lo ra to ry  d ata  a n aly sis  a n d s ta tis tic a l a n aly sis  t o	 	\ng en era te  i n sig h ts .	\n0 9/2 0 21 &ndash;  p re se n t\nG uru gra m , I n dia	\n&bull;P erfo rm ed  T ra in in g, H yp erp ara m ete r t u n in g, a n d M od el S ele ctio n .\n&bull;D eve lo p ed  a  c o m pre h en siv e  s e n tim en t a n aly sis  m od el u sin g T ra n sfo rm ers  f o r a	 	\nc li e n t b y a n aly z in g c u sto m er a n d a g en t c h at t r a n sc rip tio n s.\n&bull;W ork ed  a n d T ra in ed  C on vo lu tio n al N eu ra l N etw ork s(C N N) u sin g T en so rF lo w  a n d	 	\nN atu ra l L an gu ag e P ro ce ssin g ( N LP ) m od els .\n&bull;U pli f te d  a  M ach in e L ea rn in g i n te n t c la ssif ic a tio n  m od el a cc u ra cy  b y 1 0 % .\n&bull;Fin e-tu n ed  L L M (L la m a2 ) A I m od el f o r b u sin ess u se  c a se .\n&bull;C olla b ora te d  w it h  5 +  d ata  e n gin eers  t o  i m pro ve  t h e m od el p re d ic ta b ili t y .	\nJu n io r 	D eve lo p er 	(I n te rn )	\nVse r v  	In fo sy ste m s 	P riv a te  	L im it e d	\n&bull;D eve lo p, t e st, a n d m ain ta in  s c a la b le  P yth on  a p pli c a tio n s.	\n0 6/2 0 18  &ndash;  0 7/2 0 18	\nD elh i,	 I n dia	\n&bull;U tili z e P yth on  l i b ra rie s f o r e ffic ie n t a n d e ffe ctiv e  c o d e i m ple m en ta tio n .\n&bull;D esig n  a n d i m ple m en t R EST fu l A PIs  f o r s e a m le ss  c o m mun ic a tio n  b etw een	 	\nco m pon en ts .	\nS K IL L S\nEnd t o  E nd d ep lo ym en t |  D eep  L ea rn in g |  A uto m atio n  |  D ock er |  A PI ( F la sk , F astA PI) |  S Q L |  G IT  |  L O RA |\nM ach in e L ea rn in g A lg orit h m s(L in ea r R eg re ssio n ,L og is tic  R eg re ssio n ,D ecis io n  T re e,K -M ea n s C lu ste rin g) |\nP yth on (S cik it - le a rn , P an das, N um py) |  T en so rF lo w  |  L arg e L an gu ag e M od el( L L M ) |  L an gch ain  |  K afk a |\nC N N |  R N N |  T ra n sfo rm ers  |  N LP  |  N LT K  |  P yto rc h  |  W ord 2V ec |  B ER T |  V ecto r D ata b ase  |\nP R O JE C TS\nData In sig h ts  	- I n te n t 	a n d 	E ntit y  	R eco gn it io n  	M od el 	u sin g 	sp aC y	\nO bje ctiv e	: D eve lo p ed  a  n atu ra l l a n gu ag e p ro ce ssin g m od el u sin g s p aC y t o  r e co g n iz e i n te n t a n d e n tit ie s i n	 	\nt e x tu al d ata .	\n&bull;D ata  C olle ctio n  a n d A nnota tio n	: R ece iv e d  u n la b ele d  d ata  f r o m  t h e c li e n t. L ab ele d  t h e d ata  w it h  t h e h elp  o f	 	\nn er- a n nota to r.\n&bull;D ata  P re p ro ce ssin g	: C on du cte d  d ata  p re p ro ce ssin g l i k e r e m ovin g t h e s to p -w ord s, L em matiz a tio n  e tc .	\n&bull;M od el I n te g ra tio n	: T ra in ed  m od el( e n _co re _w eb _sm ) o n  o u r d ata  u sin g s p aC y a rc h it e ctu re  b y l o ad in g a  p re -	\ntr a in ed  E ngli s h  l a n gu ag e m od el p ro vid ed  b y s p aC y.\n&bull;T ra in in g a n d E va lu atio n	: T ra in ed  t h e m od el,  m on it o re d  t r a in in g p ro g re ss a n d o p tim iz ed  h yp erp ara m ete rs	 	\nto  a ch ie ve  o p tim al p erfo rm an ce .\n&bull;R esu lt s	: T he t r a in ed  m od el a cc u ra te ly  r e co g n iz ed  i n te n t a n d e n tit ie s i n  t e st d ata , w it h  a n  o ve ra ll a cc u ra cy  o f	 	\nove r 9 0 % .	\nEnvir o n m en t	 :  S pacy, P an das, F astA PI, D ock er, G IT	\n                                                                                                                                                               	r o sh an .y a d av2 8 12 97@ gm ail. c o m\n\nReg alA I 	- L arg e 	L an gu ag e 	M od el( L L M )	\n F in e-T u n ed  a n d i n te g ra te d  a  A rtif ic ia l I n te lli g en ce (A I) L arg e L an gu ag e M od el( L la m a-2 ) t h at c a n	 	\nh elp  i n  m ult ip le  b u sin ess r e q u ir e m en ts  a n d d eve lo p  a  q u estio n -a n sw erin g m od el.	\n&bull;D ata  P re p ara tio n :	 P re p are d  a  q u estio n -a n sw erin g d ata  a n d t h en  i n te g ra te d  i t  i n  t h e f o rm at o f p ro m pt	 	\nw hic h  L la m a-2  a cce p ts .\n&bull;M od el F in e-T un in g	: T ra in ed  t h e m od el u sin g S u perv is e d  F in e T u n in g(S FT ) w it h  t h e h elp  o f Q LoR A.	\n&bull;M od el E va lu atio n	: R evie w ed  t h e t r a in in g r e su lt s  i n  t h e T en so rb oard  a n d b y c h eck in g t h e o u tp u t b y	 	\np ro vid in g s a m ple  p ro m pts .	\nE nvir o n m en t	 :  L la m a2 , T ra n sfo rm ers, P eft, B it s a n dbyte s, D ock er, G IT	\nC hatS en tin el 	-  S en tim en t 	A naly sis  	fo r 	C usto m er 	C hat 	T ra n sc rip ts	\nO bje ctiv e	: D eve lo p ed  a  c o m pre h en siv e  s e n tim en t p re d ic tio n  m od el f o r a  p ro m in en t c li e n t b y a n aly z in g	 	\ncu sto m er a n d a g en t c h at t r a n sc rip tio n s. E m plo ye d  a d va n ce d  N atu ra l L an gu ag e P ro ce ssin g t e ch n iq u es t o	 	\na cc u ra te ly  c la ssif y  i n te ra ctio n s i n to  p osit iv e, n eu tr a l,  a n d n eg ativ e  s e n tim en ts .	\n&bull;D ata  G ath erin g	: E sta b li s h ed  a  r o b u st c o n nectio n  t o  t h e c li e n t&#039;s  M yS Q L d ata b ase , e x tr a ctin g c h at t r a n sc rip ts	 	\nfo r s e n tim en t a n aly sis .\n&bull;D ata  C le a n in g	: P erfo rm ed  T ex t C le a n in g, L ow erc a sin g, T o ken iz a tio n , S to p w ord  R em ova l,  S te m min g a n d	 	\nLem matiz a tio n , H an dli n g A bbre via tio n s, R em ovin g N on -T ex tu al c o n te n t, H an dli n g N ois e , E nco d in g	 	\nE m otic o n s a n d S ym bols .\n&bull;S en tim en t A naly sis	: I m ple m en te d  C hatS en tin el u sin g p re -tr a in ed  N LP  m od els (e .g ., R ob erta ) f o r a cc u ra te	 	\ns e n tim en t c la ssif ic a tio n .I f t h e i n pu ts  e x ce ed s 5 12  t o ken s, c re a te d  b atc h es o f 5 12  t o ken s a n d t h en  c o m bin ed	 	\nth e s c o re s t o  g et s e n tim en t.\n&bull;A PI D eve lo p m en t	: D esig n ed  a n d d ep lo ye d  C hatS en tin el,  a  h ig h -p erfo rm an ce  R EST fu l A PI, u sin g F astA PI.	\n&bull;C on ta in eriz a tio n	: D ock eriz ed  C hatS en tin el f o r p orta b le  d ep lo ym en t a n d s c a la b ili t y .	\nE nvir o n m en t	 :  P yth on , T ra n sfo rm ers (H uggin g f a ce ), F astA PI, D ock er, G IT	\nS u pportf ir st 	-  R etr ie va l- A ugm en te d  	G en era tio n  	(R AG ) 	f o r 	c u sto m er 	su pport	\nO bje ctiv e	 -  D eve lo p  a  c u sto m er s e rv ic e  c h atb ot t h at l e ve ra g es R etr ie va l- A ugm en te d  G en era tio n  ( R AG ) t o	 	\np ro vid e m ore  a cc u ra te , i n fo rm ativ e, a n d u p-to -d ate  a n sw ers  t o  c u sto m er i n qu ir ie s.	\n&bull;D ata  C olle ctio n  a n d P re p ro ce ssin g	 -  G ath er c u sto m er s e rv ic e  d ata  f r o m  v a rio u s s o u rc e s, s u ch  a s F A Q s,	 	\np ro d u ct m an uals , a n d p ast s u pport t ic k ets . P re p ro ce ss t h e d ata  b y c le a n in g a n d s tr u ctu rin g.\n&bull;L arg e L an gu ag e M od el ( L L M ) I n te g ra tio n	 -  C hoose  a n d i n te g ra te  a  p re -tr a in ed  L L M (L la m a2 ) i n to  t h e	 	\nsy ste m  u sin g b it s a n dbyte s t o  r e d u ce  m em ory  c o n su m ptio n  f o r i n fe re n ce .\n&bull;V ecto r D ata b ase  s e tu p 	- C hoose  a n d s e tu p a n  o p en -s o u rc e  v e cto r d ata b ase (c h ro m ad b) t o  s to re  a ll t h e d ata	 	\ne m bed din gs. E m bed ded  t h e d ata  u sin g S en te n ce -T ra n sfo rm er(a ll- M in iL M -L 12 -v 2 )\n&bull;R etr ie va l C om pon en t D eve lo p m en t	 -  D eve lo p ed  a  r e tr ie va l s y ste m  t h at c a n  e ffic ie n tly  s e a rc h  t h e	 	\npre p ro ce sse d  c u sto m er s e rv ic e  d ata  b ase d  o n  u se r q u erie s u sin g s e n te n ce  e m bed din g.\n&bull;R AG  I n te g ra tio n  a n d R esp on se  G en era tio n	 -  D eve lo p ed  a  p ip eli n e f o r t h e L L M  t o  i n te ra ct w it h  t h e r e tr ie va l	 	\nsy ste m  u sin g L an gC hain . T he L L M  p ro ce sse s t h e r e tr ie ve d  i n fo rm atio n  a lo n gsid e i t s  o w n k n ow le d ge t o	 	\ng en era te  a  c o m pre h en siv e  a n d i n fo rm ativ e  r e sp on se  t o  t h e u se r&#039;s  i n qu ir y.	\nE nvir o n m en t 	: L la m a2 , C hro m ad b, L an gC hain , T ra n sfo rm ers	\nE D UCATIO N\nBach elo r 	o f 	T ech n olo gy 	( B .T ech  	)	\nD ro n ach ary a  	C olle g e 	o f 	E ngin eerin g', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 18:25:06', 0),
(440, 103, 76, NULL, NULL, '76_103_178953194669d5282a7758_Shilpa_Shaw_Resume.pdf', 'Shilpa Shaw Resume.pdf', 'Shilpa   Shaw  \n \nData   Scientist   |   Data Analy st   |  Machine   Learning Engineer   | AI   Enthusiast  \n  +91 	- 9903369681\n 	 shilpashaw9681@gmail.com  	 LinkedIn  	 GitHub  	 \nPortfolio	 \n \n     SKILLS   AND   TOOLS  \n&bull;  \nProgramming &amp; Development:  Python, Scikit - Learn, TensorFlow, Keras, PyTorch, Transformers, Beautiful Soup, Librosa, EDA, ETL, \nPySpark, Matplotlib, Plotly, Open - CV, SQL, Flask, Docker, GitHub Action, Git    \n&bull;  \nData Science &amp; Al:   Deep Learning, Data Analysis, Pre dictive Modeling, Artificial Intelligence, Statistical Modeling, Data Visualization, Time \nSeries Analysis, Cloud Machine Learning (AWS), NLP, Prompt Engineering, Generative Al, LangChain, LLama, LLMs.  \n&bull;  \nData Analysis &amp; Visualization:   MS SQL (SSMS), MS Excel   ( Pivot tables   &amp;  Pivot Charts ) , Power BI   (DAX) , IBM SPSS  \n&bull;  \nDeveloper Tools:   Github, VScode, Jupyter, Colab, pip, Docker, HuggingFace, Jenkins, OpenAI GPT - 3.5  \n&bull;  \nSoft Skills:   Analytical skills, Effective Communication, Collaboration, Team Building, data - driven de cision - making, problem - solving, Curiosity    \nWORK   EXPERIENCE      \nData   Scientist / Machine learning  intern   |   Vlippr   Jan   &#039;24  \n-   Present  \n&bull;   Audio Database Management &amp; Analysis : Proficient in managing and analyzing audio databases with GCP Console and YouTube Data  API \nv3, integrated with SSMS for comprehensive data handling.  \n&bull;   NLP &amp; Text - to - Speech Expertise : Advanced experience in deploying large language models like Whisper, X - TTS, MetaVoice, and Wav2Vec \nfor text - to - speech tasks, achieving up to 90% accuracy through  meticulous fine - tuning.  \n&bull;   Speech Processing &amp; AI Dubbing : Adept in speech - to - text processing using Wav2Letter, with a focus on feature extraction for style and tone, \nachieving 95% accuracy. Skilled in enhancing AI - powered multilingual dubbing, significantly  improving production workflows and reducing \ntime - to - market.      \nData   Scientist   Intern   |   Intellipaat   Apr   &#039;23  \n-   Dec   &#039;23  \n&bull;   Data Science Collaboration : Engaged in data operations, including collection, cleaning, and preprocessing, leveraging Python, SQL, MS \nExcel, and Power BI to support team objectives.  \n&bull;   Dashboard Migration &amp; Enhancement : Executed the migration and feature enhancement of merchandising dashboards, focusing on data \nintegration and improvement using DAX for optimal performance.      \nResearcher  |   Writerbay   Aug   &#039;21  \n-   Dec   &#039;23  \n&bull;   Recognizes the importance of research data management as a fundamental aspect of resource management across various domains, \ncontributing to the overall efficiency and success of research projects.  \n&bull;   Created extensive projects  and assignments centered around statistical concepts, harnessing the power of Microsoft tools and IBM SPSS.      \nResearch Data management  |   Royal   Research   Jan   &#039;1 8  \n-   Sep   &#039;21  \n&bull;   Expert in crafting data organization and storage strategies for quantitative and  qualitative research   throughout the project&rsquo;s duration.   \n&bull;   Adept at applying statistical inference with SPSS, NVivo, and RStudio for comprehensive primary and secondary analysis.  \n    \nPROJECTS      \nBoston House Pricing Prediction:  End to End Machine Learning Project Implementation with Dockers, GitHub Actions and Deployment.   \nFinetune LLM models:  Fine - tuned llama2 model with custom dataset using PEFT, LORA, QLORA via quantization and calibration to get 90% accuracy.    \nSpearheaded a  comprehensive Cricket Data Analytics Project : Employed Web Scraping techniques to extract T20 World Cup data from ESPN Cricinfo, \nfollowed by data cleansing and analysis using Python and Pandas, culminating in insightful visualizations with Power BI.  \nMusic  Store Data base   Analysis : Facilitated   the   analysis   using SQL to  help the store understand its business growth  strategies   by 50% at EOY.    \nCredit Card Financial Dashboard : To develop a comprehensive credit card weekly dashboard that provides real - time  insights into key performance \nmetrics and trends, enabling stakeholders to monitor and analyze credit card operations effectively.  \nWalmart   Sales   Forecasting :  Forecasted   sales   for   the   next   12   weeks   using   predictive   modeling   techniques using ARIMA, SARIMA  time   series   model.  \nRVC (Retrieval - based Voice Conversion) model - based LLM project : Created a speech - to - speech translation of data using the RVC v2 model for voice \ncloning and transformed AI voice   obtaining 95% accuracy in audio output   with cloned voice .  \nAT S Friendly resume:   Leveraged Google Gemini Pro Vision LIM Model to enhance resume analysis, aligning with job descriptions and providing \nactionable improvement suggestions, resulting in a 25% increase in interview callbacks for job seekers.  \nEnd - to - End Adva nced RAG Project : Llama2 and Mistral integrated with Groq&#039;s high - performance inferencing engine to enhance real - time AI response.    \n \nEDUCATION   AND   CERTIFICATIONS  \n&bull;   PGP   (Post Graduation Program)   in   Data   Science   and   Machine   Learning   ( SQL   &amp;   Python )   |   Intellipaat   |   Dec   2023  \n&bull;   Machine   Learning   with   Python:   MITxMicroMasters/IDSS   |   MIT   -   Massachusetts   Institute   of   Technology   |   Dec   202 3  \n&bull;   B.Tech   in   Electronics   and   Communications   Engineering   (ECE)   |   MAKAUT   (WBUT)   |   Aug   2013   -   Jul   2017  \n&bull;   Generative AI with Large  Language Models | DeepLearning.AI, AWS | Coursera | March 2024  \n&bull;   Microsoft   Azure   Data   Scientist   Associate   (DP - 100)   Professional   |   Coursera   and   Microsoft   |   Feb   2024   -   Present  \n&bull;   British   Airways ,  Boston   Consulting   Group , BCG   &ndash;   DS   &amp; Gen AI   Job   Simulation   |   Forage   |   2024', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 18:25:06', 0),
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(442, 103, 76, NULL, NULL, '76_103_220491248669d5282a7abc_Sivakumar_DL_CV.pdf', 'Sivakumar_DL_CV.pdf', 'Siv a k u m ar R	\nD ata  A naly st	\nsiv ak u m ar.r s e k ara n @ gm ail.c o m	 	+918220825229	 	B an galo re	 	lin ked in .c o m /in /s iv a-k u m ar- 2 5a3 b 1227	 	\nP R O FIL E	\nD eta il- o rie n te d  d ata  a n aly st w it h  a  B .T ech  i n  B io in fo rm atic s.  P ro fic ie n t i n  d ata b ase  m an ag em en t a n d s k ille d  i n  v ario u s\npro gra m min g la n gu ag es,  in clu din g P yth on ,  M yS Q L,  a n d B ase  S A S.  E xp erie n ce d  in  m ach in e le a rn in g,  d eep  le a rn in g,\nd ata  a n aly sis ,  q u alit y  a ssu ra n ce ,  a n d p ro d u cin g e n d-u se r d ocu m en ta tio n .  P artic u la rly  a d ep t a t l e v e ra g in g P ow er B I f o r\nd ata   vis u aliz a tio n   an d  cra ft in g  co m pellin g  narra tiv e s  fo r  m ed ic a l  co n fe re n ce s.  Su cce ssfu lly   dev e lo p ed   m ult ip le\nm ach in e  le a rn in g  an d  deep   le a rn in g  alg o rit h m s  fo r  re g re ssio n   an d  cla ssif ic a tio n   ta sk s,  w it h   a  fo cu s  on   te x t\ncla ssif ic a tio n ,  m ach in e t r a n sla tio n ,  a n d im ag e c la ssif ic a tio n  in  o n co lo gy d is e a se s,  a s d em on str a te d  in  p ro je cts  f o r o u r\npro d u ct F erm a.A I.	\nP R O FE SSIO N AL E X PER IE N CE	\nExce lR  	EdT ech  	Priv a te  	L im it e d	\nD ata  	A naly st\n&bull;L ed  t h e d ev e lo p m en t o f a  p re d ic tiv e  m od el u sin g m ach in e l e a rn in g t o  f o re ca st	 	\nc u sto m er c h urn ,  r e su lt in g i n  a  1 5%  i m pro ve m en t i n  r e te n tio n  r a te s.	\nM ar&nbsp;2 023 &ndash;  p re se n t	\nB an galo re ,	 I n dia	\n&bull;A uto m ate d  d ata  e x tr a ctio n  t a sk s b y s tr e a m lin in g p ro ce sse s w it h  P yth on  a n d S Q L,	 	\nach ie v in g a  w eek ly  t im e s a v in gs o f 1 5 h ou rs .\n&bull;U tiliz e d  P ow er B I t o  v is u aliz e  c o m ple x  d ata ,  f a cilit a tin g e a sie r i n te rp re ta tio n  a n d	 	\nin fo rm ed  d ecis io n -m ak in g b y t h e m an ag em en t.	\nO rb it h ru st 	C on su lt in g 	P riv a te  	L im it e d	\nA sso cia te  	D ata  	A naly st	\n&bull;C on du cte d  m etic u lo u s d ata  e x tr a ctio n  a n d m in in g o f c lin ic a l d ata  f r o m	 	\nC lin ic a lT ria ls .g o v,  e n su rin g c o m pre h en siv e  d ata  c o ve ra g e.	\nJa n &nbsp;2 022 &ndash;  F eb &nbsp;2 023	\nC hen nai,	 I n dia	\n&bull;E xecu te d  a  t h oro u gh  q u alit y  c h eck  o n  t h e a n aly ze d  d ata  b y c ra ft in g a  c o h ere n t	 	\nsto ry lin e a n d o rg an iz in g i n sig h ts  t h ro u gh  e ffe ctiv e  b u ck etin g.\n&bull;P re p are d  d eta ile d  d ocu m en ta tio n  o u tlin in g t h e s to ry lin e f o r m ed ic a l c o n fe re n ce s,	 	\nfa cilit a tin g t h e d is se m in atio n  o f k ey  f in din gs a n d i n sig h ts  t o  s ta keh old ers .\n&bull;U tiliz e d  R N N a n d C N N m od els  t o  p erfo rm  t e x t c la ssif ic a tio n ,  i m ag e c la ssif ic a tio n  a n d	 	\nm ach in e t r a n sla tio n  o n  o n co lo gy r e la te d  i m ag es a n d s ta te m en ts ,  e n han cin g t h e	 	\nca p ab ilit ie s o f o u r p ro d u ct F erm a.A I i n  u n ders ta n din g a n d p ro ce ssin g m ed ic a l d ata .	\nB io n iv id  	T ech n olo gy	\nD ata  	A naly st 	I n te rn	\nP erfo rm ed  d ata  a n aly sis  o n  N GS u sin g M S e x ce l,  f a stq c,  c u ta d ap t,  f a stp ,  b ow tie ,	 	\nsa m to ols ,  b cft o ols , V EP	\nM ay&nbsp;2 021 &ndash;  N ov&nbsp;2 021	\nB an galo re ,	 I n dia	\nP R O JE C T S	\nAI/M L 	P ro je cts	\n&bull;D ev e lo p ed  m ult ip le  c h atb ots  u tiliz in g n eu ra l n etw ork s a n d N LP  l ib ra rie s s u ch  a s N LT K ,  G en sim ,  a n d o th ers ,	 	\nsh ow ca sin g p ro fic ie n cy  i n  A I- d riv e n  c o n ve rs a tio n al s y ste m s.\n&bull;C re a te d  i m ag e d ete ctio n  a lg o rit h m  u sin g O pen cv.\n&bull;C re a te d  t e x t c la ssif ic a tio n  u sin g p re  t r a in ed  B ER T  m od el.\n&bull;I m ple m en te d  i m ag e c la ssif ic a tio n  u sin g t r a n sfe r l e a rn in g o n  t h e R esN et m od u le ,  s h ow ca sin g a n  i n novativ e	 	\na p pro ach  t o  l e v e ra g in g p re -tr a in ed  m od els  f o r i m pro ve d  p erfo rm an ce .\n&bull;C re a te d  a  l o gis tic  r e g re ssio n  m od el t o  d ia b etic s d is e a se  w it h  8 7%  a cc u ra cy.\n&bull;C re a te d  a  d ecis io n  t r e e a n d r a n dom  f o re st m od el f o r l e n din g c lu b l o an  p re d ic tio n .	\nS K IL LS	\nPyth on (P an das,  N um py,S ea b o rn ,	 	\nSkle a rn ,T en so rflo w	 	\nN LT K ,P yto rc h ,O pen C V )\nM ach in e  L ea rn in g(D ecis io n  T re e,	 	\nL o gis tic  R eg re ssio n ,  S V M ,  K	 	\nm ea n s,  C lu ste rin g,	 	\nR eco m men datio n  S yste m  e tc )	\nO OPS\nSQ L	\nCN N,  L ST M ,  B ER T,  C BO W ,	 	\nSK IP G RA M ,  Y O LO ,  G AN ,  F o u rie r	 	\nT ra n sfo rm er,  G LO VE\nPow er B I,  B ase  S A S', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 18:25:06', 0),
(443, 103, 76, NULL, NULL, '76_103_1962274146669d5282a7c59_Varun_Achar_M_N_GenAI.pdf', 'Varun_Achar_M_N_GenAI.pdf', 'VARUN ACHAR M N	 	\nvarunachar91@gmail.com	 | https://www.linkedin.com/in/varun	-achar	-m-n/ | https://github.com/hayavar	 | Ph: +918105918846	 	\n 	\nProfile	 Summary	 	\nHighly motivated and results	-driven 	professional	 with 	around 4	 years of experience in 	Robotic	 Process 	Automation (RPA) and 	\nGenerative AI, seeking to leverage expertise in automating business processes and building AI solutions to contribute to 	the	 company&#039;s 	\ngrowth and efficiency. Proven ability to identify, analyze, and automate tasks, collaborate with stakeholders, and deliver so	lutions that 	\nimprove productivity and reduce costs. Strong technical skills in RPA tools (Automation Anywhere, UiPath, K	ofax Kapow), 	\nGenerative AI platforms (LangChain), and Python. Eager to learn and contribute to innovative projec	ts in a fast	-paced environment	. 	\nProfessional Experience	  	\nSenior 	Associate Consultant (April 202	2 &ndash; Present)	 Infosys Ltd, Mysuru	, Karnataka.	 	\n&bull; 	Led the development of a hyper	-automation solution combining Generative AI, RPA (UiPath), and Python to streamline the 	\nprocesses in the BFSI, Manufacturing, and Healthcare industry.	 	\n&bull; 	Facilitated weekly conference calls with stakeholders in North America, APAC, and EMEA regions, providing operational \ninsights and fostering strong partnerships	. 	\n&bull; 	Developed state	-of-the	-art generative models using LangChain and Python to automate text generation tasks, resulting in a 	\n30% increase in content creation efficiency for clients in the BFSI sector	. 	\n&bull; 	Designed and implemented AI	-powered chatbots for customer service applications, enhancing user experience and reducing 	\nresponse times by 40%	. 	\n&bull; 	Fine	-tuned pre	-trained models to specific client datasets, significantly improving the relevance and accuracy of AI	-generated 	\ncontent and solutions.	 	\n&bull; 	Collaborated with data scientists and machine learning engineers to create end	-to-end AI solutions, including data 	\npreprocessing, model training, and deployment.	 	\n&bull; 	Conducted thorough research and experiments on transformer models and GPT architectures to improve the accuracy and \nperformance of AI applications.	 	\n&bull; 	Utilized Generative AI for automated testing of software products, creating realistic test scenarios and datasets that enhanc	ed 	\nthe efficiency and coverage of testing processes	 using techniques like RAG, CRAG 	and so on.	 	\n&bull; 	Integrated AI solutions with existing IT infrastructure using RESTful APIs, facilitating seamless adoption and integration fo	r 	\nclients.	 	\n&bull; 	Conducted rigorous testing and validation of AI models, ensuring high reliability and compliance with industry standards.	 	\n&bull; 	Led workshops and training sessions for internal teams on the implementation and benefits of Generative AI, fostering a \nculture of innovation.	 	\n&bull; 	Developed RPA solutions using UiPath and Automation Anywhere to automate various business processes, leading to a \nreduction in manual effort and processing time.	 	\n&bull; 	Created Proof of Concept (POC), System Design Document (SDD), Process Design Document (PDD), and flowcharts for \nprocess requirements, forming the foundation for successful process automation.	 	\nAssistant System Engineer (August 2020 	&ndash; April 2022)	 Tata Consultancy Services, Bengaluru, Karnataka.	 	\n&bull; 	Created Proof of 	Concept (POC), System Design Document (SDD), Process Design Document (PDD), and flowcharts for 	\nprocess requirements, forming the foundation for successful process automation.	 	\n&bull; 	Developed RPA bots using Automation Anywhere to automate resource	-intensive tasks for infrastructure monitoring, device 	\nhealth checks, and backup reporting.	 	\n&bull; 	Migrated robots from Automation Anywhere v11.3 to A360 to comply with new development standards and optimize \nefficiency.	 	\n&bull; 	Partnered with stakeholders to gather and refine requirements, evaluate process suitability for automation, and design optima	l 	\nworkflows.	 	\n&bull; 	Managed user access provisioning, bot deployments, license management, and infrastructure setup &amp; maintenance for \nAutomation Anywhere as an RPA Administrator.	 	\n&bull; 	Resolved production issues as a Problem Manager by investigating incidents, identifying root causes, collaborating with \nstakeholders for resolution, preventing recurrence, and documenting solutions for future reference.\n\nEducation	 	\n&bull; 	08/2016 	- 09/2020 8.98 CGPA (CS&amp;E) 	- P.E.S College of Engineering, Mandya, Karnataka, India.	 	\n&bull; 	06/2014 	- 03/2016 12th (II PUC) 	&ndash; 95 Percentile 	- Vijaya Vittala Composite P.U College	. 	\n&bull; 	05/2014 10th (CBSE) 9.0 CGPA 	- Maharshi Public School	, Mysuru.	 	\nSkills Matrix	 	\n&bull; 	RPA Tools 	&ndash; UiPath 	(Intermediate), Automation Anywhere (Proficient), Kofax Kapow (Intermediate)	 	\n&bull; 	Languages 	- Python	, HTML(Beginner), CSS(Beginner)	 	\n&bull; 	Database 	&ndash; SQL (Beginner), MongoDB (Beginner)	 	\n&bull; 	Cloud 	&ndash; Azure, Azure OpenAI Services	 	\n&bull; 	Agile Tools 	- ServiceNow	, Azure DevOps Board, Confluence	 	\n&bull; 	Frameworks 	&ndash; Agile, Scrum	, Waterfall	, ITSM	 	\n&bull; 	Technology 	&ndash; Generative AI, APIs, Microservices	, Flask	 	\n&bull; 	Design Tools 	- Figma, GIMP, Canva	 	\n&bull; 	Leadership 	- Project Management, Communication &amp; Collaboration,	 Problem	-Solving &amp; Decision	-Making	 	\n&bull; 	Industry Experience 	&ndash; BFSI, Manufacturing and Healthcare	 	\nCertifications	 	\n&bull; 	AZ 900 	- Microsoft Azure Fundamentals	 	\n&bull; 	Certified Business Analyst 	&ndash; Automation Anywhere	 	\n&bull; 	UiPath Certified Professional Automation Business Analyst Professional	 	\n&bull; 	Diploma 	&ndash; UiPath RPA Developer Foundation	  	\n&bull; 	Coursera Managing Talent 	- University of Michigan	 	\nHobbies:	 Cooking, Music, Badminton, Travelling', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-21 18:25:06', 0),
(444, 104, 1, NULL, NULL, '1_104_166189052669e035d62775_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', 0, 0, NULL, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-22 06:59:41', 0),
(445, 104, 1, NULL, NULL, '1_104_1815087197669e035d62f13_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', 0, 0, NULL, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-22 06:59:41', 0),
(446, 104, 1, NULL, NULL, '1_104_1272063015669e035d63168_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', 0, 0, NULL, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-22 06:59:41', 0),
(447, 104, 1, NULL, NULL, '1_104_1238480217669e035d635c1_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', 0, 0, NULL, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-22 06:59:41', 0),
(448, 105, 1, NULL, NULL, '1_105_1839314745669e035dccde4_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', 0, 0, NULL, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-22 06:59:41', 0),
(449, 106, 1, 4, NULL, '1_106_1949089133669e0360dbbee_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, '2024-09-22 11:34:14', '2024-09-19 11:34:14', 0, NULL, NULL, '2024-07-22 06:59:44', 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
(450, 106, 1, 4, NULL, '1_106_1666907836669e0360dc15a_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, 0, '2024-07-25 07:51:14', '2024-07-22 07:51:14', 0, NULL, NULL, '2024-07-22 06:59:44', 0),
(451, 106, 1, 4, NULL, '1_106_801164583669e0360dc35b_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, '2024-07-25 07:51:59', '2024-07-22 07:51:59', 0, NULL, NULL, '2024-07-22 06:59:44', 0),
(452, 106, 1, 4, NULL, '1_106_1564251179669e0360dc771_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, '2024-07-25 07:52:44', '2024-07-22 07:52:44', 0, NULL, NULL, '2024-07-22 06:59:44', 0),
(453, 107, 76, 48, 15, '76_107_48_2027986868669f7783c2764_Sivakumar-R-DL-Latest.pdf', 'Sivakumar-R-DL-Latest.pdf', 'Siv a k u m ar R	\nD ata  A naly st	\nsiv ak u m ar.r s e k ara n @ gm ail.c o m	 	+918220825229	 	B an galo re	 	lin ked in .c o m /in /s iv a-k u m ar- 2 5a3 b 1227	 	\nP R O FIL E	\nD eta il- o rie n te d  d ata  a n aly st w it h  a  B .T ech  i n  B io in fo rm atic s.  P ro fic ie n t i n  d ata b ase  m an ag em en t a n d s k ille d  i n  v ario u s\npro gra m min g la n gu ag es,  in clu din g P yth on ,  M yS Q L,  a n d B ase  S A S.  E xp erie n ce d  in  m ach in e le a rn in g,  d eep  le a rn in g,\nd ata  a n aly sis ,  q u alit y  a ssu ra n ce ,  a n d p ro d u cin g e n d-u se r d ocu m en ta tio n .  P artic u la rly  a d ep t a t l e v e ra g in g P ow er B I f o r\nd ata   vis u aliz a tio n   an d  cra ft in g  co m pellin g  narra tiv e s  fo r  m ed ic a l  co n fe re n ce s.  Su cce ssfu lly   dev e lo p ed   m ult ip le\nm ach in e  le a rn in g  an d  deep   le a rn in g  alg o rit h m s  fo r  re g re ssio n   an d  cla ssif ic a tio n   ta sk s,  w it h   a  fo cu s  on   te x t\ncla ssif ic a tio n ,  m ach in e t r a n sla tio n ,  a n d im ag e c la ssif ic a tio n  in  o n co lo gy d is e a se s,  a s d em on str a te d  in  p ro je cts  f o r o u r\npro d u ct F erm a.A I.	\nP R O FE SSIO N AL E X PER IE N CE	\nExce lR  	EdT ech  	Priv a te  	L im it e d	\nD ata  	A naly st\n•L ed  t h e d ev e lo p m en t o f a  p re d ic tiv e  m od el u sin g m ach in e l e a rn in g t o  f o re ca st	 	\nc u sto m er c h urn ,  r e su lt in g i n  a  1 5%  i m pro ve m en t i n  r e te n tio n  r a te s.	\nM ar 2 023 –  p re se n t	\nB an galo re ,	 I n dia	\n•A uto m ate d  d ata  e x tr a ctio n  t a sk s b y s tr e a m lin in g p ro ce sse s w it h  P yth on  a n d S Q L,	 	\nach ie v in g a  w eek ly  t im e s a v in gs o f 1 5 h ou rs .\n•U tiliz e d  P ow er B I t o  v is u aliz e  c o m ple x  d ata ,  f a cilit a tin g e a sie r i n te rp re ta tio n  a n d	 	\nin fo rm ed  d ecis io n -m ak in g b y t h e m an ag em en t.	\nO rb it h ru st 	C on su lt in g 	P riv a te  	L im it e d	\nA sso cia te  	D ata  	A naly st	\n•C on du cte d  m etic u lo u s d ata  e x tr a ctio n  a n d m in in g o f c lin ic a l d ata  f r o m	 	\nC lin ic a lT ria ls .g o v,  e n su rin g c o m pre h en siv e  d ata  c o ve ra g e.	\nJa n  2 022 –  F eb  2 023	\nC hen nai,	 I n dia	\n•E xecu te d  a  t h oro u gh  q u alit y  c h eck  o n  t h e a n aly ze d  d ata  b y c ra ft in g a  c o h ere n t	 	\nsto ry lin e a n d o rg an iz in g i n sig h ts  t h ro u gh  e ffe ctiv e  b u ck etin g.\n•P re p are d  d eta ile d  d ocu m en ta tio n  o u tlin in g t h e s to ry lin e f o r m ed ic a l c o n fe re n ce s,	 	\nfa cilit a tin g t h e d is se m in atio n  o f k ey  f in din gs a n d i n sig h ts  t o  s ta keh old ers .\n•D ev e lo p ed  c u sto m  Q & A c h atb ot F erm a.A I u sin g l a n gch ain  f r a m ew ork  w it h  a d van ce d	 	\nR AG  a p plic a tio n .	\nB io n iv id  	T ech n olo gy	\nD ata  	A naly st 	I n te rn	\nP erfo rm ed  d ata  a n aly sis  o n  N GS u sin g M S e x ce l,  f a stq c,  c u ta d ap t,  f a stp ,  b ow tie ,	 	\nsa m to ols ,  b cft o ols , V EP	\nM ay 2 021 –  N ov 2 021	\nB an galo re ,	 I n dia	\nP R O JE C T S	\nAI/M L 	P ro je cts	\n•D ev e lo p ed  m ult ip le  c u sto m  Q & A c h atb ot u sin g b oth  O pen A I a n d o p en  s o u rc e  m od els  ( G PT,L L A M A 2 ,L L A M A 3 ,	 	\nM is tr a l) .\n•C re a te d  e n d-to -e n d R AG  p ro je ct w it h  O lla m a a n d O pen  A I A PI k ey  u tiliz in g V ecto r D B s u ch  a s C hro m aD B,  F A IS S,	 	\nA str a D B .\n•C re a te d  t e x t c la ssif ic a tio n  u sin g p re  t r a in ed  B ER T  m od el.\n•I m ple m en te d  i m ag e c la ssif ic a tio n  u sin g t r a n sfe r l e a rn in g o n  t h e R esN et m od u le ,  s h ow ca sin g a n  i n novativ e	 	\na p pro ach  t o  l e v e ra g in g p re -tr a in ed  m od els  f o r i m pro ve d  p erfo rm an ce .\n•C re a te d  a  l o gis tic  r e sg re ssio n  m od el t o  d ia b etic s d is e a se  w it h  8 7%  a cc u ra cy.\n•C re a te d  a  S V M  a n d r a n dom  f o re st m od el f o r l e n din g c lu b l o an  p re d ic tio n .	\nS K IL LS	\nPyth on (P an das,  N um py,S ea b o rn ,	 	\nSkle a rn ,T en so rflo w	 	\nN LT K ,P yto rc h ,O pen C V )\nM ach in e  L ea rn in g(D ecis io n  T re e,	 	\nL o gis tic  R eg re ssio n ,  S V M ,  K	 	\nm ea n s,  C lu ste rin g,	 	\nR eco m men datio n  S yste m  e tc )	\nO OPS\nSQ L	\nCN N,  L ST M ,  B ER T,  C BO W ,	 	\nSK IP G RA M ,  Y O LO ,  G AN ,  F o u rie r	 	\nT ra n sfo rm er,  G LO VE,  R AG ,	 	\nLan gch ain ,L LA M A I N DEX\nPow er B I,  B ase  S A S	\nE D UCA T IO N	\nKaru n ya  	In stit u te  	o f 	T ech n olo gy 	a n d 	Scie n ce s	\nB .T ech  	B io in fo rm atic s	\nJu n  2 017 –  M ay 2 021	\nC oim bato re ,	 I n dia', 2, 2, 1, 'Candidate', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-23 09:27:31', 48),
(454, 108, 76, 49, 16, '76_108_49_11878669266a24e95ee27f_Amit_Jain_Data_Science_Resume_2024.pdf', 'Amit_Jain_Data_Science_Resume_2024.pdf', 'Public	 	\n                	 	\n \n \n     	     	 	\n \n \n \n \n \nPROFILE SUMMARY	 	     	        	PROFESSIONAL EXPERIENCE	 	\n 	\n• 	6.5+  YoE	 	in  Data  Science  roles  across 	\nindustries.	 	\n• 	Thorough  understanding  of  Data  Science \ntools, techniques and technologies in Machine \nLearning,	 Deep  Learning,  Natural  Language 	\nProcessing	 	(NLP)	 	Using	 	Python,  R	 	\nprogramming.	 	\n• 	Thorough  understanding  of  algorithms  like \nRegression, 	Classification,	 	Clustering, 	\nForecasting,  Anomaly  Detection,	 Time  series 	\nModelling etc.	 	\n• 	Sound  knowledge  of  deployment  using  Git, \nDocker, Jenkins, 	Kubernetes, OpenShift	. 	\n• 	Sound knowledge of Azure Machine Learning \nStudio,  AWS  (Amazon  Web  Services)  AI	-ML 	\nServices.	 	\n• 	Extract	ed	 usable  data  from  valuable  data 	\nsources	. 	\n• 	Carr	ied	 out  preprocessing  of  structured  and 	\nunstructured data	. 	\n• 	Analyz	ed	 large amounts of information to find 	\npatterns and solutions.	 	\n• 	Developed  prediction  systems  and  machine \nlearning algorithms.	 	\n• 	Propose	d solutions  and  strategies  to  tackle 	\nbusiness challenges.	 	\n 	\n   	\n• 	Total 1	4+ 	YoE	. 	\n• 	6.5+	 YoE	 in Analytics, Machine Learning, Data 	\nScience.	 	\n• 	7.8 YoE	 in Academics.	 	\n 	\n      	DATA SCIENTIST	 	\n• 	Data Scientist at 	Wipro	, Pune Since 	Mar	 202	2 – 	\nTill date	 	\n• 	Data  Scientist  at  Equations  Work  IT  Services \nPvt. Ltd., Pune Since Sept 2020 	to Feb 2022	 	\n• 	Data Scientist at Cloudmantra, Pune since Mar \n2020 to Sept 2020	 	\n• 	Data Scientist at Open Insights, Pune since Aug \n2019 to Feb 2020.	 	\n• 	Data  Scientist  at  TorcAI  Digital  Media  Private \nLimited, Pune since Feb 2019 to Jul 2019	 	\n• 	Data  Analyst  at  Findability  Sciences, \nAurangabad since Jan 2018 to Jan 2019.	 	\n       	 	\n      	ACADEMICS	 	\n• 	7.8+  YoE	 Teaching 	experience  as  assistant 	\nprofessor  in  engineering  colleges  since  Aug \n2009 to Mar 2017	 	\n 	\nEDUCATIONAL QUALIFICATION	 	     	PROGRAMMING SKILLS & TOOLS	 	\n 	\n• 	PGP	-2018	 	in  Data  Science,  Business 	\nAnalytics & Big Data in association with IBM	 	\nfrom  Aegis  School  o	f Data  Science	, Cyber	 	\nSecurity	 & Tele	communicati	on	,  Mumbai 	\n(M.H.)	 	\n• 	M.Tech.	-2014	 from  university:  B.U.  Bhopal 	\n(M.P.) with 73%	 	\n• 	PGDIT	-2008	 	from  Indian  Institute  of 	\nTechnology,  Kharagpur  (W.B.)  with  6.67 \nCGPA.	 	\n• 	B.E.	-2006	 from  University:  R.G.P.V.  Bhopal 	\n(M.P.) with 73.16%	 	\n 	\n• 	Programming Language:	 Python	, R Programming	 	\n• 	Software Tools/Technologies:	 Machine Learning, 	\nDeep  Learning,  Natural  Language  Processing \n(NLP), AWS 	AI-ML, Azure 	Machine Learning	 	\n• 	Databases:	 MySQL, PostgreSQL	, Db2	 	\n• 	Operating System:	 Windows, Linux/Unix	 	\n• 	Authoring Tools:	 Microsoft Office, Open Office	 	\n• 	BI Tools/ Data Reporting 	Tool:	 Qlik Sense	 	\n• 	Version Control:	 GIT	 	\n• 	Model Deployment Tool:	 Heroku, AWS, Azure	 	\n• 	Cloud platform:	 IBM	, AWS, Azure	, GCP	 	\n• 	Project 	M	anagement 	Too	l: Jira, 	GitHub	 	\n 	\nAmit Jain	 	\nData Scientist	 	\n  amitjain2110@gmail.com	 	\nlinkedin.com/in/amit	-jain	-83292740/	 	\n  youTube/amit	-jain	 	\n  github.com/amitjain2110	 	\n 917	9982256\n\nPublic	 	\nWIPRO	 PROJECTS	:   	 	 	 	 	 	 	 	Mar 2022 	– Till 	date	 	\n \nProject Title: 	Space Insights	 	\nProject Profile: 	To Build AI model to predict about Ideal sharing ratio	. 	\nRoles & Responsibility: 	 	\na. Analysis to build a machine learning model for Ideal sharing ratio.	 	\nTools/Technologies used:	 Python, 	IBM Maximo 	Application Suite	 	\n \nProject Title: 	Tririga Building	 Insights	 	\nProject Profile: 	To Build AI model for 	TBI.	 	\nRoles & Responsibility: 	 	\n    	a. 	Create Anomaly detection model and other AI models for 	OpenShift	 Platform (OCP)	 	\n    	b.  	Successful transition of project from Kubernetes to 	OpenShift	 Platform	 in IBM Cloud	 	\n    	c.     	PostgreSQL to Db2 migration  	 	\n    	d.  	Installation of modules like IoT, cp4d(WML), 	Monitor etc.	 	\n    	e.  	Responsible to run security Scan (Static, Dynamic, 	white source	, mend, PVR, 	twist lock	) 	\n Tools/Technologies used: 	Python, Machine Learning, IBM Maximo 	Application Suite	, IBM 	Cloud,	 Openshift	  	\n        	Cluster, 	Kubernetes	 	\n \nEQUATIONS WORK PROJECTS:	    	 	 	 	 	 	Sept 2020 to Feb 2022	 	\n \nProject Title:	 Sales forecasting and Demand Forecasting	 	\nProject Profile:	 To forecast the sales and revenue of e	-commerce company.	 	\nRoles & Responsibility: 	 	\na. Build the model using LSTM Time Series	 Modelling.	 	\nTools/Technologies used:	 Python, Azure 	Machine Learning	 	\n \nProject Title:	 Prediction of Motor Speed & temperature 	 	\nProject Profile:	 To predict the temperature and deployed it using Power platform.	 	\nRoles & Responsibility: 	 	\n    	a.  	End to end model creation & deployment	 	\n    	b.  	Build the model using 	Random Forest	 regression	 and XGBoost 	regression.	 	\n    	c.  	Enabled to run the project in Azure Power Platform.	 	\nTools/Technologies used:	 Python, Azure Machine	 Learning Studio, Power App, Power Automate	 	\n \nProject Title:	 Prediction /Analysis of Horse Race	 	\nProject Profile: 	 	\na. To predict which horse will win the race.	 Also, 	decide	 the position of all the horses.	 	\nRoles & Responsibility: 	 	\na. 	Responsible for prediction 	of result 	using 	Random 	Forest	 classification	, XGBoost	 classification	 and ANN 	    	\nclassification	 model.	 	\n    	b.  	Requirement collection from client.	 	\n    	c.  	Schedule and planning for project execution. 	 	\nTools/Technologies used:	 Python, Machine 	Learning	 	\n \nProject Title:	 Text summarization of audit files	 	\nProject Profile:	 To read text from 	audit 	reports	(pdf	) and	 summari	ze	 text	 report	. 	\nRoles & Responsibility: 	 	\n    	a. 	Responsible for text extraction	 using AWS Textract 	and summarization	 using BERT	 library	. 	\n    	b.  	 Requirement collection and deployment.	 	\nTools/Technologies 	used:	 Python, NLP, A	mazon	 Machine 	Learning, AWS Textract, 	Amazon S3, 	Git, Docker, 	  	\n       	Jenkins\n\nPublic	 	\nCLOUDMATRA	 PROJECTS	:  	 	 	 	 	 	 	Mar 2020 to Sept 2020	 	\n \nProject Title:	 Specific text extraction of audit reports 	 	\nProject Profile	: To extract specific text and its related	 data with units from audit reports and publish & analyze	. 	\nRoles & Responsibility: 	 	\n   a. 	Responsible for text extraction using AWS	 Textract	. 	\n   b. 	Discussion with project planning team	 	\nTools/Technologies used:	 Python, NLP, A	mazon 	Machine 	Learning	, A	mazon	 SageMaker, AWS Textract, A	mazon	   	\n       	Comprehend	 	\n \nOPEN INSIGHTS	 PROJECTS	:  	 	 	 	 	 	 	Aug 2019 to Feb 2020	 	\n \nProject Title:	 BIFE 	- Banking Intension Fulfillment	 Engine (CLTV Module)	 	\nProject Profile:	 To predict customer lifetime value,	 the amount of revenues that you expect to generate	 from a 	  	\n  customer during the period over which	 your service will be of value. 	 	\nRoles & Responsibility:	 	\n    	a. 	Responsible for developing software.	 	\n    	b. 	Wrote 	down test cases for checking the	 functionality of various functions.	 	\nTools/Technologies used:	 Python, Machine 	Learning	 	\n \nTORCAI	 PROJECTS	:  	 	 	 	 	 	 	 	 	Feb 2019 to Jul 2019	 	\n \nProject Title:	 Zirca Campaign	 	\nProject Profile:	 To collect advertiser campaign	 information based on 	distinctive features	 performance to predict 	  	\n                         	and	 recommend	 blacklist & whitelist values.	 	\nRoles & Responsibility: 	 	\na. Responsible for collecting	 data 	using Spark 	and 	analysis	 data using keywords and 	based on	 result create 	\nblacklisted and whitelisted features	. 	\nTools/Technologies used	: Spark, Scala	 	\n \nFINDABILITY SCIENCES	 PROJECTS	: 	 	 	 	 	 	Jan 2018 to Jan 2019	 	\n \nProject Title:	 Ajinomoto Price prediction	 	\nProject Profile:	  To predict the price of product	 after every week, after 1 month, 	after 2 months and after 3 	  	\n                           	months	 value.	 	\nRoles & Responsibility: 	 	\na. Build the model using 	Linear, 	Random Forest	 regression 	and XGBoost regression.	 	\nb. Responsible for EDA, deliver insights and	 prediction result.	 	\nTools/Technologies used:	 R - Programming	, Machine 	Learning	 	\n \nProject Title:	 Net promotor score 	 	\nProject Profile:	 Classification of user sentiment for various telecom plans. 	 	\nRoles & Responsibility: 	 	\na. 	Build the model using 	Logistics regression, 	Random Forest	 classification	 and 	Naïve Bayes	 classification.	 	\nb. 	Responsible for predicting classification report.	 	\nc. 	Responsible for EDA, deliver insights and prediction result.	 	\nTools/Technologies used:	 R - Programming	, Machine Learning', 2, 2, 1, 'Candidate', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-25 13:09:42', 49);
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
(455, 108, 76, 51, 17, '76_108_51_28999818966a25e5e82b60_CV_Architect__Amol_Naik.pdf', 'CV_Architect__Amol_Naik.pdf', 'Resume of Amol	 	 	Page 	1 of 	9 	\n                    	         	           	             	       	               	\n 	\n 	\nAMOL	 HIRAMA	N NAIK	 	\nFLAT NO 	403	 BLDG	 TULIP 	ADITYA 	GARDEN CITY 	PHASE 	5  PUNE CITY 	PUNE 	(CB)	  411058	 	\n Mob: 	9356997358 	Email	: amolhiramannaik	@gmail	.com	 	\n \nEXECUTIVE 	PROFILE	. 	\n 	Around	 17 years of 	experience in	  Designing 	Web,	 Win	dow 	and Cloud Native 	Applications	. 	\n 	7+  years of  experience in  Solution architecture  and 	developing 	End  to  End 	complex  Single	-Page  Responsiv	e 	\nWeb Applications	 	\n 	7+ years of experience in designing, implementation a	nd architecting the cloud solution	-AWS,GCP,Azure	 	\n 	6+  years  of  experience  using  AWS,  ideally including  comfort  with  the  majority  of  the  following  services  (or \nequivalent):  EC2,  S3,  CloudFront,  Lambda,  IAM,  Route  53,  ECR,  ECS, 	EKS,	CodeBuild,  CodeDeploy, 	\nCodeP	ipeline, SNS, CloudWatch	,Datadog,AWS Neptune,AWS Control Tower	 	\n 	7+ years of rich experience in 	UI 	Architect	ing Scalable, Secure 	Web solutions	. 	\n 	9+ years 	of  experience  as  Full  stack  developer  in  building  web  App 	UI  Design, 	Micro  Frontends  using 	\nAngular2/4	/6	/8	/10	,AngularMaterial,	JavaScript	,HTML	5,ReactJS,	MongoDB,	Cassandra,	Microservices	,Spring	\nBoot,NestJS	,.Net Core 3.0	 	\n 	5+ years of client 	facing 	experience worked	 on 	cross	-functional	 teams for resolving various functional issues 	\nand gathering appropriate requirement	s.  	\n 	3+ years of working experience on Developing Window Applications using WPF with MVVM	 Pattern	 	\n 	Support	ed 	the  business  development  lifecycle  (Business  Development,  Capture,  Solution  Architect,  Pricing 	\nand Proposal Development)	 	\n 	Strong  knowledge  of  Amazon  K	inesis,  AWS  Lambda,  Amazon  Simple  Queue  Service  (Amazon  SQS), 	\nAmazon Simple Notification Service (A	mazon SNS),EC2,S	ssss	3,Bucket,ALB.	 	\n 	Strong knowledge with Web Services, API Gateways and application integration development and design	. 	\n 	 GCP Knowledge of Clou	d Function,Google Kubernetes Engine(GKE),Cloud Pub/Sub,Cloud Load Balancing	 	\n 	Skilled 	in Code Optimization, Review,	 Perfor	mance Tuning for web application	 and SQL	 server 	 Database	 	\n 	 Implementation  of  design  patterns  such  as  Singleton, 	Factory,  Abstract	 Factor	y,  Command	,  Adapter	,  	\nObserver 	in .Net	 	\n 	 Implementation of Software Design Principle, SOLID Principles	 	\n 	Worked on Dependency Injection for code refactoring and loose coupling	 	\n 	 Extensively used core 	.Net technologies like 	LINQ, SOAP Web Services, WCF	 	\n 	 Extensi	vely used Microsoft Tools like Enterprise Library, Entity Framework, etc	 	\n 	 Experience in writing Reporting 	Services	 Rendering, Delivery and Data Source Extensions	 	\n 	 Experience  in  providing  Proposals,  Estimations  (Task  Ba	sed  and  Function  Point)  for  New 	Develo	pment, 	 	\nReengineering and Sustained Engineering projects	 	\n 	 Well  versed  with  complete  Software  Development  Life  Cycle  (SDLC)  process  which  includes	 Design, 	\nConstruction, Testing and Deployment	 	\n 	 Created UI Library using	 Angular Material and Storybook	 componen	t Library.	 	\n 	Proficient 	knowledge in SSO,	 Saml,	 OpenIDConnect, OAuth 2.0	 	\n 	Experienced in working on RFP	 and 	Presales	 	\n 	Worked  with  DevOps  tools  Jenkins  for  Continuous  Integ	ration, 	Deployment,  JIRA	 for  project  Management 	\nand Confluence for 	keeping project	 relate	d documents.	 	\n 	Worked with testing tools framework Jasmine, Karma and Protractor	 	\n 	Worked with 	IIS and .Net Assemblies	 during application deployment.	 	\n 	Profound knowledge in working with 	RD	BMS includes MS SQL Server 2012	\\2008	, Oracle	11g	 	\n 	Excellent skills in writi	ng 	stored 	procedures, T	-SQL 	Queries, 	functions, triggers, views	 and schemas.	 	\n 	Good Experience with Unified Modeling Language(UML) standards and documentation and experience	 	\nIn preparing 	Class 	Diagrams, Sequence	 Diagrams using	 design tools 	such as Microsoft 	Visio.\n\nResume of Amol	 	 	Page 	2 of 	9 	\n 	Performed  Unit  Testing  using  tool  NUnit 	and	 performed  several  integration 	testing,  System	 testing  and 	\nperformance testing.	 	\n 	Strong  analytical  and  dynamic  trouble  shooting  skills coupled  with  excellent  communication  skills  and  able \nto work individuall	y and as a team.	 	\n 	Basic knowledge of Generative AI(Currently attending classes on Generative AI with Great Learning)	 	\nCERTIFICATION	 	\n 	\n 	TOGAF 9(Combined Level 1 & 2) Certified Professional	 	\n 	Google Professional Cloud Architect	 	\n 	AWS  Certified Solutions Architect	-Associate	 	\n 	Microsoft Certified: Azure Solution Architect Expert	 	\n 	SAFe 4.0 Agile Certified Professional	 	\n 	Microsoft Certified: Azure AI 900 Fundamentals	 	\n 	Generative AI for Business with MSFT Azure Open AI Program	 	\n 	\nORGANIZATIONAL EX	PERIENCE	 	\n6 Jan 2022 to till date	          	T-Systems as	 Senior Technical Architect.	 	\nApril 2021	 to 	4 Jan 2022	     	HCL Technologies 	as Senior Technical Architect	 	\nMay 2019 to 29 Jan 	2021 	   Western	 Union	 Technology 	Engineering as	 Solution Architect.	 	\nMay 17 to 	April 2019	       	  Infosys, Pune	 as Technology Architect	 	\nNov’11 	 - May 17	 	Tata 	Consultancy	 Services, Pune as Assistant Consultant	 	\nSep’10 	– Nov’11	  	Syntel Ltd., Pune as Analyst Programmer	 	\nJul’08 	– Aug’10	  	Acidaes Solutions Pvt. Ltd., Mumbai as Engineer 	- Application Development Group	 	\nJan’	08 	– Jul’08	 	 	Orion India Systems Pvt. Ltd., Mumbai as Software Developer	 	\nApr’07 	– Jan’08	  	IL & FS Education & Technolo	gy, Mumbai as Software Developer	 	\n \n \nCAREER 	FOCUS	 	\n 	Enterprise  application  |  Solution  Architect  |  Cloud  Migration  |Digital  Transformation  |  M	icroservices  | 	\nStrategic  Planning &  Execution  |  Leadership  & Team  Building  |Customer  Relationship  | Generative  AI  for \nBusiness	 	\nTECHNICAL 	SKILL 	SET 	\n \nProgramming Languages	 	C#,JAVA, Typescript	 	\nJavaScript  Framework  & \nLibrary	 	\nAngular	 14, NodeJS	,Javascript, Boo	tstrap	,ReactJS,Angular	Material,	 	\nStorybook UI Component 	library, Web Component	,SpringBoot	,NestJS	 	\nDatabase	 & No SQL DB	 	SQL Server 2012	\\2008	,Oracle11g	,MongoDB	,Casandara	 	\nMiddleware	 	Microservices	,Kafka	,RabbitMQ	,Springboot	,Python	,Micronaut	 	\nBuild  Packaging  Too	l 	and 	\nFramework	 	WIX 3.7	,MSBuild	,Angular CLI,Gulp	 	\nModeling 	 and Design Tools	 	UML,MS Visio	,Enterprise Architect	 	\nTestingTools Management and \nFramework	 	NUnit	,Jasmine,Karma,Protractor	,SonarQube,Resharper,HP ALM	 	\nVersion Control Tools	 	MS Visual Source Safe(VSS	),SVN,TFS	,Perforce,JIRA	,Github	 	\nDimension	 	\nCloud 	 Computing	 	\nAWS	EC2,RDS,S3,Glacier,SQS,SNS,VPC,CloudFormation,IAM,Route53	\n,EBS,Lambda,Kinesis,API  Gateway,ALB	 GCP	-Cloud  Function,Google 	\nKubernetes  Engine(GKE)  Cloud  Pub/Sub,Cloud  Load \nBalancing.	Azure	 Event Hubs,	API Management,Storage,Queues,	 	\nSecurity	,AWS Datadog,AWS Neptune,AWS Control Tower	 	\nOperating System	 	Win 95/98/NT/XP	 /Win 2003	/Win 2007	 	\nDevOps 	 	Jenkins, 	JIRA	, Docker	, Kubernetes	,OpenStack\n\nResume of Amol	 	 	Page 	3 of 	9 	\n \n \n \nPROJECTS 	EXECUTED 	 	 	\n \nT-Systems as Senior Technical Architect	 	\nDuration: January 2022 to Till Date	 	\nProject: LogisticBus: The LogisticBus is a system used 	Daimler	 for supplying parts of vehicles to Retailer.	 	\nLogisticBus  systems  consists  of  Modules  like  Dealer  Inventory  Management  Systems,  Stock  Information  and \nControll	ing 	Systems	. When	 retailer, systems, places the order	 checks if the part is availab	le with wholesaler.	 	\nAbout  90%  parts  ordered  by  retailer  are  available  with  corresponding  wholesaler.  This  is  possible  due  to \napplication such as systems demands and Forecast	 applications. But if it is not available with wholesaler then the 	\nrequest goes to central warehouse and retailer is informed after how many days his demand will be fulfilled	 	\n 	Responsible for delivering architecture guidelines for LogisticBus Modernization 	Application.	 	\n 	Le	d development team in 	Modernization	/Transformation 	LogisticBus	 legacy Application.	 	\n 	Involved 	in 	the 	requirement gathering m	eetings with Product owner. 	 	\n 	Created the Micro services Orchestration layer for 	retailer order, Transferring order deta	ils to other systems.	 	\n 	Worked with the UX designer in designing the wireframes like lending page with the main components.	 	\n 	Design, both technically compliant and secure Cloud solutions, as well as value	-based, on	-demand services to 	\nfacilitate the effective 	transition and migration of projects and p	rograms into 	unique 	cloud	 environment	. 	\n 	Design and implemented AWS Simple S	torage Services to store sales inventory information.	 	\n 	Worked with the EC2 instances to host the 	Micro services	 and the Application.	 	\n 	Involved	 in creating the VPC used cloud Formation Template	 	\n 	Used the Hystrix Library to implement the circuit pattern for 	Micro services	. 	\n 	Implemented the AWS API Gateway for 	Authorization, caching	 and storing the  REST API  Response.	 	\n 	Involved in exploring the cloud	 agnostic architecture AWS,Azure and GCP	 	\n 	Involved 	in Deploying	, Monitoring and Hosting of the 	Micro service	. 	\n 	Used Angular Material	 to design	 and build up a multi 	layered System	. 	\n 	Used Sonar Qube to 	monitor	 the Code Quality Metrices.	 	\n 	Involved in code review 	and approve the Pull Request	 	\n 	Led the deployment of  the code builds and helping in continuous integration and deployment.	 	\n 	Used JIRA, Remedy to create user stories ,is	sues, plan.	 	\n 	Involved in creating the Database Model	. 	\nEnvironment: 	Visual Studio Code, 	AWS 	Cloud.	Angular	 12, Typescript,HTML5, 	\nCSS,JIRA,,AngularC	LI,Angular Material PostgreSQL,	Kafka,Amazon Web 	\nservices,Docker,Gitlab,NodeJS,Java,SpringBoot	,Kubernetes,	IntellijIDEA,	 	\n \nHCL Technologies as Senior Technical Architect	 	\nDuration	 April 2021	 to January	 2022	 	\nProject:  Working on a project to 	enhance	 secured password system for a US based client	. 	\nEnvironment: 	C#	, Web	 Services	, WPF, SQL	 Server	 	\n \nWestern 	Union, Pune	 	\nDuration: 	May 2019	 to 29 Jan 2021	 	\nProject:	 iWatch	,RTRA,Transvision  applications  are  involved  in 	case  management  application  that	 provides 	\ncompliance officers, 	investigators and  analysts  the  ability  to  create 	and/or  review information  about	 a  subject  or 	\ngroup of subjects for the purposes	 of investigation, assessment, 	and intelligence maintenance. iWatch	 was crea	ted 	\nin response to requirements 	from the Global Compliance organization and is intended to serve	 as a single “source 	\nof truth” 	for compliance activities globally includin	g those compliance user groups.	An iWatch case can be for any 	\nsubject such as 	an Agent, a consumer, a geography or a group/network of Agents and/or Consumers.	 	\nRTRA is a Real Time Risk Analysis application provides the details about the 	customers	. 	\nTransvision  is  a  read  only  web 	application  used	 by  the  Agents  to  monitor 	the  suspicious	 activity  on  the 	\ntransactions.	 	\n \nResponsibilities:	 	\n 	Responsible 	for delivering architecture	 guidelines	 for iWatch Modernization Application.	 	\n 	Le	d development	 team in 	Modernization	/Transformation iWatch	 legacy Application.	 	\n 	Involved 	in 	the 	requirement gathering	 meetings with 	Product owner	.  	\n 	Created the 	Micro services Orchestration	 layer for Case creation, Case bulk load, Case push ,Case search, 	\nCase Integration with other application.	 	\n 	Worked with the UX designer in designing the wireframes like lending page with	 the main components	.\n\nResume of Amol	 	 	Page 	4 of 	9 	\n 	Design, both technically compliant and secure Cloud solutions, as well as value	-based, on	-demand services to 	\nfacilitate the effective transition and migration of projects and p	rograms into unique 	 cloud environment	. 	\n 	Design	 and impleme	nted AWS Simple Storage Services to store and retrieve user specific kyc document	 	\n 	Worked with the EC2 instances to host 	the Microservices	 and the Application.	 	\n 	Involved in creating the VPC used cloud Formation Template	 	\n 	Used the Hystrix Library to implement 	the circuit pattern for Microservices.	 	\n 	Implemented the AWS API Gateway for Authorization,caching and storing the  REST API  Response.	 	\n 	Involved in exploring the cloud 	agnostic architecture 	AWS	,Azure and GCP	 	\n 	Involved in  Deploying, Monitoring and Hosting of 	the Microservice.	 	\n 	Used Angular Material	 to  design and build up a multi layered  System.	 	\n 	Used Sonar Qube to monitored the Code Quality Metrices.	 	\n 	Involved in code review and approve the Pull Request	 	\n 	Led the deployment of  the code builds and helping in cont	inuous integration and deployment.	 	\n 	Used JIRA, Remedy to create user stories ,is	sues, plan	. 	\n 	Involved in creating the Database Model	 	\n 	Created and maintained the confluence page for all project specific details like Project Architecture etc	 	\n 	Involved in the PI 	planning to select the MBI and grooming the team on same.	 	\nEnvironment: 	Visual Studio Code, Angular	 8, Typescript,	HTML5, CSS,JIRA,,AngularC	LI,Angular Material 	\n,Cassandra,Kafka,Ama	zon Web s	ervices,Docker,Gitlab,NodeJS,	Java,	SpringBoot	,Kubernetes,AWS	 & 	\nGCP	,SSO	,ASP.Net core 3.0	 	\n 	\nInfosys Ltd,Pune	 	\nClient: E.ON UK	(Worked at client location  Nottingham,UK from June 18 to Feb 19)	 	\nDuration: May  2018 to April 2019.	 	\nGSOS	-Guaranteed Standards of Service: These are the standards set by the E.ON and some of these are part	 of the 	\nobligations  set  for  energy  companies  by  Ofgem,  the  energy  industry  regulator.  Some  are  standards  that  the \nelectricity  distributors  and  gas  transporters,  who  make  up  the  distribution  network,  have  to  meet.  If  these \nstandards  doesn\'t  meet  then  electr	icity  distributor  or  gas transporter 	- will  pay  to  the  customer  subject  to certain 	\nexemption	 	\nResponsibilities:	 	\n 	Led in requirement gathering meetings with business customers.	 	\n 	Technical design including developing the component views of system	 	\n 	Design/Develop	ment of a new .Net Core Microservice to read Servicing data that invoked by the API.	 	\n 	Created MSMQ  to capture the customer transactions and support the developers in implementation of \ndesign wireframes.	 	\n 	Created the service layer which helps all developers/	 feature packs to utilize the APIs t	o be consumed in app	 	\n 	Created standardized API designing such that every  supplier uses its own RES	Tful API design	 	\n 	Involved in  Deploying, Monitoring and Hosting of the Microservice.	 	\n 	Used Angular Material	 to  design and b	uild up a multi layered  System.	 	\n 	Led the deployment of  the code builds and helping in continuous integration and deployment.	 	\n 	Used JIRA, Remedy to create user stories ,issues, plan sprints and to distribute tasks amongst team members.	 	\n 	Worked on the Advance	d queue on high volume transactional systems in Oracle.	 	\n 	Involved in DB Performance Optimization as well.	 	\nEnvironment: 	Visual Studio Code, Angular	4/6	, HTML5, CSS,JIRA,,	NodeJS,AWS,	AngularCLI,Angular 	\nMaterial ,Oracle 11g.	Azure	,ASP.Net core 2.0	 	\nInfosys Ltd,Pun	e 	\nClient: HSBC	 	\nDuration: May 	 2017 to March 2018	 	\nStaff  Frond  End  :  The  SFE  is  an  web  application  used  by  the  front  end  bank  employees  to  get/view  all  the \ncustomer related information like Customer overview, Customer Family ,Loan Repayment schedule and Loan	 	\nRepayment Holiday etc. 	 	\nResponsibilities:	 	\n 	Development and technology planni	ng and implementation 	– providing	 guidance in best practice and tool 	\nuse in the design and build of technical frameworks and the applications built on them and own and \nimplement co	mplex area of the UI systems.	 	\n 	Architecture and design 	- proposes & implements technical solutions, ensures their integrity, and that the 	\nsolutions can be built, implemented and maintained within timelines/budgets.	 	\n 	Technical design authority 	- internally re	cognized as a specialist in complex technical areas, will oversee 	\nbenchmarking, installation, upgrade, configuration, deployment, and testing activity.\n\nResume of Amol	 	 	Page 	5 of 	9 	\n 	Improves quality 	- investigates and prototypes innovative approaches to improve software quality.	Provide	 	\nStability 	- ensures development teams can develop in a stable and productive environment, with minimal 	\nrework required due to architectural change or related problems as products evolve.	 	\n 	Assisting Project Management in planning technical aspects of projec	ts. 	\n 	Providing regular updates on project status and risks.	 	\n 	Supporting and mentoring individual developers and ensure the team is positive & motivated.	 	\n 	Performing detailed technical reviews to ensure the overall design is being implemented.	 	\n 	Full stack	 Web F	ramework development experience.	 	\n 	Demonstrable detailed understanding of architecture principles and methods, technology, and standards.	 	\n 	Utilizing 	research	 and self	-learning to ensure technical credibility.	 	\n 	Work	ing	 with UI Designer to provide feasibility di	rections and lead UI development team.	 	\n 	Possess	ing 	good	 analytical, communication & interpersonal skill.	 	\n 	Hands on experience in responsive designs  (Bootstrap, Telerik or any other framework)	 	\n 	Participated in meetings with Business users and with other proje	ct means to ensure that the volatile	 	\n business requirements reflecting the project dev	elopment.	 	\n 	Contributing 	to the implementation of User Stories	 	\n 	Participating 	in SCRUM process	 	\n 	Fulfilling 	the acceptance criteria with the contributed code 	(quality, unit te	sts e	tc.)	 	\n 	Adherence to architecture, design and quality guidelines	 	\n 	Maintenance, problem analysis and bug fixing within the 	application	 	\n 	Technical clarifications with other team members	 	\nEnvirionment: 	Visual 	Studio Code, 	\nAngular	,HTML5,CSS,GitHub	,JIRA	,Jenkins,	Protractor,	NodeJS,AWS,	AngularCLI	,OAuth2.0	, ,ASP.Net core 2.0	 	\n 	\nTata Consultancy Services,	 Pune	 	\nClient:NBS Bank	 	\nDuration	:Nov  2015 to March 2017	(Worked at client location Swindon,UK	 from 	Nov 2015 to Nov 2016	) 	\nThe  Nucleus  is  a  web  application that  will  enable	 the  user  to  carry out  account  and customer  related  back  office 	\nservices on the accounts stored in SAP.Nucleus consists of a number of back office services which can be invoked  \neither  from  the  Nucleus  application  or  externally	 from  other  applications  by  p	assing  appropriate  data  to 	\nNucleus.The  external  applications  can  either  invoke  the  Nucleus  application  as  a  whole  or  a  specific  Nucleus \nprocess.In  both  the  cases  the  external  application  needs  to  pass  appropriate  data  confirming  to    a  pre 	defined 	\ninterface	.Nucleus  also  contains  links  to  other  many 	applications.  The	 data  that  is  available  within  Nucleus	 is 	\npassed to 	these external systems	 using the interface.	 	\nResponsibilities:	 	\n 	Develops software solutions by studying information needs; conferring with users; 	Studying systems flow, 	\ndata usage, and work processes; investigating problem areas; Following the software development lifecycle.	 	\n 	Develop features across multiple subsystems within our applications, including collaboration in requirements \ndefinition, proto	typing, design, coding, testing and deployment.	 	\n 	Documents and demonstrates solutions by developing documentation (HLD, LLD), flowcharts, layouts, \nssss	diagrams, charts, code comments and clear code.	 	\n 	Design,  develop  and  maintain  the  Database  Schema,  Entity  r	elationship  diagrams,  Data  modeling,  Tables, 	\nStored procedures, Functions and Triggers, Constraints, Indexes, Schemas, Functions, Views, Rules, Defaults \nand complex SQL statements. 	 	\n 	Maintain a technical understanding of a component or sub	-component within 	an application / product, 	\nproviding support for technical queries, live incidents and problems. 	 	\n 	To ensure that the technical integrity and quality of the applications / products is maintained across their \nlifetime, contributing to the development of any t	echnical changes being proposed. 	 	\n 	To build knowledge of how technical strategies are defined to provide business solutions.	 	\n 	Review Technical Feasibility Studies for projects that impact applications / products within domain, and \nassess potential impact.	 	\n 	So	lve software	-related problems, providing analysis and recommendations as appropriate. 	 	\n 	Develop an awareness of new tools, processes and technical developments relevant to component area of \nexpertise.	 	\n 	Understand emerging software development methods, tools 	and standards. Look for ways to apply as 	\nappropriate	 	\n 	Provide input to end	-to-end system technical designs that involve applications / products within domain, 	\ncollaborating with other internal and supplier teams as required.	 	\n 	Understand the various phases of	 the software development lifecycle.	 	\n 	Undertake impact assessment of change requests against applications / products within domain.\n\nResume of Amol	 	 	Page 	6 of 	9 	\n 	Review test strategies to guarantee the quality of the delivered software assist in the diagnosis of system \nproblems encounte	red during testing. 	 	\n 	Collaborate with other members across teams to build technical solution. 	 	\n 	Define architecture, R&D on new technologies	 	\n 	Make the framework up	-to date based on new technology or new way to implement the software solutions.	 	\n 	Documenting st	andard features, guide to integrate framework features, user manuals, versions etc.	 	\n 	Create deliverables (Packages, Configurations) using IT Strategy approved build tools (Team foundation \nservers) and standards, ensuring they meet all specific install polic	ies defined for the system.	 	\n 	Maintained the source	-code repository, developed multi	-platform product installers and developed scripts 	\nfor builds and source code automation.	 	\n 	Co	-ordination with the Technical Project Managers, Software Developers, Testers, App	lication Support, SAs 	\nand DBAs for any Deployment and Change across environments.	 	\n 	Developed and managed testing and roll	-out project plans for software releases, desktop updates and server 	\nimplementations.	 	\n 	Designing and creating the web services using WCF 	and SQL Server 2010.	 	\n 	Designing the application by using the different design pattern like creation pattern (Factory design pattern, \nMVC, Abstract Factory, and Singleton) and structural pattern (Adapter, Facade etc.).	 	\n 	Complete assignment work to budget, tim	e and quality requirements. Document all work in accordance with 	\nagreed standards, and with re	-use in mind	 	\n 	Involved in Project planning, Resource utilization & Timeline estimations.	 	\n 	Estimating the tasks based on functional requirement and assign the work t	o team	 	\n 	Managed the  offshore and onshore team.	 	\nEnvirionment: 	C#,Visual Studio 2015	, WCF,	SQL Server,,AngularJS,NodeJS	,SAML	 	\n 	\nTata Consultancy Services,Pune	 	\n Client:DNB Bank	 	\nDuration	:Jan2014 to Oct 2015	 	 	\nDescription:	 DLA  (DNB  Loan  Administration)  application  i	s  used  for  Administration  of  Currency  Loan  as 	\nwell  as  tailor  made  loans  in  NOK.  DLA  is  applicable  for  large  corporate 	customer 	and  limited  group  of 	\nprivate customers (Multi Currency Loans only).	 	\n 	Zenit  Workflow  interacts  with  different  rule  engines  and  syst	ems    and  the  offer  letter  to  the  customer   	\ngenerated for the customer mentioning limit and terms and condition. DLA loan is offered to very limited \nspecial customers only, so most of the terms and condition negotiated between loan officer and customer \nout	side the system over the counter.	 	\n 	Large  Corporate:  For  large  corporate  &  International  Customer,  ASAP!LC  takes  care  of  the  Credit \nProcess.  As  the large  corporate  customers involve  high value  loans,  most  of  the  agreement  has  been  set \noutside the box between	 the lawyers of customer and DNB. Details agreement prepared based on various 	\nnegotiation factors like limit, collateral, margins etc. A Credit process can be initiated in ASAP!LC for an \nexisting customer or may be for a new customer.	 	\n 	After  Credit  process 	done  and  finalization  of  the  agreement,  A  Decision  have  been  have  been  taken  to 	\ngrant  the  loan  and  Limit  have  been  decided.  After  negotiation  of  agreement  have  been  over,  a  request \nhave been sent to DLA users through mail to open a loan project in the DLA 	system.	 	\n 	For  a  DLA  Loan collateral is  being  saved  to  Felix  Depot by  the  collateral  department  and  the  Collateral \nDepartment gives the final sign off and send the agreement to DLA department for further processing.	 	\n 	After  receiving  the  credit  decision,  DLA  Ap	plication  users  open  a  new  DLA  loan  project  using  the 	\nCustomer details provided in the agreement. 	 	 	 	 	\n 	After  Credit  process  done  and  finalization  of  the  agreement,  A  Decision  have  been  have  been  taken  to \ngrant  the  loan  and  Limit  have  been  decided.  After  neg	otiation  of  agreement  have  been  over,  a  request 	\nhave been sent to DLA users through mail to open a loan project in the DLA system.	 	\n 	For  a  DLA  Loan collateral is  being  saved  to  Felix  Depot by  the  collateral  department  and  the  Collateral \nDepartment gives the 	final sign off and send the agreement to DLA department for further processing.	 	\n 	After  receiving  the  credit  decision,  DLA  Application  users  open  a  new  DLA  loan  project  using  the \nCustomer details provided in the agreement. 	 	\n 	From DLA client after creation  of 	the DLA  project  there  is  a limit  have  been  entered  for  customer  based 	\non  the  limit  set  in  the  Credit  Process.  This  DLA  limit  is  used  for  reference  and  warning  purpose  only, \nDLA limit will be changed manually based on revision of the limit from Credit Depar	tment	 	\n 	After creation project a Single Loan or Limit	-Tranche Facility have been created through DLA client and 	\nthe amount getting disbursed as per the agreement.	 	\n 	After creation of project and loan it sends information to Felix exposure.	 	\n 	Loan  disbursement  is	 a  manual  process  in  DLA.  DLA  user  need  to  disburse  the  loan  to  the  customer 	\naccount. In case of non DNB customer Disbursement will be done through a internal Global Account.\n\nResume of Amol	 	 	Page 	7 of 	9 	\nResposibilities:	 	\n 	Participated in meetings with Business users and with other pro	ject means to ensure that the volatile	 	\n      	business requirements reflecting the project 	development. Application	 development was developed was 	 	\n      	based on UML methodology.	 	\n 	Involved in the design of the Use Case Diagrams and class diagrams using Micro	soft Visio.	 	\n 	Reworked on a part of the GUI to improve interface without affecting the performance of the application.	 	\n 	Used C# as language to develop code behind business logic	 	\n 	Used C# for middle tier business logic and implementation of Web Services	 	\n 	Followe	d the MVVM design 	pattern, separating	 the 	business, presentation	 and data models.	 	\n 	Performed the conversions of existing VB Applications into WPF application.	 	\n 	Designed the WPF GUI for accessing product 	details, Comparisons	 and Client details.	 	\n 	Developed User	 Interface(UI) using WPF for the better look and feel of the Window based application.	 	\n 	Wrote Stored 	Procedures, Triggers	 and SQL Queries and LINQ in SQL Server 2008.	 	\n 	Developed and consumed WCF Web Service to access data layer components	 	\n 	Involved in Impleme	ntation of Exception handling on User Interface layer.	 	\n 	Created test cases and did basic manual testing.	 	\n 	Used TFS as a central repository and source code control.	 	\n 	Mapping the business requirement to the technical specification and detail design documents.	 	\n. 	\nEnvirionment: 	C#,Visual Studi	o 2012	, WCF,WPF,S	QL Server,Entity 	Framework., Angular	 JS,MVC.	 	\nTata Consultancy Services,Singapore	 	\nClient:Barclays Bank ,Singapore	 	\nDuration	: April 2013 to  Dec 2013.	 	\n Barclays is a major global financial services provider engag	ed in retail and commercial banking, credit cards, 	\ninvestment banking, wealth management and	 investment management services	 	\nDescription:Exposure Analysis & Reporting	-Credit Risk Portal	 	\nExposure, Analysis and Reporting application in Credit Risk Portal is a	n application that supports and 	\nenhances new BASEL 	– III and SRA requirements. Changes are been introduced in new BASEL III and 	\nStrategic Risk Architecture (SRA) framework, which impact the current reporting architecture. This project \naims to build a syste	m that enable users to perform What	-if calculations and view pre	-calculated exposure 	\nmeasures, apply adjustments for any counterparty, site, product, what	-if trades, actual trades. View 	\nnumerical and graphical display of risk measures. View list of actual 	trades, trade attributes, settlement 	\nprofiles, netting agreements, Collateral arrangements etc for any CSP and Trades.	 	\nPortfolio simulations are required to generate risk measures to manage the counterparty and trading \nbusiness.This can be used to see the 	impact on a portfolio when new derivative and Securities Financing 	\ntrades are entered into by calculating several credit risk measures.	 	\nThe impact on the regulatory capital is also measured by calculating several regulatory metrics.	 	\nResponsibilities:	 	\n 	Respo	nsible for Design and Development of tactical IT solutions for Credit Risk Management System, 	\nactively involved in UI Design, WCF Services, Database Access Layer including Stored Procedures, \nCreating and maintaining Tables, Triggers, Views, Functions, Inde	xes for performance tuning. 	\nInvolvement in SRA Batches and Downstream Feeds for data to be picked up.	 	\n 	Using WPF, WCF, C#.Net 4, Visual Studio 2010, SQL Server 2008, Infragistics Controls, Xceed Grids and \nChart Controls to design and build up a multi layere	d Credit Risk System.	 	\n 	Championed using MVVM and PRISM design approach to ease separation of concerns between UX \ndesign, business logic, service back end and testing layers.	 	\n 	Involved in Performance Optimization at application and database level, Defect Fixe	s, Migration of 	\nExcel to Application and vice versa.	 	\n 	Involved in all aspects of design and development including co	-ordination of testers, BAs and business 	\nusers. Worked with business analysts to determine business rules and feature list.	 	\nEnvirionment: 	C#,	Visual Studio 2010, WCF,WPF,SQL Server,	 Multithreading	 and IIS.	 	\n Syntel. Ltd , Pune	 	\nAMEX 	 	\nClient:American Express 	 	\nDuration:	 Sept 2010  to 18 Nov 2011	 	\nRole:	 Analyst Programmer	 	\nDescription	: 	\n 	Statement  of  Work  (SOW)  Module:Users  can  create  a  request,  fill  out 	the  forms  by  selecting 	\nappropriate  request  type  and  submit  that  SOW  request,  which  notifies  respective  teams  to  take \naction  Once the request process is completed, the status will  be changed to complete      	 	\nand request can be closed. However, request wi	ll be in DB for future reference	.\n\nResume of Amol	 	 	Page 	8 of 	9 	\n 	Resource  Change  Request:Change  can  be  made  for  changing  the  request  by  leader,Requestor  only	 	\ncancel the request.After complete approvation of request,resource allocates to the requestor.	 	\n 	Work  In  Progress(WIP):This  module  i	s  used  to  manage  Project  Estimation  where  transfer  of  hours 	\nfrom projects is managed.	 	\n \n        	Responsibilities:	 	\n 	Involved  in  Requirement  Analysis,designed  and  developed  Web  application  using  C#.Net  4.0  and \nSilverlight.	 	\n 	Gathering the Client Requirements by 	participating in minute	-to-minute meetings and Analysis.	 	\n 	Design the High Level and Low Level Design of the system.	 	\n 	Programming Using Silverlight,C#	 	\n 	Developed  UI  Using  Silverlight  Controls  and  implemented  business  components  and  data  access \ncode using C#.	 	\n 	Involved in the database design and design tables,indexes and views.	 	\n 	Developed Tables,Indexes,Stored Procedures,Database Triggers and Functions.	 	\n 	Implemented WCF Web Services for database connectivity in Silverlight application.	 	\n 	Analyzed and formulated the T	est plan for requirements,created and test scenario from use cases,	 	\ntest case design from design document,regression and test automation using NUnit.	 	\n 	Involved  in  Unit  and  module  level  testing,reviewing  the  requirements  and  fixing  the  defects \nappropriately.	 	\n 	 Involved in detailed documenting of the application that was developed by me.	 	\n 	Provided production support and deployment support .	 	\n 	Project version management and code control and management was done in VSS.	 	\n 	Project was delievered following CMM methodolog	y. 	\n        	Envirionment:	 C#,Visual Studio.Net,Silverlight,WCF,WPF,SQL Server,Nunit and IIS.	 	\n Acidaes Solutions Pvt. Ltd ,Mumbai	 	\nCRMnext	 	\nClient	: HDFC Bank	 	\nDuration:	 Jul 2008 to Aug 2010	 	\nRole:	 Engineer 	- Application Development Group.	 	\nDescription	:  CRMnext  is 	a  business  application  designed  specifically  to  address  companies  wide  ranging 	\nneeds  of  managing  collaboration  and  interactions  between  vendors,  suppliers,  and  customers.  It  helps \ncompanies  efficiently  manage  the  front	-end  processes,  provide  consistency  ac	ross  all  customer  interaction 	\npoints,  and  focus  on  efficiencies,  boosting  bottom  line  revenue  potential.  Implementing  CRMnext  is  a \nstrategic  initiative  for  any  company.  CRMnext  provides  the  technology  platform  required  to  implement  an \nenterprise  CRM    initi	ative.    A  typical  CRM  initiative  is  a  mix  of  strategy,  process  and  technology  CRMnext 	\nenables companies to better manage and seamlessly share information, across departments by centralizing all \ncustomer  data.  It  automates  various  processes  using  its  workfl	ow  capabilities,  provides  powerful  reporting 	\nand  analytical  capabilities  that  deliver  actionable  business  intelligence.  This  enables  CRMnext  to  help \norganizations  create  a  true  360°  view  of  their  own  customers  that  spans  across  departments.  Typically,  an \nend	-to-end  CRMnext  deployment  will  cover  all  customers  facing  departments  and  manage  the  entire 	\ncustomer  lifecycle.  It  covers  the  entire  working  of  the  company  starting  from  lead  generation,  to  closure  of \nsales and from customer service to cross	-sell / up	-sell services. 	 	\n        	Responsibilities:	 	\n 	Involved  in  defining  business  and  system  requirements  and  designed  the  functional  and  technical \nspecifications.	 	\n 	Programming using ASP.Net,C#.	 	\n 	Design and Developed web Forms using ASP.Net,XML.	 	\n 	Used ASP.Net Server Con	trols and HTML controls to design and web pages.	 	\n 	Involved in writing the programming code for web pages using ASP.NET object model.	 	\n 	Used ADO.Net Object Model to Interact with SQL Server Database using C# language.	 	\n 	Used Dataset object and Data Reader object	 to get the data from Database.	 	\n 	Wrote stored procedures and triggers.	 	\n 	Developed  Reporting  and  Analysis  module  by  web  enabling  reports,Web  development  using \nHTML,ASP.Net to deploy reports for the end user to view,print and export data from analysis purposes	. 	\n 	Involved in the development of the test plan Visual Source safe used on source control tool.	 	\n 	\nEnvironment:	 C#, ASP.Net, SQL Server 2005,Javascript,WCF,AJAX  Nunit,Silverlight	 	\n Orion India Systems Pvt. Ltd., Mumbai	 	\nVector 2008	 	\nClient:	 KPMG\n\nResume of Amol	 	 	Page 	9 of 	9 	\nDuration:	 Jan 20	08 to Jul 2008	 	\nRole:	 Software Developer	 	\nPlatform: 	Windows 2003	 	\nDescription	:   This is a custom auditing tool developed for the pioneers in auditing having their footprint all 	\nover the world. The application is developed in .Net  with client component devel	oped in ASP.Net with a 	\nservice running on the server and backend being MS SQL server.  The application is designed to manage all \nthe activities involved in the auditing process. It also uses service oriented architecture for the integration of \nplug in tool	s which allows system integration through loosely coupled components. The system has also got a 	\ncustom made document management system incorporated to it which holds the information in the SQL file \nsystem.	 	\nResponsibilities	   	\n 	Developed web forms using C#,AS	P.Net and SQL Server 2005.	 	\n 	Used Data Binding to bind Servers controls with the parameter from the tables in the database.	 	\n 	Published  Web  Services  using  C#  to  interact  with  the  other  applications  and  exposed  them  using SOAP \nand HTTP.	 	\n 	Designed and Developed A	SP.Net pages including Master and Navigation pages.	 	\n 	Implemented Data Grid view adding,deleting,sorting of rows for all the contacts and addresses of clients.	 	\n 	Involved  in  unit  and  module  level  testing,reviewing  the  requirements  and  fixing  the  defects \napprop	riately.	 	\nEnvironment:	 C#, ASP.Net, SQL Server 2005,Javascript,WCF,AJAX  Nunit.	 	\n 	\n IL & FS Education & Technology, Mumbai	  	\n Assessment Online	 	\nClient:	 ABNAMRO Bank, ICICI Prudential	 	\nDuration: 	April 2007 to Jan 2008	 	\nRole: 	Software Developer.	 	\nDescription	: Assess	ment Online is an online testing engine, which facilitates: 	 	\nCreation of Tests	 - Tests in any domain can be created from a global question bank (owned by organization)	 	\nAdministration of Tests	 - The tests can administer on	-line question bank or any personal	 question bank of a large 	\nof employer 	.The System enables frequent and Effective evaluation of employee and provides feedback about the 	\nTest  to  the  test  administrators  in  terms  of  statistical  analysis  of  questions  and  tests.  The  Assessment  Online  is  a \npowe	rful  Application  suite  of  creating  tests  and  surveys  on  the  web.  AOL  is  designed  to  deliver  online 	\nassessments  that  can  test  not  only  standard  literacy  and  numeric  skills  but  also  avows  organizations  to  easily \ndesign  their  own  questions.  With  AOL  software,	 you  can  quickly  and  easily  create  and  administer  online  tests 	\nwith minimal effort, giving you more time to spend with learners in the classroom or the workplace. 	 	\nResponsibilities:	  	\n 	Developed and Implemented the web page interfaces	 	\n 	Created  ASP.Net  pages  u	sing  C#.Net  for  middle	-tier  processing  of  clients  requests  of  clients  requests 	\nwith ADO.NET interfaces for database and implemented stored procedures.	 	\n 	Used  ADO.NET  and  data  objects  such  as  Data  Adapter,Data  Reader,Dataset,data  table  for  consistent \naccess t	o SQL data sources.	 	\n 	Used SQL Server as RDBMS to create and maintain Tables,Procedures and Views.	 	\n 	Implemented session state management	 	\n 	Migrated the functionality from existing asp pages to  new aspx pages and also added new functionality \nto reflect the Busin	ess users requirements.	 	\nEnvironment:	 C#, ASP.Net, SQL Server 2005,Javascript,Web Services.	 	\n \nEDUCATIONAL 	QUALIFICATIONS	 	\n P.G.D.A.C (Software)	, Y.C.P.A.I.T, A.C.T.S, C.D.A.C Centre, Mumbai,(Feb,2007)	 	\n B.E (	Computer Technology	), K.I.T.S Ramtek, Nagpur,	 (June,20	02)	 	\n 	\nPERSONAL 	DETAILS	 	\n 	Date of Birth	: 1st January 1978	 	\n 	Languages Known	: English, Hindi and Marathi	 	\n 	Passport No:	 W7633055	 	\n 	Marital Status:	 Married', 2, 2, 1, 'Candidate', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-25 14:17:22', 51),
(456, 109, 73, 46, NULL, '73_109_177263729066a60c6e71d77_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, '2024-07-31 09:24:52', '2024-07-28 09:24:52', 0, NULL, NULL, '2024-07-28 09:16:30', 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
(457, 110, 77, NULL, NULL, '77_110_159672912366a6566ea6855_Ujjwal_Mahar_26062024.pdf', 'Ujjwal Mahar 26062024.pdf', 'Ujjw al M ah arCloud and DevOps: 	Azure, AWS, Docker, Kubernetes, Jenkins, Github Actions, Prometheus, Grafana, Terraform	\nProgramming:	 GoLang, Python	 	\n&bull; D esig ned  a n d  d ep lo ye d  A W S in fra str u ctu re ,  in clu d in g  s e ttin g  u p  p ip elin es,  b acke n d  s e rv ic e s,  a n d\nm onit o rin g  s o lu tio ns f o r v a rio us c lie n ts .\n &bull; I m ple m en te d  c o st o ptim iz a tio n s tr a te g ie s t o  m axim iz e  e ffic ie n cy a n d  r e d uce  o pera tio nal  e xp en se s.\n&bull; M an ag ed  m ajo r p ro je cts  u tiliz in g  A W S s e rv ic e s s u ch  a s E C S,  E K S,  a n d  o th er D evO ps t o ols .\n&bull; E nsu re d  s c a la b le  a n d  r e lia b le  a rc h it e ctu re s t o  m eet c lie n t r e q uir e m en ts  a n d  b usin ess o bje ctiv e s.\n&bull; C ontr ib ute d  t o  G SoC ,  f o cu sin g  o n u se r-p ro vid ed ,  lo ng -liv e d  e n vir o nm en ta l  v a ria b le s in  U nik ra ft b uild s.\n&bull; I m pro ve d  K ra ft C LI t o  d yn am ic a lly  in je ct c u sto m  v a ria b le s,  in clu d in g  G CC v e rs io ns a n d  c o m pile -t im e s e ttin g s.\n&bull; E nab le d  f le xib le  a n d  c u sto m iz a b le  U nik ra ft b uild s f o r d eve lo pers .\n+91 7500070465| ujjwal.mahar01@gmail.com	  | Github	  | LinkedIn	\nE X P ER IE N CEDevO ps E ng in eer\nC lo ud Z en ia\nG oog le  S um mer o f C ode\nU nik ra ft\nN ove m ber 2 023 &ndash;  P re se n t	 	A pril  2 024 &ndash;  P re se n tE D U CA TIO NShard a U niv e rs it y  	B .T ech . in  C om pute r S cie n ce ,	\nIn d ia ,  G au ta m  B ud dha N ag ar,  G re a te r N oid a,  U P\nJun e 2 021 &ndash;  J un e 2 025	\nC G PA	:  8 .4	T E C H NIC A L	  S K IL LS	AWS Solutions Architect Associate	 	C ER TIF IC A TIO N SCours e ra  C ertif ic a te sK odeK lo ud	 	O ra cle  a ca d em yAW S	 	&bull; U tiliz e d  T erra fo rm  t o  b uild  a n d  c o nfig ure  A W S in fra str u ctu re ,  in clu d in g  E C S.\n&bull; I m ple m en te d  G it H ub  A ctio ns f o r C I/ C D  t o  a u to m ate  d ep lo ym en ts  u p o n c o de p ush .\n&bull; A ch ie ve d  s tr e a m lin ed  a n d  e ffic ie n t d ep lo ym en t p ro ce sse s f o r t h e A W S e n vir o nm en t.\n&bull;  I m ple m en te d  P ro m eth eu s f o r m etr ic s c o lle ctio n a n d  G ra fa n a f o r v is u aliz a tio n a n d  a le rtin g .\n&bull; A uto m ate d  A W S A uto  S ca lin g  b ase d  o n P ro m eth eu s m etr ic s f o r o ptim al  r e so urc e  u sa g e.\nP RO JE C TSAuto m ate d  A W S I n fr a str u ctu re  P ro vis io nin g  a n d  C I/ C D P ip elin e I m ple m en ta tio n	 	\nD evO ps P ro je ct\n C lo ud -N ativ e  A pplic a tio n M onit o rin g  a n d  O ptim iz a tio n\nD evO ps P ro je ct\n&bull; L ed  a ctiv it ie s a n d  in it ia tiv e s,  p ro m otin g  A W S c lo ud  t e ch n o lo gie s a n d  c o lla b o ra tio n.V O LU N TEER  E X P ER IE N CEAW S C lo ud  C lu b  C ap ta in&bull;  C o-le d  G DSC ,  o rg an iz in g  e ve n ts  t o  e d uca te  s tu d en ts  o n c lo ud  c o m putin g .G DSC  C o-L ead  a n d  C lo ud  L eadM arc h  2 024 &ndash;  P re se n tA ug ust 2 023 &ndash;  P re se n t', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-28 14:32:14', 0),
(458, 111, 77, 57, NULL, '77_111_177006264066a6569324d1c_Kritika_Aggarwal_resume.pdf', 'Kritika Aggarwal_resume.pdf', 'KRITIKA \nAGGARWAL	 	\n 	\nPROFESSIONAL SUMMARY	 	\nA keen, 	well	-organized	, creative and goal	- 	oriented 	intermediate 	possessing excellent 	communication, problem	-solving and 	leadership skills with 	enthusiasm and 	curiosity 	to 	work on new and creative ideas 	in order to explore the world of science.	 	 TECHNICAL COMPETENCIES	 	 	C  	 	C++	 	 	Python 	 	 	Java	 	 	HTML	 	 	CSS	 	 	MySQL	 	 	AutoCAD	 	 	Excel 	 	 	Microsoft Office	  	 	Canva	 	 	Machine Learning	 	 	Data Science	 	 	Data Analysis	 	 	WordPress	 	\nCONTACT	 	\nPHONE:	 	7982994906	 	EMAIL:	 	kritikaagg134@gmail.com	 	LINK	EDIN: 	https://www.linkedin.com/in/kritika	-	aggarwal	-84a944241	 	 \nINTERESTS &amp; HOBBIES	 	\nReading | Dancing | Painting | Playing basketball &amp; volleyball | Listening to musi	c 	 LANGUAGES KNOWN	 	English | Hindi	 	 PERSONAL DETAILS:	 	Mother&rsquo;s name : POOJA AGGARWAL	 	Father&rsquo;s name	 : TARUN AGGARWAL	 	D.O.B. : 1	st March 2004	 	Address : RZ	-18 D/3 West Sagarpur New 	Delhi	 	\n 	\nEDUCATION	 	 	\nIntermediate (CBSE) | LORETO CONVENT SCHOOL DELHI CANTT	 	Session : 2020	-2021	 | Percentage : 9	3% 	 Matriculation (CBSE) | LORETO CONVENT SCHOOL DELHI 	CANTT	 	Session : 2018	-2019 | Percentage : 91.6%	 	 GRADUATION | SHARDA UNIVERSITY GREATER NOIDA	 	Session: 2021	-2025 | CGPA : 8.	924	  	\nCERTIFICATONS	 	\n&bull; 	Course of MACHINE VISION AND ROBOTICS | Sharda Skills	 	(18th April 2022 	&ndash; 28th May 2022)	 	o 	Bar code reading 	machine concepts	 	o 	QR generators and reading concepts	 	 	&bull; 	ARTIFICIAL INTELLIGENCE 	COURSE	 | VERZEO	 	(1st July	 2022 	&ndash; 31th August 	2022)	 	 EXPERIENCES	 	 	&bull; 	5TH TECHNOVATION HACKATHON	 | SHARDA UNIVERSITY	 	(30	th January 2023 	&ndash; 4th February 2023)	 	 	&bull; 	Internship at Metro Telworks 	 	(5th June 2023 	&ndash; 14th July 2023)	 	 	&bull; 	Internship at BanBanjara	 	(11th August 2023 	&ndash; 11th Nove	mber 2023)	 	 PROJECTS	 	 	&bull; 	Dog Breed Classification | VERZEO	 	o 	Machine learning 	&ndash; image recognition	 	 	&bull; 	Abnormal Event Detection in Surveillance videos	 	o 	Machine learning 	&ndash; CNN, image recognition	 	 	&bull; 	Cryptocurrency Prediction 	Using GRU and LSTM	 	o 	Machine learning 	&ndash; GRU, LSTM, pattern recognition	 	 	&bull; 	T-Shirt Designer 	Website	 	o 	Web Development 	&ndash; React, HTML	, CSS	 	\nINTERPERSONAL SKILLS	 	\nTeam Leadership | Management &amp; Coordination | Decision Making | Communication and emotional intelligence | Critical thinking	 | Intellectual 	Curiosity 	| Public Speaking', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-08-01 06:26:34', '2024-07-29 06:26:34', 0, NULL, NULL, '2024-07-28 14:32:51', 0),
(459, 111, 77, 58, NULL, '77_111_136266061866a6569325481_MoiezResume.pdf', 'MoiezResume.pdf', '/  	\nS Y ED  M OH AM MAD  M OIE Z  U R R A H M AN\nASP IR IN G D ATA  A N ALY ST	\nM OIE Z R16 1	w ww.lin ke d in .c o m /in /s y e d -m -m oie z-u r-\nr a h m an -9 a1a 17 2 4 8	\nhttp s:/ /g it h ub .c o m /M oie zR	O KH LA , N EW  D ELH I	\nP R O JEC TS\nAuth ore d  R ese arc h  P ap er T it le d  &quot; C hro n ic  K id n ey D is ea se	 	\nP re d ic tio n  u sin g M ach in e L e arn in g: F eatu re  S ele ctio n &quot;\nPap er c u rre n tly  u n d er p ro ce ss	\nS ele cte d  t h e b est 1 0  f e atu re s f ro m  t h e a va ila b le  2 6  f e atu re  s p ace  u sin g	 	\nS ele ctK Best m eth o d .\nR ed uce d  t h e r is k  o f o ve rfit tin g  o n d ata  m od el  b y lo w erin g  t h e d im en sio n a n d	 	\nth e f e atu re  s p ace  o f t h e d ata se t.\nC om pare d  t w o d if fe re n t m od els ,  t r a in in g  b oth  o n t h e b est 1 0  f e atu re s	 	\nse le cte d :  G au ssia n  N aiv e  B aye s a n d  K\nA ch ie ve d  t h e h ig hest a ccu ra cy u sin g  t h e K	 	\nT e ch niq ue (X G Boost),  9 8% .	\nS peech  E m otio n  D ete ctio n  w it h  F u zzy  c la ssi\nPro je ct L in k	\nTra in ed  a  n eura l  n etw ork  m od el  t o  d ete ct t h e e m otio n in  a u d io  f ile s o f	 	\np eo p le &#039;s  s p eech .\nN eura l  N etw ork  w as t r a in ed  o n t h e L o ng  S ho rt T e rm  M em ory  m od el  t o	 	\nc a p tu re  e ffe ctiv e  d ep en d en cie s in  p ast d ata .\nT ES S d ata se t w as u se d  f o r t h e d eve lo p m en t o f t h is  p ro je ct.	\nU ni	 	\nan d F acia l A naly sis  ( c u rre n tly  o n -g oin g)\nIn te g ra tin g  t e xt,  s p eech  a n d  f a cia l  a n aly sis  o n a  s in g ula r b acke n d  p la tfo rm .	\nRob erta  m od el  f ro m  t h e H ug gin g  F ace  lib ra ry  b y M eta  f o r s e n tim en t a n aly sis	 	\no f d ata  in  t e xtu al  f o rm at o r &quot; c h ats &quot;\nS elf  d eve lo p ed  m od el  ( m en tio ned  a b ove ) f o r t h e s e n tim en t a n aly sis  o f d ata  in	 	\na u d io  f o rm at o r &quot; s p eech &quot;\nO pen C V lib ra ry  u se d  f o r t h e s e n tim en t a n aly sis  o f f a cia l  e xp re ssio ns.	\nE D U CATIO N\nSH ARD A U NIV ER SIT Y  |  G REATE R  N OID A, U TTA R	 	\nPR A D ES H\nBac h elo r o f T e ch nolo g y i n  C om pute r S cie n ce	\n10/2021 	&nbsp;	\nGP A	\n8.0 1	10 .0	\nR ele va n t C ours e w ork :  D ata b ase  M an ag em en t S yste m s,  N eura l  N etw ork s,	 	\nO pera tin g  S yste m s,  C om pute r N etw ork s,  In tro d uctio n t o  E ntre p re n eurs h ip ,	 	\nD eep  le arn in g	\nIN TE R N ATIO N AL I N DIA N  S C H OOL A l- J ubail   |  K S A\nHig h S ch ool	\n04/200 7 	&nbsp;	\nCla ss X IIt h :  8 3 %\nC la ss X th :  8 2.6 %	\nS U M MARY\nDeta il  a n d  g oal  o rie n te d  d ata  d riv e n  in d iv id ual  w it h  a	 	\np assio n in  e xp lo rin g  p atte rn s a n d  d ep en d en cie s	 	\nam ong  v a rio us la rg e d ata se ts .  O rg an iz in g ,	 	\npre p ro ce ssin g  a n d  c le an in g  d ata se ts  o f v a ry in g  s iz e	 	\nto  e ffic ie n tly  u se  t h em  a n aly sis  a n d  p re d ic tio ns	 	\nle ve ra g in g  v a rio us t e ch nic a l  t o ols .\nA C H IE V EM EN TS	\nHac kath on  W in ner i n  t h e D ata  S cie n ce	 	\nD om ain\nW on a  h acka th o n c o nd ucte d  in  a  S hard a	 	\nU niv e rs it y  b ootc a m p in  t h e D ata  S cie n ce	 	\nd om ain .\nW in ner o f S park ath on &#039;2 3\nW on a n  in te r- d ep artm en t a p tit u d e a n d  s o ft	 	\ns k ills  b ase d  c o m petit io n.\nT e ch noK ra ts  C od in g  C om petit io n  F in alis t\nR each ed  t h e f in al  r o un d  o f p ro b le m  s o lv in g	 	\nb ase d  c o d in g  c o m petit io n o rg an iz e d  in  S hard a	 	\nU niv e rs it y .\nB est D ele g ate  a w ard  a t I IS M UN &#039;2 0\nJo rd an  b ase d  v ir tu al  M od el  U nit e d  N atio ns.	\nS KIL LS\nData  P re p ro ce ssin g  a n d  A naly sis\nA dva n ce d  E xc e l	P ow erP oin t	P yth on	\nM ac h in e l e arn in g	S Q L	\nSta tis tic al A naly sis	D ata  V is u aliz a tio n	\nJav a	E ffe ctiv e  C om munic atio n	\nTe am  C olla b ora tio n\nA C TIV IT IE S	\nCon te n t W rit in g, B lo g ger\nat 	W is e rY o u th .C lu b	\nR ead in g\nS w im min g\nTra v e lin g	\nwww .enhancv .com	\n	\nPow er ed b y	\nE		q	\nq		\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\n\n\n\n\n\n\n', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-08-01 06:29:25', '2024-07-29 06:29:25', 0, NULL, NULL, '2024-07-28 14:32:51', 0),
(460, 112, 77, 56, NULL, '77_112_33183043366a656b3273ef_Abhinav_.pdf', 'Abhinav .pdf', 'Abhinav	 Singh	 	\n2021470897.abhinav	@	.ug.sharda.ac.in	 ❖	 (+91	) 93190	-61178	 ❖	 Gorakhpur	, U.P.	 	\n❖	 LeetCode link	 ❖	 	 	\n \n \n \n \nTECHNICAL SKILLS: 	JAVA, JavaScript, HTML, CSS, 	Tailwind, 	Node.js, Express.js, PostgreSQL, React, Git, 	\nMarkup	 	\n  \n \nMERN Image Generation Website	  	 	 	 	 	                     	 Oct. 20	23	 &ndash; Dec .2023	 	\n▪ 	Independently conceptualized, designed, and developed a sophisticated image generation platform using the \nMERN (MongoDB, Express.js, React.js, Node.js) stack.	 	\n▪ 	Integrated cutting	-edge artificial intelligence capabilities by leveraging the OpenAI API for advanced image 	\ncreation, enhancing the platform&#039;s functionality and appeal.	 	\n▪ 	Employed MongoDB as the primary database solution to efficiently manage and store user data, ensuring \nseamless retrieval and manipulation of generated images.	 	\n  	\n					 	 	                    			 	\n▪ 		 	\n▪ 				 	\n	 	\n▪ 	 \nHTTP requests efficiently.	 	\n \nEDUCATION 	 	 	 	\nSharda 	University	  	 	 	 	 	                     	         	 	 	        	     	Aug .2021 	&ndash; Present 	 	\nB.tech	, Computer Science	  	 	 	 	    	 	 	     	        	     	           	Greater Noida	, U.P.	 	\n▪ 	CGPA 	&ndash; 8.9	 	 	 	 	 	 	 	 	 	         	     	Up until 	6th Semester	 	\n▪ 	Related Coursework : 	Computer Networks 	Operati	ng	 System, Database Management	 System, etc.	 	\n \nRam	-eesh International School (CBSE)	 	 	 	                     	         	              	April	 .20	19	 &ndash;July 2020	   	\nClass 12th	 	 	 	 	    	 	 	     	        	       	         	                        	Greater Noida	, U.P.	 	\n▪ 	Percentage	 &ndash; 84	 % 	\n 	\nRam	-eesh International School (CBSE)	 	 	 	                     	         	              	April .2017 	&ndash;July 2018  	 	\nClass 10th	 	 	 	 	    	 	 	     	        	       	                                 	Greater Noida	, U.P.	 	\n▪ 	Percentage 	&ndash; 91	 % 	\n  	\nCERTIFICATIONS, 	SKILLS &amp; INTERESTS	  	 \n▪ 	Certifications: 	JAVA Foundation	 	\n▪ 	Skills	 : Proficient in DSA, Strong Computer Science Fundamentals,	 Efficient at communicating issues,	 	\n Good	 System Design Understanding	 	\n▪ 	Interests	 : 						  	\n 	\n 	\nI am a Full Stack Developer with a passion for problem	-solving and a curious mindset. I embrace feedback 	\ngracefully, integrating it into my work to continually improve. Eager to expand my skills, I approach each task \nwith a willingness to learn and adapt w	ithin the job. My approachable nature and ability	 communicate ideas make 	\nme a valuable team member, fostering a collaborative environment where innovation thrives.	 	\nFeb . 202	4 &ndash; Mar .202	4	\nCompetitive Chess, Reading Technical Blogs, Linux Ricing , Avid Movie Critique	\nDeveloped a web scraping application using Node.js to generate internal links reports for websites.\nUtilized popular Node.js libraries such as 	`node-fetch	` for making HTTP requests and 	`jsdom	` for	\nImplemented URL normalization to ensure consistent URL formats using the Node.js URL object.	\n			\nGitHub link	\nparsing HTML responses.	\nWeb Cra	wler and Internal Links Analy	zer using Node.js', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-08-01 06:17:16', '2024-07-29 06:17:16', 0, NULL, NULL, '2024-07-28 14:33:23', 0),
(461, 112, 77, NULL, NULL, '77_112_161702027566a656b327bd2_Mohit_2021001021_Resume.pdf', 'Mohit_2021001021_Resume.pdf', 'MOHIT SARASWAT\r\nmohitsaraswat1703@gmail.com | (+91) 8130697855\r\nGreater Noida,India\r\nMohitSaraswat17 MohitSaraswat/ MohitSaraswat\r\nPROFESSIONAL SUMMARY\r\nPassionate and results-driven 4th-year Computer Science Engineering student specializing in full-stack\r\ndevelopment. Skilled in data structures and algorithms with a proven ability to solve complex problems and lead\r\nprojects to successful completion. Eager to leverage technical skills in innovative technology solutions.\r\nSKILLS\r\nTechnical Skills:- Full Stack Web Development (MongoDB,NodeJs,ReactJs,ExpressJs), MySql, Java, HTML, CSS,\r\nJavaScript\r\nCourse Work :- Data Structures and Algorithms, Computer Networks,DBMS,OOPs,Operating System.\r\nTools:- Git , Github, VS Code, MS Office, Oracle Cloud Infrastructure , Google WorkSpace\r\nSoft Skills:- Decision Making, Creative Thinking, Research&Analysis, Project Management\r\nEDUCATION\r\nBtech Computer Science | Sharda University ,Greater Noida CGPA: 8.358| (2021-25)\r\nXII (CBSE) | Father Agnel School, Greater Noida Percentage: 84%| 2021\r\nACADEMIC PROJECTS\r\nTask Management WebApp(TaskSync)\r\nDeveloped a MERN stack task management app with secure authentication, CRUD operations, and Cloudinary\r\nintegration for image uploads. Showcased expertise in React, MongoDB, ExpressJS, and NodeJS.\r\nTextUtils\r\nCreated TextUtils, a React web app for text manipulation, including case conversion, space removal, and word\r\ncount. Features include text preview, copy functionality, and light/dark modes for readability.\r\nStress And Anxiety Detection\r\nDeveloped a real-time stress and anxiety detection system using Python, OpenCV, and deep learning for emotion\r\nrecognition. Integrated live video monitoring with stress indicators, showcasing skills in image processing, facial\r\nrecognition, and machine learning.\r\nReact Portfolio Website\r\nCreated a personal portfolio website using ReactJS and Tailwind CSS, featuring a modern, responsive design and\r\ninteractive elements. Demonstrated expertise in frontend development and design frameworks.\r\nACHIEVEMENTS / CERTIFICATIONS\r\nResearch Paper:- Presented my paper on stress and anxiety detection at ICTACS 2023, showcasing a real-time\r\nfacial expression analysis system using Python and deep learning. The paper is published by IEEE.\r\nUdemy:- Java In-Depth : Become Complete Java Engineer!\r\nOracle Academy:- Database Foundations | Database Programming with SQL\r\nDevTown:- JavaScript and React\r\nINTERESTS / HOBBIES\r\nGaming\r\nTravelling\r\nCooking', 0, 0, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-28 14:33:23', 0),
(462, 113, 77, 54, NULL, '77_113_188343306466a656d533536_AbhiAkshat-CV.pdf', 'AbhiAkshat-CV.pdf', 'Abhi Akshat	 	(Aspiring	 	Engineer)	 	\nLinkedIn:	 	linkedin.com/in/abhi	-	akshat	-	56473a228	 	\n 	\n       	abhiakshatofficial@gmail.com	 	\n+91	-	7001356029	\nGitHub:	 	github.com/abhi	-	akshat	 	\n \nSKILLS	 	SUMMARY	 	\nLanguages	 	C/C++,	 	JavaScript,	 	Python, JAVA, GoLang, HTML, CSS, Swift	, SQL	 	\nFrameworks	 	P	yT	orch, TensorFlow	, OpenCV, 	NodeJS, React	J	S	, Echo, SwiftU	I	, StreamLit	 	\nTools	 	VS Code, GIT, GitHub, Google Colab, AWS, Docker	, PostgreSQL, MongoDB	 	\nPlatform	 	Web, Cloud, iOS	 	\nSoft Skills	 	Project Management, Leadership, Teamwork, Writing, Public Speaking	 	\n \nEXPERIENCE	 	\nSoftware Developer 	Intern @ 	SKILLMONDE	 	Greater Noida	 	\nInternship	 	 	June	 	202	4	 	&ndash;	 	Present	 	\n&bull;	 	Developed Internal Automation to st	ream	li	ne w	ork	flow using AI. Reducing time taken 	by 	6	0	-	70%.	 	-	 	Pyth	on	 	\n&bull;	 	Redesigning of 	websi	te and 	developing n	ew features such as 	&ndash;	 	Subscription 	System	.	 	&ndash;	 	ReactJ	S, 	NodeJS.	 	\n \nAI 	Intern @ COINCENT.AI	 	Remote	 	\nInternship	 	 	July 202	3	 	&ndash;	 	August 202	3	 	\n&bull;	 	Developed a landmark detection application using Google Landmarks V2 dataset. 	Built	 	and Trained a	 	VGG	-	\n19 model.	 	\n&bull;	 	Used technologies like TensorFlow and Streamlit. Python was the primary language for the project.	 	\n \nPROJECTS	 	\n&bull;	 	Dynamic Object 	Detector	 	 	MERN with Typescript	 	\no	 	Developed a 	memory efficient system that detects moving object. Built using C++ and OpenCV. Added 	\nefficient memory management. 	Winner	 	of BGSW AutoVision X hackathon. 	 	\no	 	Main focus of the project was memory efficiency.	 	\n&bull;	 	ML Preprocessor CLI	 	CLI Tool, AI	 	\no	 	Developed 	a	 	No	-	Code	 	preprocessor  that  handles  preprocessing  needs  of 	any  ML  projects.	 	Developed 	\nfeature  like  dataset  description,  handling  null  values, 	Encoding  Categorical  Data	, 	Feature  Scaling	 	and 	\nDownloading modified dataset.	 	\no	 	Deployed it on an EC2 instance in AWS.	 	Built using Python and libraries like 	&ndash;	 	Pandas, NumPy, SciKit 	\nLearn.	 	\n \nACHIEVEMENT	 	\n&bull;	 	Winner of BGSW AutoVisionX	 	2024 	&ndash;	 	Hackathon conducted by Bosch Global Software Technologies.	 	\n&bull;	 	Published  a  paper,  &ldquo;A  Comparative  Analysis  on  Various  Machine  Learning  Algorithms  Used  for \nHandwritten Digit Recognitions&rdquo;, at ICCIS 2023.	 	\n \nEDUCATION	 	\nSharda University, Greater Noida	 	   	Uttar Pradesh, India	 	\nBachelor Of Technology 	&ndash;	 	Computer Science and Engineering	 	 	July 2021 	&ndash;	 	May 2025	 	\nCGPA 	&ndash;	 	9.1	87	 	\nSpecialization	: Artificial Intelligence and Machine Learning	 	\nNew Light Academy, Namchi	 	Sikkim, India	 	\nCBSE: 82.4%	 	  	March 2020	 	\nDon 	Bosco School, Siliguri	 	West Bengal, India	 	\nICSE: 90.4%	 	 	March 2018', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-08-01 05:31:30', '2024-07-29 05:31:30', 0, NULL, NULL, '2024-07-28 14:33:57', 0),
(463, 113, 77, 52, NULL, '77_113_42175591766a656d533b23_Ishan_Sen_Resume.pdf', 'Ishan Sen_Resume.pdf', 'Ishan Sen\n\nJollyBolt \ntheishansen \nishansen.in \nsenishan21@gmail.com \n+91 9953774233\nWORK EXPERIENCE\nEYTHOR PVT LTD | Software Developer Intern April 2024 &ndash; July 2024\n&bull;\nSpearheaded the migration of the company&rsquo;s monitoring software from React.jstoNext.js andTypeScript ,\nresulting in a 27%increase in performance.\n&bull;\nEnhanced accessibility by16% andSEO by37% by implementing best practices and optimizing the\napplication.\n&bull;\nDeveloped interactive tables using TanStack Table, improving data visualization and user interaction.\n&bull;\nEmployed ShadCN/UI to improve the design and integrate dark mode.\nSK INFO TECHIES | Software Developer Intern June 2023 &ndash; July 2023\n&bull;\nWorked on a new company portfolio using NextJs.\n&bull;\nImproved SEOperformance by 13%through breadcrumb implementation.\n&bull;\nIntegrated a sophisticated contact form with email services.\nSKILLS\nLanguages: C++, Python, Java, C\nDevelopment: HTML, CSS, JavaScript, Typescript, Tailwind CSS, React JS, Next JS, MongoDB, Express JS, Node JS,\nREST API, Git, Github\nLibraries: Redux Toolkit, Recharts, React Hook Forms, TanStack Table, Framer Motion, BootStrap\nPROJECTS\nINVOICERY Live | Github React Js, Tailwind CSS, MongoDB, Express JS, Node JS\n&bull;\nInvoicery is a GST billing software that enables users to create complex GST billsin under30 seconds .\n&bull;\nEngineered an advanced analytics dashboardproviding detailed insights into key business metrics.\n&bull;\nIntegrated Rechartsto create interactive charts and visualizations.\n&bull;\nImplemented TanStack Table for managing and displaying tabular data effectively.\n&bull;\nUtilized Redux Toolkit for efficient state management and React-HookForm for form handling.\nINOTES Live | Github React Js, Tailwind CSS, MongoDB, Express JS, Node JS\n&bull;\nBuilt a full-stack note-taking website that allows users to create, edit, organize, and delete notes.\n&bull;\nIntegrated robust user authentication mechanisms, employing JWTfor secure access.\n&bull;\nEngineered custom RESTful APIfor efficient data interactions to ensure a seamless and responsive user\nexperience.\nWATCH IT ALL Live | Github React Js, Tailwind CSS, Material UI\n&bull;\nCreated a responsive multimedia platform enabling users to search and view YouTube videos.\n&bull;\nSeamlessly integrated the &rsquo;YouTube v3&rsquo; API.\nEDUCATION\nSharda University, India September 2021 - Expected 2025\nBachelor of Technology in Computer Science Engineering CGPA:8.96\nDelhi Public School,Mathura Road April 2019 - March 2020\nAISSCE (CBSE), CLASS XII Percentage:94.2\nACHIEVEMENTS\n&bull;\nSecured firstplace in Technokrats&rsquo;3.0\n and Technokrats&rsquo;23  .\n&bull;\nSolved over 300DSA problems on LeetCode.\n\n&bull;\nSteered a team of 4 to achieve a top-10ranking in the &rdquo;Smart Health, Agriculture, and Hygiene&rdquo; category at\nthe 5th Technovation Hackathon.\n\n&bull;\nReached Pupilon codeforces.\n\n&bull;\nAwarded Merit Scholarship for ranking undertop-20for 3 consecutive years.', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-08-01 05:29:44', '2024-07-29 05:29:44', 0, NULL, NULL, '2024-07-28 14:33:57', 0),
(464, 113, 77, NULL, NULL, '77_113_14544491366a656d533cd2_Janvi.pdf', 'Janvi.pdf', 'Janvi Sharma	 	\nDetail	-oriented and enthusiastic 	software	 	\ndeveloper	 with	 a solid	 foundation	 in com puter	 	\nscience principles and programming languages	 	\nlike	 Python	 and	 Java	 	\nsharmaajanvi9@gmail.com	 	 	\n 	\n9971058561	 	\n 	\nDelhi, 	Noida,	 India	 	\n \n \nEDUCATION	 	\nClass	 X (	CBSE	) 	\nMANI BEN PATEL BHARTIYA MAHILA \nSARVODAYA KANYA VIDHYALAY	 	\n03/2018	 - 05/2019	, 	79.2%	 	\n \nClass	 XII	 (CBSE)	 	\nMANI BEN PATEL BHARTIYA MAHILA \nSARVODAYA KANYA VIDHYALAY	 	\n03/2020	 - 05/2021	, 	81.6%	 	\n \nBachelor	 of	 Technology	 (CSE)	 	\nSharda	 University	 	\n10/2021	 - Present	, 	Second Y ear	 - 7.663 CGPA	 	  \n \nPERSONAL	 PROJECTS	 	\nQuiz	 Game	 - Java	 and	 Spring	 Boot	 	\n(05/2023	 - 05/2023)	 	\nCreated	 a quiz	 game	 using	 Java	 and	 Spring	 boot	 	 \nTO	-DO Web 	Application 	- Java and Spring Boot	 	\n(04/2023	 - 04/2023)	 	\nCreated	 a TO	-DO	 web	 application	 using	 Java	 and	 Spring	 Boot	 	 \nMedistat	 - Java	 and	 Spring	 Boot	 (12/2022	 - 02/2023)	 	\nThis	 application	 stores	 the	 user&#039;s	 medical	 reports	 in an 	organized	 manner	 so that	 they	 could	 be accessible	 eﬃciently	 by 	any	 doctor	 and	 the	 user	 variety	 of features	 to analyze	 the	 data.	 	 \nStudy	 Buddy	 Web	 Application	 - Python	 and	 Django	 	\n(09/2021	 - 11/2021)	 	\nThis application helps the students utilize their time and	 	provide	 them	 with	 all the	 curriculum	 like	 previous	 year	 papers,	 	books,	 notes,	 etc.	 	  \n \nWORK	 EXPERIENCE	 	\nBackend	 Developer(Java)	 - Internship	 	\nFlickMatch	 	\n07/2023	 - Present	, 	Noida,	 India	 	\nSpringBoot	 Project	 	\nDeveloped RESTful APIs for creating events, added	 	\ncurrency	 and	 worked	 on various	 diﬀerent	 scenarios.	 	\nWrote	 unit test cases in	 JUnit5 and Hamcrest.	 	\nSKILLS	 	 	\n 	 	 	 	 	\n 	 	 	 	 	\n 	 	 	 	\n 	\n \n \nACHIEVEMENTS	 	\nTechnovation Hackathon 	- Sharda Univers	ity	 	\n(01/2023	 - 02/2023)	 	\nGot	 certiﬁcate	 of participation	 on smart	 health	 project	 	 \nOlympiad	 of Mathematics	 (05/2011	 - 05/2011)	 	\nFourth	 Rank	 in Class	 	 \nInternational Conference on Recent Trends in	 	\nBiotechnology	 and	 Applied	 Bioinformatics	 (ICRTBAB)	 	\n2023	 - Sharda	 University	 (04/2023	 - 04/2023)	 	\nCertiﬁcate	 of Participation	 	   \n   Successful food drives in NGO	 	\n \nCERTIFICATES	 	\nJava	 Course	 Completion	 by	 Oracle	 Academy	 	\n(12/2022	 - 02/2023)	 	Completion	 of Java	 Course	 	 \nDatabase Completion	 by	 Oracle	 Academy	 	\n(05/2023	 - 07/2023)	 	Completion	 of Database	 Course	 	 \nJava	 Foundation	 By	 Oracle	 Academy	 	\n(07/2022	 - 11/2022)	 	Completion	 of Java	 Foundation	 Course	 	 \n \n \n \n \n \nLANGUAGES	 	\nImplemented	 GraphQL	 queries	 using	 DynamoDB.	 	      	English	 	\nFull	 Professional	 Proﬁciency	 	\nHindi	 	\nFull	 Professional	 Proﬁciency	 	\n \n 	\nINTERESTS	 	\nAdaptability	 	\nProblem	 Solving	 	Time	 Management	 	Leadership	 	\n \n 	\nTeam work	 	\n 	\nMySQL	 	Educator	 	Data Entry	 	\nData	 Structures	 	C 	Java	 	Python	 	\nCricket	 	Coding', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-28 14:33:57', 0),
(465, 113, 77, 53, NULL, '77_113_81585760766a656d533ec8_jyoti_harbola_resume.pdf', 'jyoti harbola resume.pdf', 'JYOTI	 HARBOLA	 	\nJyotiharbola2016@gmail.com	 | +91	 8269639607	 	\n 	\n  Leetcode 	-Jyotiharbola2016	 	  /Jyoti	-Harbola	 	\nSUMMARY	 	\nPassionate  and  dedicated  Software  Developer	 with  expertise  in  Java,  Data  Structures,  and 	\nAlgorithms.  Proven  proficiency  in  web  development  using  React  and  Node.js.  Skilled  in  building \nresponsive,  dynamic  web  applications	.  Highly  motivated  to  learn  and  grow,  thriving  in  challenging 	\nenvironments, and adept at applying technical skills to solve complex problems.	 	\nEXPERIENCE	 	\n❖  Web	 Development	 | Pyramid	 Cyber	 	June 	2024	 	\nCollaborated with a team of developers to design and implement user	-friendly interfaces.	 	\nDeveloped	 and	 maintained	 responsive	 web	 applications	 using	 React	 and	 Node.js,	 ensuring	 	\nhigh	 performance	 and	 scalability.	 	\n❖ Frontend	 Development	 	April	 2022	 	\nCreated visually appealing and user	-friendly interfaces using HTML, CSS, and JavaScript.	 Ensured	 	\nseamless	 cross	-browser	 compatibility	 and	 mobile	 responsiveness	 for all	 web applications.	 	\n❖ Research	 Paper	 | Stress	 and	 Anxiety	 Detection	 via	 facial	 expression	 	Dec 2023	 	\nPublished 	a research paper in the 2023 3rd International Conference	 on	 Technological	 	\nAdvancements	 in Computational Sciences	 (ICTACS).	 	\n \nACADEMIC	 PROJECTS	 	\n 	\n❖ Path	 Finding	 Algorithm	 Visualizer	 	\nDeveloped a tool to visualize and demonstrate various pathfinding algorithms, enhancing user	 	\nunderstanding	 of algorithmic processes	 and	 efficiencies.	 	\n 	\n❖ IOT	 Based	 water	 Quality	 Monitoring	 System	 	\nImplemented a system using sensors to measure and monitor water quality parameters,	 	\nassessing	 water	 safety and	 usability in real	-time.	 	\n 	\n❖ Dog	 Care	 web	 Application	 for	 NGO	 	\nDesigned	 and	 built	 a web application	 for	 &ldquo;TheProjectDaisy,&rdquo;	 a local	 college NGO,	 to manage	 	\nand	 support dog	 care	 initiatives.	 	\n 	\n❖ Voice	 Based	 Emailing	 System	 for	 Blinds	 	\nCreated	 a voice	-based	 system	 to transcribe	 user	 voice	 commands	 into	 text,	 facilitating	 email	 	\ncomposition	 and	 management for	 individuals	 with	 visual impairments.	 	\n \nEDUCATION	 	\n❖	 Computer	 Science |	 Sharda	 University	 	CGPA	: 8.2	 	\n❖	 XII	 (CBSE)	 | Army	 Public	 School	 	76.8%	| 2020	 	\nEXTRACURRICULAR	 ACTIVITIES	 	\n&bull; 	Hackathon	 Hospitality	 Team	 Member.	 	\n&bull; 	Active	 Member of	 the	 NGO	 &ldquo;The	 Project	 Daisy&rdquo;', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-08-01 05:30:57', '2024-07-29 05:30:57', 0, NULL, NULL, '2024-07-28 14:33:57', 0),
(466, 113, 77, 55, NULL, '77_113_120449631666a656d53409f_Kritika_Tripathi_Resume.pdf', 'Kritika_Tripathi_Resume.pdf', 'Kritika Tripathi\nEmail: kritika.tripathi03@gmail.com\nLinkedIn: linkedin.com/in/kritika-tripathi-b5052a186/ Mobile: +91-7011435021\nGithub: github.com/kritikatripathi03\nSkills Summary &bull;\nLanguages : Python, C++, C, JavaScript, HTML, CSS, MySQL, JAVA\n&bull; Frameworks : React, Angular, Bootstrap, Flask, Django\n&bull; Tools : VS Code, PyCharm, Anaconda; Docker, GIT, Bash, Google Colab, Google Cloud\n&bull; Platforms : Web, Windows, Cloud, Linux\n&bull; Soft Skills : Leadership, Teamwork, Event Management, Writing, Public Speaking, Time Management\nEducation &bull;\nSharda University\nUttar Pradesh, India\nBachelor of Technology - Computer Science; CGPA: 9.285 October 2021 - June 2025\nSpecialisation: Artificial Intel ligence, Machine Learning\n&bull; Delhi Public School, Maruti Kunj\nHaryana, India\nClass 12th 92.2 %; Class 10th 95.8 % March 2018 - March 2021\nExperience &bull;\nSDE Intern @Amazon-Team CMT Systems\nBengaluru, Karnataka\nInternship May&rsquo;24 - July&rsquo;24\n◦ Worked on a Marketplace Onboarding into the CMT Systems by adding config changes.\n◦ Worked on the core problem faced by CMT Systems where the price is not assigned to products.\n◦ Learned to work on, test, and perform production-level deployment on pipelines. Learned to create version sets\nand do config changes.\n&bull; Data Analyst Intern @NoQs Digital\nRemote\nInternship Mar&rsquo;23 - July&rsquo;23\n◦ Used data to create models that depict trends in the customer base and the consumer population as a whole.\n◦ Developed and maintained databases, and data systems &ndash; reorganized data in a readable format.\n&bull; Google Developer Student Clubs(GDSC) Tech Lead\nRemote\nCore Team Member Jan&rsquo;22 - Jun&rsquo;22\n◦ Conducted online and offline technical &amp; soft-skills training, and coding contest for students, especially freshers.\n◦ Helped freshers get familiar with the club and solved their queries.\nProjects &bull;\nDynamic Ob ject Detection (C++ - CMake, OpenCV) :\nCreate a tool that detects dynamic ob jects on the road. Employed capabilities of OpenCV module in C++ to detect ob jects.\nLearned and attempted to enhance memory management in the pro ject using capabilities of C++ language. (February&rsquo;24)\n&bull; Responsive Portfolio Website(React, CSS, Bootstrap) :\nWorked on a website that showcases personal portfolio. It contains the About, Skills, and Pro jects sections, and a contact\nform. Worked with Bootstrap to make the website responsive. (Mar &rsquo;23)\n&bull; Handwritten Digit Recognition Using 5 Different Algorithms (Python - Machine Learning) :\nLearned how to recognize handwritten digits using 5 different algorithms. Used MNIST and SKLearn load digits datasets. CNN\nachieved the highest accuracy of 99.56 percent and 97.15 percent on training data and testing data respectively. (April &rsquo;23)\n&bull; YouTube Transcript Summariser (Python, HTML, CSS, Javascript) :\nAn extension that would take up the transcript of any video available on YouTube whose transcript is present and summarise\nits transcript for the user. I used. I learned to use the Flask framework and used T5tokeniser for summarising the transcript.\n(December &rsquo;23)\nAchievements &bull;\nBosch Global Software Technologies AutoVisionX Hackathon 2024 Winner :\nBagged the First Prize in the AutovisionX Hackathon held from December 2024 to March 2024. Create a Dynamic Ob ject\nDetection tool with efficient memory management unit.\n&bull; IEEE 3rd International Conference on TESMET 2023 :\nPresented the paper titled - &rdquo;Enhancing the Security of Online Voting System Using Defined Biometrics&rdquo;, which discusses\nimproving the voting system and shifting to online voting. The paper has been accepted and published in IEEE Xplore.\n&bull; International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) 2023 :\nPresented the paper titled - &rdquo;A Comparative Analysis of Various Machine Learning Algorithms for Handwritten Digit\nRecognition&rdquo;, which compares 5 popular algorithms for handwritten digit recognition. The paper has been accepted and\npublished in IEEE Xplore.\n&bull; Women Engineers Program Scholar :\nSelected for a two-year experiential program among 250 women engineering students from nearly 30,000 applicants all-over\nIndia. TalentSprint conducts it in collaboration with Google.', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-08-01 05:32:02', '2024-07-29 05:32:02', 0, NULL, NULL, '2024-07-28 14:33:57', 0),
(467, 114, 77, NULL, NULL, '77_114_80960437566a707c281f90_Abhinav_.pdf', 'Abhinav .pdf', 'Abhinav	 Singh	 	\n2021470897.abhinav	@	.ug.sharda.ac.in	 ❖	 (+91	) 93190	-61178	 ❖	 Gorakhpur	, U.P.	 	\n❖	 LeetCode link	 ❖	 	 	\n \n \n \n \nTECHNICAL SKILLS: 	JAVA, JavaScript, HTML, CSS, 	Tailwind, 	Node.js, Express.js, PostgreSQL, React, Git, 	\nMarkup	 	\n  \n \nMERN Image Generation Website	  	 	 	 	 	                     	 Oct. 20	23	 &ndash; Dec .2023	 	\n▪ 	Independently conceptualized, designed, and developed a sophisticated image generation platform using the \nMERN (MongoDB, Express.js, React.js, Node.js) stack.	 	\n▪ 	Integrated cutting	-edge artificial intelligence capabilities by leveraging the OpenAI API for advanced image 	\ncreation, enhancing the platform&#039;s functionality and appeal.	 	\n▪ 	Employed MongoDB as the primary database solution to efficiently manage and store user data, ensuring \nseamless retrieval and manipulation of generated images.	 	\n  	\n					 	 	                    			 	\n▪ 		 	\n▪ 				 	\n	 	\n▪ 	 \nHTTP requests efficiently.	 	\n \nEDUCATION 	 	 	 	\nSharda 	University	  	 	 	 	 	                     	         	 	 	        	     	Aug .2021 	&ndash; Present 	 	\nB.tech	, Computer Science	  	 	 	 	    	 	 	     	        	     	           	Greater Noida	, U.P.	 	\n▪ 	CGPA 	&ndash; 8.9	 	 	 	 	 	 	 	 	 	         	     	Up until 	6th Semester	 	\n▪ 	Related Coursework : 	Computer Networks 	Operati	ng	 System, Database Management	 System, etc.	 	\n \nRam	-eesh International School (CBSE)	 	 	 	                     	         	              	April	 .20	19	 &ndash;July 2020	   	\nClass 12th	 	 	 	 	    	 	 	     	        	       	         	                        	Greater Noida	, U.P.	 	\n▪ 	Percentage	 &ndash; 84	 % 	\n 	\nRam	-eesh International School (CBSE)	 	 	 	                     	         	              	April .2017 	&ndash;July 2018  	 	\nClass 10th	 	 	 	 	    	 	 	     	        	       	                                 	Greater Noida	, U.P.	 	\n▪ 	Percentage 	&ndash; 91	 % 	\n  	\nCERTIFICATIONS, 	SKILLS &amp; INTERESTS	  	 \n▪ 	Certifications: 	JAVA Foundation	 	\n▪ 	Skills	 : Proficient in DSA, Strong Computer Science Fundamentals,	 Efficient at communicating issues,	 	\n Good	 System Design Understanding	 	\n▪ 	Interests	 : 						  	\n 	\n 	\nI am a Full Stack Developer with a passion for problem	-solving and a curious mindset. I embrace feedback 	\ngracefully, integrating it into my work to continually improve. Eager to expand my skills, I approach each task \nwith a willingness to learn and adapt w	ithin the job. My approachable nature and ability	 communicate ideas make 	\nme a valuable team member, fostering a collaborative environment where innovation thrives.	 	\nFeb . 202	4 &ndash; Mar .202	4	\nCompetitive Chess, Reading Technical Blogs, Linux Ricing , Avid Movie Critique	\nDeveloped a web scraping application using Node.js to generate internal links reports for websites.\nUtilized popular Node.js libraries such as 	`node-fetch	` for making HTTP requests and 	`jsdom	` for	\nImplemented URL normalization to ensure consistent URL formats using the Node.js URL object.	\n			\nGitHub link	\nparsing HTML responses.	\nWeb Cra	wler and Internal Links Analy	zer using Node.js', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-29 03:08:50', 0),
(468, 114, 77, NULL, NULL, '77_114_132377760266a707c28252b_Mohit_2021001021_Resume.pdf', 'Mohit_2021001021_Resume.pdf', 'MOHIT SARASWAT\nmohitsaraswat1703@gmail.com | (+91) 8130697855\nGreater Noida,India\nMohitSaraswat17 MohitSaraswat/ MohitSaraswat\nPROFESSIONAL SUMMARY\nPassionate and results-driven 4th-year Computer Science Engineering student specializing in full-stack\ndevelopment. Skilled in data structures and algorithms with a proven ability to solve complex problems and lead\nprojects to successful completion. Eager to leverage technical skills in innovative technology solutions.\nSKILLS\nTechnical Skills:- Full Stack Web Development (MongoDB,NodeJs,ReactJs,ExpressJs), MySql, Java, HTML, CSS,\nJavaScript\nCourse Work :- Data Structures and Algorithms, Computer Networks,DBMS,OOPs,Operating System.\nTools:- Git , Github, VS Code, MS Office, Oracle Cloud Infrastructure , Google WorkSpace\nSoft Skills:- Decision Making, Creative Thinking, Research&Analysis, Project Management\nEDUCATION\nBtech Computer Science | Sharda University ,Greater Noida CGPA: 8.358| (2021-25)\nXII (CBSE) | Father Agnel School, Greater Noida Percentage: 84%| 2021\nACADEMIC PROJECTS\nTask Management WebApp(TaskSync)\nDeveloped a MERN stack task management app with secure authentication, CRUD operations, and Cloudinary\nintegration for image uploads. Showcased expertise in React, MongoDB, ExpressJS, and NodeJS.\nTextUtils\nCreated TextUtils, a React web app for text manipulation, including case conversion, space removal, and word\ncount. Features include text preview, copy functionality, and light/dark modes for readability.\nStress And Anxiety Detection\nDeveloped a real-time stress and anxiety detection system using Python, OpenCV, and deep learning for emotion\nrecognition. Integrated live video monitoring with stress indicators, showcasing skills in image processing, facial\nrecognition, and machine learning.\nReact Portfolio Website\nCreated a personal portfolio website using ReactJS and Tailwind CSS, featuring a modern, responsive design and\ninteractive elements. Demonstrated expertise in frontend development and design frameworks.\nACHIEVEMENTS / CERTIFICATIONS\nResearch Paper:- Presented my paper on stress and anxiety detection at ICTACS 2023, showcasing a real-time\nfacial expression analysis system using Python and deep learning. The paper is published by IEEE.\nUdemy:- Java In-Depth : Become Complete Java Engineer!\nOracle Academy:- Database Foundations | Database Programming with SQL\nDevTown:- JavaScript and React\nINTERESTS / HOBBIES\nGaming\nTravelling\nCooking', 0, 1, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-07-29 03:08:50', 0),
(469, 115, 77, 59, NULL, '77_115_197236027766a73687eb2ca_MOHIT_SARASWAT.docx', 'MOHIT SARASWAT.docx', '\r\nMOHIT SARASWAT\r\nmohitsaraswat1703@gmail.com | (+91) 8130697855\r\nGreater Noida,India\r\nMohitSaraswat17 MohitSaraswat/MohitSaraswat\r\nPROFESSIONAL SUMMARY\r\nPassionate and results-driven 4th-year Computer Science Engineering student specializing in full-stack development. Skilled in data structures and algorithms with a proven ability to solve complex problems and lead projects to successful completion. Eager to leverage technical skills in innovative technology solutions.\r\nSKILLS\r\nTechnical Skills:- Full Stack Web Development (MongoDB,NodeJs,ReactJs,ExpressJs), MySql, Java, HTML, CSS, JavaScript\r\nCourse Work :- Data Structures and Algorithms, Computer Networks,DBMS,OOPs,Operating System.\r\nTools:- Git , Github, VS Code, MS Office, Oracle Cloud Infrastructure , Google WorkSpace\r\nSoft Skills:- Decision Making, Creative Thinking, Research&amp;amp;Analysis, Project Management\r\nEDUCATION\r\nBtech Computer Science | Sharda University ,Greater Noida   CGPA:  8.358 (2021-25)\r\nXII (CBSE) | Father Agnel School, Greater NoidaPercentage:  84% 2021\r\nACADEMIC PROJECTS\r\nTask Management WebApp(TaskSync)\r\nDeveloped a MERN stack task management app with secure authentication, CRUD operations, and Cloudinary integration for image uploads. Showcased expertise in React, MongoDB, ExpressJS, and NodeJS.\r\nTextUtils\r\nCreated TextUtils, a React web app for text manipulation, including case conversion, space removal, and word count. Features include text preview, copy functionality, and light/dark modes for readability.\r\nStress And Anxiety Detection\r\nDeveloped a real-time stress and anxiety detection system using Python, OpenCV, and deep learning for emotion recognition. Integrated live video monitoring with stress indicators, showcasing skills in image processing, facial recognition, and machine learning.\r\nReact Portfolio Website\r\nCreated a personal portfolio website using ReactJS and Tailwind CSS, featuring a modern, responsive design and interactive elements. Demonstrated expertise in frontend development and design frameworks.\r\nACHIEVEMENTS / CERTIFICATIONS\r\nResearch Paper:- Presented my paper on stress and anxiety detection at ICTACS 2023, showcasing a real-time facial expression analysis system using Python and deep learning. The paper is published by IEEE.\r\nUdemy:-Java In-Depth : Become Complete Java Engineer!\r\nOracle Academy:-Database Foundations | Database Programming with SQL\r\nDevTown:-JavaScript and React\r\nINTERESTS / HOBBIES                                                                  \r\nCooking\r\nTravelling                                                                                                       \r\n', 2, 2, 1, 'Recruiter', 'SL', 'N', 14, 1, '2024-08-01 06:31:47', '2024-07-29 06:31:47', 0, NULL, NULL, '2024-07-29 06:28:23', 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
(470, 116, 73, 41, NULL, '73_116_13905622166ac3b7a82fc9_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, '2024-08-05 01:53:34', '2024-08-02 01:53:34', 0, NULL, NULL, '2024-08-02 01:50:50', 0),
(490, 117, 76, NULL, NULL, '76_117_162646246066b4bd1a5ceae_1_VinayChaudhari_DataScientist_6yr_updated_on_202406_02GenAI_1720595461567_Vinay_Chaudhari_.pdf', '1.VinayChaudhari_DataScientist_6yr_updated_on_202406_02GenAI_1720595461567_Vinay Chaudhari .pdf', 'Vin ay C hau d hari \nData  S cie n tis t \nExp erie n ce d  D ata  S cie n tis t w it h  \n6 y e ars\n i n  \nML,\ngen era tiv e  A I, a n d  p re d ic tiv e  a n aly tic s\n, s e ekin g  t o\nin no va te  i n  \nGen A I p ro je cts\n. \nvin ay ch au d hari1 996@ gm ail .c o m  \n+91 8 484991328 \nPune, I n d ia  \nlin ke d in .c o m /in /v in ay -c h au d hari- a i \nmed iu m .c o m /@ vin ay 1 996 \nWORK  E X PER IE N CE \nData  S cie n tis t \nBrid gesto ne E M EA  \n01/2 023 -  P re se n t\n, \n  (R em ote ) P un e, I n dia  \nGlo bal l e a d er i n  m obil it y  s o lu tio n &amp;  t y re  m an ufa ctu rin g \nRole : \nI d eve lo ped  M L &amp;  a n aly tic s s o lu tio ns f o r i n te rn al s ta ke h o ld ers  a n d\nsu b sid ia rie s a cro ss t h e E M EA  r e g io n. \nLLM -B ase d  C usto m er R evie w  A naly sis\n: I m pro ve d  c u sto m er s a tis fa ctio n b y\nid en tif y in g  c o m mon p ro duct i s su es a n d  a re as f o r i m pro ve m en t. U se d  O pen ai\nGPT-4  m odel &amp;  R AG  o n c u sto m er r e vie w  d ata  \nDem an d  F o re ca stin g : \nDesig ned  a n d  i m ple m en te d  1 0+ u niq ue f o re ca stin g\nmeth o do lo gie s a cro ss E u ro pe, o ptim iz in g  5 000+ p ro duct S K U s a n d  i n te g ra tin g\nLa rg e L a n g uag e M odels  ( L LM s) f o r s c a la b le  s o lu tio ns. \nApplie d  R ese arc h : \nCond ucte d  g ro und bre akin g  r e se arc h  o n m ult i- t im e s e rie s\npre d ic tio n a t s c a le , e n han cin g  c o m puta tio nal e ﬃ cie n cy  b y 8 0%  a n d  i n cre asin g\nfo re ca stin g  a ccu ra cy  b y 2 5% . \nTe ch  s ta ck : \nNeu ra lF o re ca st, S ta ts F o re ca st, L la m aIn dex ,  l la m a, \nHuggin g F a ce\n,\npysp ark , p an das, A zu re  D ata b ric k s, O pen A I\n \nSe n io r D ata  S cie n tis t -  P ro duct D eve lo pm en t \nAays A naly tic s \n01/2 022 -  1 2/2 022\n, \n  (R em ote ) M um bai, I n dia  \nSe a so ned  v e n do r f o r G en A I &amp;  a n aly tic s \nRole :\n I  c re ate d  N LP  a n d  A uto M L p ro duct a n aly tic s s o lu tio ns f o r c o rp o ra te  f o r\nFo rt u ne&#039;s  1 00 c lie n ts  \nZero -s h o t l iv e  t ra n sc rip ts  c la ssiﬁ ca tio n: \nIm ple m en te d  t o pic  m odelin g  u sin g\nHug gin g  F a ce  B A RT-L a rg e-M NLI f o r z e ro -s h o t c la ssiﬁ ca tio n o n L iv e C hat\ntra n sc rip ts , e xtra ctin g  i n sig hts  t o  g uid e b usin ess d ir e ctio n f o r t h e S e n io r\nLe ad ers h ip  T e am  \nUtil iz e d  L D A  m odel \nin  G en sim  t o  i d en tif y  k e y t o pic s f ro m  t h e t ra n sc rip ts  d ata ,\nto  g uid e t h e b usin ess d ir e ctio n f o r t h e p ro duct t e am . \nML P ro duct D eve lo pm en t:\n  Deve lo ped  s c a la b le  M L a rc h it e ctu re  a n d  M LO ps\nwork ﬂ ow s w it h  a u to  m odel s e le ctio n, M Lﬂ ow  t ra ck in g , a n d  C I/ C D  p ip elin e,\nbo ostin g  d ata  s c ie n ce  p erfo rm an ce . \nTe ch  s ta ck : \nHuggin gfa ce , T ra n sfo rm er, \nGen sim , N LT K , P ysp ark , p an das, A zu re\nData b ric k s, M lﬂ ow , A zu re  D evO ps\n \nData  S cie n tis t \nConnectin g D ots  I n fo te ch  \n11/2 019 -  0 1/2 022\n, \n  Pun e, I n dia  \nEnd-t o -e n d C re a tiv e  a n d T e ch  S e rv ic e s H ouse . \nRole : \nCore  c o ntrib uto r f o r d ra g -a n d -d ro p, n o -c o de s o lu tio n |  D eve lo ped  s c a la b le\nML/N LP\n m odel f o r \nre al- t im e t ic k e t r e so lu tio n\n |  C re ate d  \npre d ic tiv e  e n g in e\n f o r\nweb  s e rie s s u cce ss |  B ooste d  e -c o m merc e  s a le s b y 3 0%  w it h  \nre co m men d atio n\nen g in e\n |  D esig ned  u se r-f rie n d ly  \nAuto M L/A uto A I\n c o m po nen ts . \nJr. D ata  S cie n tis t \nMaxg en  T e ch n o lo gie s \n09/2 018 -  0 9/2 019\n, \n  Pun e, I n dia  \nWeb  d eve lo pm en t s e rv ic e s \nRole :\n  In d ep en d en tly  d eve lo ped  M L s o lu tio ns f o r a d -h o c t a sk s a n d  i n te g ra te d\nasp ect-s e n tim en t a n aly sis  f o r H IN GLIS H  m ed ia  c o m men ts\n, e n han cin g  w eb\nse rie s c o nte n t s tra te g ie s. \nSK IL L S  \nPyth o n \nAI S o lu tio ns D eve lo pm en t \nMach in e L e arn in g  \nDeep  L e arn in g  \nData b ric k s \nTim e S e rie s F o re ca stin g  \nNLP  \nLLM  \nRAG  \nMLF lo w  \nAI \nModel D ep lo ym en t \nClo ud  P la tfo rm s ( A W S, A zu re ) \nLa n g ch ain  \nGen A I \nED UCATIO N \nPune U niv e rs it y  \nBE i n  I n fo rm atio n T e ch n o lo gy ( 7 8% ) \n06/2 014 -  0 6/2 018\n, \n \nPun e, I n dia  \nACH IE V EM EN TS \nDeve lo ped  L LM  b ase d  s o lu tio n \nEnh an cin g c o m pu ta tio nal e ﬃ cie n cy  b y 8 0%  a n d i n cre a sin g\nfo re ca stin g a ccu ra cy  b y 2 5% . \nDeve lo ped  E arly  M ed ia  c o nte n t p re d ic tio n\npla tfo rm  \nOTT m ed ia  w eb  s e rie s s u cce ss o r f a il u re  p re d ic tio n b efo re  i t\nla u n ch  \nONLIN E C O URSE S &amp;\nCER TIF IC ATIO NS \nOra cle  C lo ud  I n fra stru ctu re  2 024 G en era tiv e  A I\nCert iﬁ ed  P ro fe ssio nal \nOra cle  \nLLM  :  A pplic a tio n T h ro ug h P ro ductio n \nData b ric k s \nData b ric k s G en era tiv e  A I F u nd am en ta ls  \nData b ric k s \nAW S M L S ch o lo rs h ip  \nUdacit y  \nNeu ra l N etw ork s &amp;  D eep  L e arn in g  \nDeep Le a rn in g.A I \nIN TER EST S \nRead in g  \nWrit in g  \nPla y in g  C hess \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', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 0),
(491, 117, 76, NULL, NULL, '76_117_31620570466b4bd1a5dceb_Abhay_Kumar_24_2.pdf', 'Abhay_Kumar_24_2.pdf', '', 2, 3, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 0),
(492, 117, 76, NULL, NULL, '76_117_206997324566b4bd1a5deb5_Amit_Jain_Data_Science_Resume_2024.pdf', 'Amit_Jain_Data_Science_Resume_2024.pdf', 'Public	 	\n                	 	\n \n \n     	     	 	\n \n \n \n \n \nPROFILE SUMMARY	 	     	        	PROFESSIONAL EXPERIENCE	 	\n 	\n&bull; 	6.5+  YoE	 	in  Data  Science  roles  across 	\nindustries.	 	\n&bull; 	Thorough  understanding  of  Data  Science \ntools, techniques and technologies in Machine \nLearning,	 Deep  Learning,  Natural  Language 	\nProcessing	 	(NLP)	 	Using	 	Python,  R	 	\nprogramming.	 	\n&bull; 	Thorough  understanding  of  algorithms  like \nRegression, 	Classification,	 	Clustering, 	\nForecasting,  Anomaly  Detection,	 Time  series 	\nModelling etc.	 	\n&bull; 	Sound  knowledge  of  deployment  using  Git, \nDocker, Jenkins, 	Kubernetes, OpenShift	. 	\n&bull; 	Sound knowledge of Azure Machine Learning \nStudio,  AWS  (Amazon  Web  Services)  AI	-ML 	\nServices.	 	\n&bull; 	Extract	ed	 usable  data  from  valuable  data 	\nsources	. 	\n&bull; 	Carr	ied	 out  preprocessing  of  structured  and 	\nunstructured data	. 	\n&bull; 	Analyz	ed	 large amounts of information to find 	\npatterns and solutions.	 	\n&bull; 	Developed  prediction  systems  and  machine \nlearning algorithms.	 	\n&bull; 	Propose	d solutions  and  strategies  to  tackle 	\nbusiness challenges.	 	\n 	\n   	\n&bull; 	Total 1	4+ 	YoE	. 	\n&bull; 	6.5+	 YoE	 in Analytics, Machine Learning, Data 	\nScience.	 	\n&bull; 	7.8 YoE	 in Academics.	 	\n 	\n      	DATA SCIENTIST	 	\n&bull; 	Data Scientist at 	Wipro	, Pune Since 	Mar	 202	2 &ndash; 	\nTill date	 	\n&bull; 	Data  Scientist  at  Equations  Work  IT  Services \nPvt. Ltd., Pune Since Sept 2020 	to Feb 2022	 	\n&bull; 	Data Scientist at Cloudmantra, Pune since Mar \n2020 to Sept 2020	 	\n&bull; 	Data Scientist at Open Insights, Pune since Aug \n2019 to Feb 2020.	 	\n&bull; 	Data  Scientist  at  TorcAI  Digital  Media  Private \nLimited, Pune since Feb 2019 to Jul 2019	 	\n&bull; 	Data  Analyst  at  Findability  Sciences, \nAurangabad since Jan 2018 to Jan 2019.	 	\n       	 	\n      	ACADEMICS	 	\n&bull; 	7.8+  YoE	 Teaching 	experience  as  assistant 	\nprofessor  in  engineering  colleges  since  Aug \n2009 to Mar 2017	 	\n 	\nEDUCATIONAL QUALIFICATION	 	     	PROGRAMMING SKILLS &amp; TOOLS	 	\n 	\n&bull; 	PGP	-2018	 	in  Data  Science,  Business 	\nAnalytics &amp; Big Data in association with IBM	 	\nfrom  Aegis  School  o	f Data  Science	, Cyber	 	\nSecurity	 &amp; Tele	communicati	on	,  Mumbai 	\n(M.H.)	 	\n&bull; 	M.Tech.	-2014	 from  university:  B.U.  Bhopal 	\n(M.P.) with 73%	 	\n&bull; 	PGDIT	-2008	 	from  Indian  Institute  of 	\nTechnology,  Kharagpur  (W.B.)  with  6.67 \nCGPA.	 	\n&bull; 	B.E.	-2006	 from  University:  R.G.P.V.  Bhopal 	\n(M.P.) with 73.16%	 	\n 	\n&bull; 	Programming Languages:	 Python	, R  	\n&bull; 	Software Tools/Technologies:	 Machine Learning, 	\nDeep  Learning,  Natural  Language  Processing \n(NLP), AWS 	AI-ML, Azure 	 Machine Learning	 	\n&bull; 	Databases:	 MySQL, PostgreSQL	, Db2	 	\n&bull; 	Operating System:	 Windows, Linux/Unix	 	\n&bull; 	Authoring Tools:	 Microsoft Office, Open Office	 	\n&bull; 	BI Tools/ Data Reporting 	Tool:	 Qlik Sense	 	\n&bull; 	Version Control:	 GIT	 	\n&bull; 	Model Deployment Tool:	 Heroku, AWS, Azure	 	\n&bull; 	Cloud platform:	 IBM	, AWS, Azure	, GCP	 	\n&bull; 	Project 	M	anagement 	Too	l: Jira, 	GitHub	 	\n 	\nAmit Jain	 	\nData Scientist	 	\n  amitjain2110@gmail.com	 	\nlinkedin.com/in/amit	-jain	-83292740/	 	\n  youTube/amit	-jain	 	\n  github.com/amitjain2110	 	\n 917	9982256\n\nPublic	 	\nWIPRO	 PROJECTS	: 	\n \nProject Title: 	Space Insights	 	\nProject Profile: 	To Build AI model to predict about Ideal sharing ratio	. 	\nRoles &amp; Responsibility: 	 	\na. Analysis to build a machine learning model for Ideal sharing ratio.	 	\nTools/Technologies used:	 Python, 	IBM Maximo Monitor	 	\n \nProject Title: 	Tririga Building	 Insights	 	\nProject Profile: 	To Build	 AI model for 	TBI.	 	\nRoles &amp; Responsibility: 	 	\n    	a. 	Create Anomaly detection model and other AI models for 	OpenShift	 Platform (OCP)	 	\n    	b.  	Successful transition of project from Kubernetes to 	OpenShift	 Platform	 in IBM Cloud	 	\n    	c.     	PostgreSQL to Db2 migration  	 	\n    	d.  	Installation of modules like IoT, cp4d(WML), 	Monitor etc.	 	\n    	e.  	Responsible to run security Scan (Static, Dynamic, 	white source	, mend, PVR, 	twist lock	) 	\n Tools/Technologies used: 	Python, Machine Learning, IBM Maximo Monitor	, IBM 	Cloud,	 Openshift Cluster,  	 	\n                                            	Kubernetes	 	\n \nEQUATIONS WORK PROJECTS:	 	\n \nProject Title:	 Sales forecasting and Demand Forecasting	 	\nProject Profile:	 To forecast the sales and revenue of e	-commerce company.	 	\nRoles &amp; Responsibility: 	 	\na. Build the model using LSTM Time Series	 Modelling.	 	\nTools/Technologies used:	 Python, Azure 	Machine Learning	 	\n \nProject Title:	 Prediction of Motor Speed &amp; temperature 	 	\nProject Profile:	 To predict the temperature and deployed it using Power platform.	 	\nRoles &amp; Responsibility: 	 	\n    	a.  	End to end model creation &amp; deployment	 	\n    	b.  	Build the model using 	Random Forest	 regression	 and XGBoost 	regression.	 	\n    	c.  	Enabled to run the project in Azure Power Platform.	 	\nTools/Technologies used:	 Python, Azure Machine	 Learning Studio, Power App, Power Automate	 	\n \nProject Title:	 Prediction /Analysis of Horse Race	 	\nProject Profile: 	 	\na. To predict which horse will win the race.	 Also, 	decide	 the position of all the horses.	 	\nRoles &amp; Responsibility: 	 	\na. 	Responsible for prediction 	of result 	using 	Random 	Forest	 classification	, XGBoost	 classification	 and ANN 	    	\nclassification	 model.	 	\n    	b.  	Requirement collection from client.	 	\n    	c.  	Schedule and planning for project execution. 	 	\nTools/Technologies used:	 Python, Machine 	learning	 	\n \nProject Title:	 Text summarization of audit files	 	\nProject Profile:	 To read text from 	audit 	reports	(pdf	) and	 summari	ze	 text	 report	. 	\nRoles &amp; Responsibility: 	 	\n    	a. 	Responsible for text extraction	 using AWS Textract 	and summarization	 using BERT	 library	. 	\n    	b.  	 Requirement collection and deployment.	 	\nTools/Technologies used:	 Python, NLP, A	mazon	 Machine learning, AWS Textract, 	Amazon S3, 	Git, Docker, 	  	\n       	Jenkins\n\nPublic	 	\nCLOUDMATRA	 PROJECTS	: 	\n \nProject Title:	 Specific text extraction of audit reports 	 	\nProject Profile	: To extract specific text and its 	related	 data with units from audit reports and publish &amp; analyze	. 	\nRoles &amp; Responsibility: 	 	\n   a. 	Responsible for text extraction using AWS	 Textract	. 	\n   b. 	Discussion with project planning team	 	\nTools/Technologies used:	 Python, NLP, A	mazon 	Machine 	Learning	, A	mazon	 SageMaker, AWS Textract, A	mazon	   	\n       	Comprehend	 	\n \nOPEN INSIGHTS	 PROJECTS	: 	\n \nProject Title:	 BIFE 	- Banking Intension Fulfillment	 Engine (CLTV Module)	 	\nProject Profile:	 To predict customer lifetime value,	 the amount of revenues that you 	expect to generate	 from a 	  	\n  customer during the period over which	 your service will be of value. 	 	\nRoles &amp; Responsibility:	 	\n    	a. 	Responsible for developing software.	 	\n    	b. 	Wrote down test cases for checking the	 functionality of various 	functions.	 	\nTools/Technologies used:	 Python, Machine 	learning	 	\n \nTORCAI	 PROJECTS	: 	\n \nProject Title:	 Zirca Campaign	 	\nProject Profile:	 To collect advertiser campaign	 information based on 	distinctive features	 performance to predict 	  	\n                         	and	 recommend	 blacklist &amp; whitelist values.	 	\nRoles &amp; Responsibility: 	 	\na. Responsible for collecting	 data 	using Spark 	and analysis	 data using keywords and 	based on	 result create 	\nblacklisted and whitelisted features	. 	\nTools/Technologies used	: Spark, Scala	 	\n \nFINDABILITY SCIENCES	 PROJECTS	: 	\n \nProject Title:	 Ajinomoto Price prediction	 	\nProject Profile:	  To predict the price of product	 after every week, after 1 month, 	after 2 months and after 3 	  	\n                           	months	 value.	 	\nRoles &amp; Responsibility: 	 	\na. Build the model using 	Linear, 	Random Forest	 regression 	and XGBoost regression.	 	\nb. Responsible for EDA, deliver insights and	 prediction result.	 	\nTools/Technologies used:	 R - Programming	, Machine learning	 	\n \nProject Title:	 Net promotor score 	 	\nProject Profile:	 Classification of user sentiment for various telecom plans. 	 	\nRoles &amp; Responsibility: 	 	\na. 	Build the model using 	Logistics regression, 	Random Forest	 classification	 and 	Na&iuml;ve Bayes	 classification.	 	\nb. 	Responsible for predicting classification report.	 	\nc. 	Responsible for EDA, deliver insights and prediction result.	 	\nTools/Technologies used:	 R - Programming	, Machine 	Learning', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 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
(493, 117, 76, NULL, NULL, '76_117_156178935966b4bd1a5e0c2_CV_Architect__Amol_Naik.pdf', 'CV_Architect__Amol_Naik.pdf', 'Resume of Amol	 	 	Page 	1 of 	9 	\n                    	                    	 	            	       	 	              	\n 	\n 	\nAMOL	 HIRAMA	N NAIK	 	\nFLAT NO 	403	 BLDG	 TULIP 	ADITYA 	GARDEN CITY 	PHASE 	5  PUNE CITY 	PUNE 	(CB)	  411058	 	\n Mob: 	9356997358 	Email	: amolhiramannaik	@gmail	.com	 	\n \nEXECUTIVE 	PROFILE	. 	\n 	Around	 17 years of 	experience in	  Designing 	Web,	 Win	dow 	and Cloud Native 	Applications	. 	\n 	7+  years of  experience in  Solution architecture  and 	developing 	End  to  End 	complex  Single	-Page  Responsiv	e 	\nWeb Applications	 	\n 	7+ years of experience in designing, implementation a	nd architecting the cloud solution	-AWS,GCP,Azure	 	\n 	6+  years  of  experience  using  AWS,  ideally including  comfort  with  the  majority  of  the  following  services  (or \nequivalent):  EC2,  S3,  CloudFront,  Lambda,  IAM,  Route  53,  ECR,  ECS, 	EKS,	CodeBuild,  CodeDeploy, 	\nCodeP	ipeline, SNS, CloudWatch	,Datadog,AWS Neptune,AWS Control Tower	 	\n 	7+ years of rich experience in 	UI 	Architect	ing Scalable, Secure 	Web solutions	. 	\n 	9+ years 	of  experience  as  Full  stack  developer  in  building  web  App 	UI  Design, 	Micro  Frontends  using 	\nAngular2/4	/6	/8	/10	,AngularMaterial,	JavaScript	,HTML	5,ReactJS,	MongoDB,	Cassandra,	Microservices	,Spring	\nBoot,NestJS	,.Net Core 3.0	 	\n 	5+ years of client 	facing 	experience worked	 on 	cross	-functional	 teams for resolving various functional issues 	\nand gathering appropriate requirement	s.  	\n 	3+ years of working experience on Developing Window Applications using WPF with MVVM	 Pattern	 	\n 	Support	ed 	the  business  development  lifecycle  (Business  Development,  Capture,  Solution  Architect,  Pricing 	\nand Proposal Development)	 	\n 	Strong  knowledge  of  Amazon  K	inesis,  AWS  Lambda,  Amazon  Simple  Queue  Service  (Amazon  SQS), 	\nAmazon Simple Notification Service (A	mazon SNS),EC2,S	ssss	3,Bucket,ALB.	 	\n 	Strong knowledge with Web Services, API Gateways and application integration development and design	. 	\n 	 GCP Knowledge of Clou	d Function,Google Kubernetes Engine(GKE),Cloud Pub/Sub,Cloud Load Balancing	 	\n 	Skilled 	in Code Optimization, Review,	 Perfor	mance Tuning for web application	 and SQL	 server 	 Database	 	\n 	 Implementation  of  design  patterns  such  as  Singleton, 	Factory,  Abstract	 Factor	y,  Command	,  Adapter	,  	\nObserver 	in .Net	 	\n 	 Implementation of Software Design Principle, SOLID Principles	 	\n 	Worked on Dependency Injection for code refactoring and loose coupling	 	\n 	 Extensively used core 	.Net technologies like 	LINQ, SOAP Web Services, WCF	 	\n 	 Extensi	vely used Microsoft Tools like Enterprise Library, Entity Framework, etc	 	\n 	 Experience in writing Reporting 	Services	 Rendering, Delivery and Data Source Extensions	 	\n 	 Experience  in  providing  Proposals,  Estimations  (Task  Ba	sed  and  Function  Point)  for  New 	Develo	pment, 	 	\nReengineering and Sustained Engineering projects	 	\n 	 Well  versed  with  complete  Software  Development  Life  Cycle  (SDLC)  process  which  includes	 Design, 	\nConstruction, Testing and Deployment	 	\n 	 Created UI Library using	 Angular Material and Storybook	 componen	t Library.	 	\n 	Proficient 	knowledge in SSO,	 Saml,	 OpenIDConnect, OAuth 2.0	 	\n 	Experienced in working on RFP	 and 	Presales	 	\n 	Worked  with  DevOps  tools  Jenkins  for  Continuous  Integ	ration, 	Deployment,  JIRA	 for  project  Management 	\nand Confluence for 	keeping project	 relate	d documents.	 	\n 	Worked with testing tools framework Jasmine, Karma and Protractor	 	\n 	Worked with 	IIS and .Net Assemblies	 during application deployment.	 	\n 	Profound knowledge in working with 	RD	BMS includes MS SQL Server 2012	\\2008	, Oracle	11g	 	\n 	Excellent skills in writi	ng 	stored 	procedures, T	-SQL 	Queries, 	functions, triggers, views	 and schemas.	 	\n 	Good Experience with Unified Modeling Language(UML) standards and documentation and experience	 	\nIn preparing 	Class 	Diagrams, Sequence	 Diagrams using	 design tools 	such as Microsoft 	Visio.\n\nResume of Amol	 	 	Page 	2 of 	9 	\n 	Performed  Unit  Testing  using  tool  NUnit 	and	 performed  several  integration 	testing,  System	 testing  and 	\nperformance testing.	 	\n 	Strong  analytical  and  dynamic  trouble  shooting  skills coupled  with  excellent  communication  skills  and  able \nto work individuall	y and as a team.	 	\n 	Basic knowledge of Generative AI(Currently attending classes on Generative AI with Great Learning)	 	\nCERTIFICATION	 	\n 	\n 	TOGAF 9(Combined Level 1 &amp; 2) Certified Professional	 	\n 	Google Professional Cloud Architect	 	\n 	AWS  Certified Solutions Architect	-Associate	 	\n 	Microsoft Certified: Azure Solution Architect Expert	 	\n 	SAFe 4.0 Agile Certified Professional	 	\n 	Microsoft Certified: Azure AI 900 Fundamentals	 	\n 	Generative AI for Business with MSFT Azure Open AI Program	 	\n 	\nORGANIZATIONAL EX	PERIENCE	 	\n6 Jan 2022 to till date	          	T-Systems as	 Senior Technical Architect.	 	\nApril 2021	 to 	4 Jan 2022	     	HCL Technologies 	as Senior Technical Architect	 	\nMay 2019 to 29 Jan 	2021 	   Western	 Union	 Technology 	Engineering as	 Solution Architect.	 	\nMay 17 to 	April 2019	       	  Infosys, Pune	 as Technology Architect	 	\nNov&rsquo;11 	 - May 17	 	Tata 	Consultancy	 Services, Pune as Assistant Consultant	 	\nSep&rsquo;10 	&ndash; Nov&rsquo;11	  	Syntel Ltd., Pune as Analyst Programmer	 	\nJul&rsquo;08 	&ndash; Aug&rsquo;10	  	Acidaes Solutions Pvt. Ltd., Mumbai as Engineer 	- Application Development Group	 	\nJan&rsquo;	08 	&ndash; Jul&rsquo;08	 	 	Orion India Systems Pvt. Ltd., Mumbai as Software Developer	 	\nApr&rsquo;07 	&ndash; Jan&rsquo;08	  	IL &amp; FS Education &amp; Technolo	gy, Mumbai as Software Developer	 	\n \n \nCAREER 	FOCUS	 	\n 	Enterprise  application  |  Solution  Architect  |  Cloud  Migration  |Digital  Transformation  |  M	icroservices  | 	\nStrategic  Planning &amp;  Execution  |  Leadership  &amp; Team  Building  |Customer  Relationship  | Generative  AI  for \nBusiness	 	\nTECHNICAL 	SKILL 	SET 	\n \nProgramming Languages	 	C#,JAVA, Typescript	 	\nJavaScript  Framework  &amp; \nLibrary	 	\nAngular	 14, NodeJS	,Javascript, Boo	tstrap	,ReactJS,Angular	Material,	 	\nStorybook UI Component 	library, Web Component	,SpringBoot	,NestJS	 	\nDatabase	 &amp; No SQL DB	 	SQL Server 2012	\\2008	,Oracle11g	,MongoDB	,Casandara	 	\nMiddleware	 	Microservices	,Kafka	,RabbitMQ	,Springboot	,Python	,Micronaut	 	\nBuild  Packaging  Too	l 	and 	\nFramework	 	WIX 3.7	,MSBuild	,Angular CLI,Gulp	 	\nModeling 	 and Design Tools	 	UML,MS Visio	,Enterprise Architect	 	\nTestingTools Management and \nFramework	 	NUnit	,Jasmine,Karma,Protractor	,SonarQube,Resharper,HP ALM	 	\nVersion Control Tools	 	MS Visual Source Safe(VSS	),SVN,TFS	,Perforce,JIRA	,Github	 	\nDimension	 	\nCloud 	 Computing	 	\nAWS	EC2,RDS,S3,Glacier,SQS,SNS,VPC,CloudFormation,IAM,Route53	\n,EBS,Lambda,Kinesis,API  Gateway,ALB	 GCP	-Cloud  Function,Google 	\nKubernetes  Engine(GKE)  Cloud  Pub/Sub,Cloud  Load \nBalancing.	Azure	 Event Hubs,	API Management,Storage,Queues,	 	\nSecurity	,AWS Datadog,AWS Neptune,AWS Control Tower	 	\nOperating System	 	Win 95/98/NT/XP	 /Win 2003	/Win 2007	 	\nDevOps 	 	Jenkins, 	JIRA	, Docker	, Kubernetes	,OpenStack\n\nResume of Amol	 	 	Page 	3 of 	9 	\n \n \n \nPROJECTS 	EXECUTED 	 	 	\n \nT-Systems as Senior Technical Architect	 	\nDuration: January 2022 to Till Date	 	\nProject: LogisticBus: The LogisticBus is a system used 	Daimler	 for supplying parts of vehicles to Retailer.	 	\nLogisticBus  systems  consists  of  Modules  like  Dealer  Inventory  Management  Systems,  Stock  Information  and \nControll	ing 	Systems	. When	 retailer, systems, places the order	 checks if the part is availab	le with wholesaler.	 	\nAbout  90%  parts  ordered  by  retailer  are  available  with  corresponding  wholesaler.  This  is  possible  due  to \napplication such as systems demands and Forecast	 applications. But if it is not available with wholesaler then the 	\nrequest goes to central warehouse and retailer is informed after how many days his demand will be fulfilled	 	\n 	Responsible for delivering architecture guidelines for LogisticBus Modernization 	Application.	 	\n 	Le	d development team in 	Modernization	/Transformation 	LogisticBus	 legacy Application.	 	\n 	Involved 	in 	the 	requirement gathering m	eetings with Product owner. 	 	\n 	Created the Micro services Orchestration layer for 	retailer order, Transferring order deta	ils to other systems.	 	\n 	Worked with the UX designer in designing the wireframes like lending page with the main components.	 	\n 	Design, both technically compliant and secure Cloud solutions, as well as value	-based, on	-demand services to 	\nfacilitate the effective 	transition and migration of projects and p	rograms into 	unique 	cloud	 environment	. 	\n 	Design and implemented AWS Simple S	torage Services to store sales inventory information.	 	\n 	Worked with the EC2 instances to host the 	Micro services	 and the Application.	 	\n 	Involved	 in creating the VPC used cloud Formation Template	 	\n 	Used the Hystrix Library to implement the circuit pattern for 	Micro services	. 	\n 	Implemented the AWS API Gateway for 	Authorization, caching	 and storing the  REST API  Response.	 	\n 	Involved in exploring the cloud	 agnostic architecture AWS,Azure and GCP	 	\n 	Involved 	in Deploying	, Monitoring and Hosting of the 	Micro service	. 	\n 	Used Angular Material	 to design	 and build up a multi 	layered System	. 	\n 	Used Sonar Qube to 	monitor	 the Code Quality Metrices.	 	\n 	Involved in code review 	and approve the Pull Request	 	\n 	Led the deployment of  the code builds and helping in continuous integration and deployment.	 	\n 	Used JIRA, Remedy to create user stories ,is	sues, plan.	 	\n 	Involved in creating the Database Model	. 	\nEnvironment: 	Visual Studio Code, 	AWS 	Cloud.	Angular	 12, Typescript,HTML5, 	\nCSS,JIRA,,AngularC	LI,Angular Material PostgreSQL,	Kafka,Amazon Web 	\nservices,Docker,Gitlab,NodeJS,Java,SpringBoot	,Kubernetes,	IntellijIDEA,	 	\n \nHCL Technologies as Senior Technical Architect	 	\nDuration	 April 2021	 to January	 2022	 	\nProject:  Working on a project to 	enhance	 secured password system for a US based client	. 	\nEnvironment: 	C#	, Web	 Services	, WPF, SQL	 Server	 	\n \nWestern 	Union, Pune	 	\nDuration: 	May 2019	 to 29 Jan 2021	 	\nProject:	 iWatch	,RTRA,Transvision  applications  are  involved  in 	case  management  application  that	 provides 	\ncompliance officers, 	investigators and  analysts  the  ability  to  create 	and/or  review information  about	 a  subject  or 	\ngroup of subjects for the purposes	 of investigation, assessment, 	and intelligence maintenance. iWatch	 was crea	ted 	\nin response to requirements 	from the Global Compliance organization and is intended to serve	 as a single &ldquo;source 	\nof truth&rdquo; 	for compliance activities globally includin	g those compliance user groups.	An iWatch case can be for any 	\nsubject such as 	an Agent, a consumer, a geography or a group/network of Agents and/or Consumers.	 	\nRTRA is a Real Time Risk Analysis application provides the details about the 	customers	. 	\nTransvision  is  a  read  only  web 	application  used	 by  the  Agents  to  monitor 	the  suspicious	 activity  on  the 	\ntransactions.	 	\n \nResponsibilities:	 	\n 	Responsible 	for delivering architecture	 guidelines	 for iWatch Modernization Application.	 	\n 	Le	d development	 team in 	Modernization	/Transformation iWatch	 legacy Application.	 	\n 	Involved 	in 	the 	requirement gathering	 meetings with 	Product owner	.  	\n 	Created the 	Micro services Orchestration	 layer for Case creation, Case bulk load, Case push ,Case search, 	\nCase Integration with other application.	 	\n 	Worked with the UX designer in designing the wireframes like lending page with	 the main components	.\n\nResume of Amol	 	 	Page 	4 of 	9 	\n 	Design, both technically compliant and secure Cloud solutions, as well as value	-based, on	-demand services to 	\nfacilitate the effective transition and migration of projects and p	rograms into unique 	 cloud environment	. 	\n 	Design	 and impleme	nted AWS Simple Storage Services to store and retrieve user specific kyc document	 	\n 	Worked with the EC2 instances to host 	the Microservices	 and the Application.	 	\n 	Involved in creating the VPC used cloud Formation Template	 	\n 	Used the Hystrix Library to implement 	the circuit pattern for Microservices.	 	\n 	Implemented the AWS API Gateway for Authorization,caching and storing the  REST API  Response.	 	\n 	Involved in exploring the cloud 	agnostic architecture 	AWS	,Azure and GCP	 	\n 	Involved in  Deploying, Monitoring and Hosting of 	the Microservice.	 	\n 	Used Angular Material	 to  design and build up a multi layered  System.	 	\n 	Used Sonar Qube to monitored the Code Quality Metrices.	 	\n 	Involved in code review and approve the Pull Request	 	\n 	Led the deployment of  the code builds and helping in cont	inuous integration and deployment.	 	\n 	Used JIRA, Remedy to create user stories ,is	sues, plan	. 	\n 	Involved in creating the Database Model	 	\n 	Created and maintained the confluence page for all project specific details like Project Architecture etc	 	\n 	Involved in the PI 	planning to select the MBI and grooming the team on same.	 	\nEnvironment: 	Visual Studio Code, Angular	 8, Typescript,	HTML5, CSS,JIRA,,AngularC	LI,Angular Material 	\n,Cassandra,Kafka,Ama	zon Web s	ervices,Docker,Gitlab,NodeJS,	Java,	SpringBoot	,Kubernetes,AWS	 &amp; 	\nGCP	,SSO	,ASP.Net core 3.0	 	\n 	\nInfosys Ltd,Pune	 	\nClient: E.ON UK	(Worked at client location  Nottingham,UK from June 18 to Feb 19)	 	\nDuration: May  2018 to April 2019.	 	\nGSOS	-Guaranteed Standards of Service: These are the standards set by the E.ON and some of these are part	 of the 	\nobligations  set  for  energy  companies  by  Ofgem,  the  energy  industry  regulator.  Some  are  standards  that  the \nelectricity  distributors  and  gas  transporters,  who  make  up  the  distribution  network,  have  to  meet.  If  these \nstandards  doesn&#039;t  meet  then  electr	icity  distributor  or  gas transporter 	- will  pay  to  the  customer  subject  to certain 	\nexemption	 	\nResponsibilities:	 	\n 	Led in requirement gathering meetings with business customers.	 	\n 	Technical design including developing the component views of system	 	\n 	Design/Develop	ment of a new .Net Core Microservice to read Servicing data that invoked by the API.	 	\n 	Created MSMQ  to capture the customer transactions and support the developers in implementation of \ndesign wireframes.	 	\n 	Created the service layer which helps all developers/	 feature packs to utilize the APIs t	o be consumed in app	 	\n 	Created standardized API designing such that every  supplier uses its own RES	Tful API design	 	\n 	Involved in  Deploying, Monitoring and Hosting of the Microservice.	 	\n 	Used Angular Material	 to  design and b	uild up a multi layered  System.	 	\n 	Led the deployment of  the code builds and helping in continuous integration and deployment.	 	\n 	Used JIRA, Remedy to create user stories ,issues, plan sprints and to distribute tasks amongst team members.	 	\n 	Worked on the Advance	d queue on high volume transactional systems in Oracle.	 	\n 	Involved in DB Performance Optimization as well.	 	\nEnvironment: 	Visual Studio Code, Angular	4/6	, HTML5, CSS,JIRA,,	NodeJS,AWS,	AngularCLI,Angular 	\nMaterial ,Oracle 11g.	Azure	,ASP.Net core 2.0	 	\nInfosys Ltd,Pun	e 	\nClient: HSBC	 	\nDuration: May 	 2017 to March 2018	 	\nStaff  Frond  End  :  The  SFE  is  an  web  application  used  by  the  front  end  bank  employees  to  get/view  all  the \ncustomer related information like Customer overview, Customer Family ,Loan Repayment schedule and Loan	 	\nRepayment Holiday etc. 	 	\nResponsibilities:	 	\n 	Development and technology planni	ng and implementation 	&ndash; providing	 guidance in best practice and tool 	\nuse in the design and build of technical frameworks and the applications built on them and own and \nimplement co	mplex area of the UI systems.	 	\n 	Architecture and design 	- proposes &amp; implements technical solutions, ensures their integrity, and that the 	\nsolutions can be built, implemented and maintained within timelines/budgets.	 	\n 	Technical design authority 	- internally re	cognized as a specialist in complex technical areas, will oversee 	\nbenchmarking, installation, upgrade, configuration, deployment, and testing activity.\n\nResume of Amol	 	 	Page 	5 of 	9 	\n 	Improves quality 	- investigates and prototypes innovative approaches to improve software quality.	Provide	 	\nStability 	- ensures development teams can develop in a stable and productive environment, with minimal 	\nrework required due to architectural change or related problems as products evolve.	 	\n 	Assisting Project Management in planning technical aspects of projec	ts. 	\n 	Providing regular updates on project status and risks.	 	\n 	Supporting and mentoring individual developers and ensure the team is positive &amp; motivated.	 	\n 	Performing detailed technical reviews to ensure the overall design is being implemented.	 	\n 	Full stack	 Web F	ramework development experience.	 	\n 	Demonstrable detailed understanding of architecture principles and methods, technology, and standards.	 	\n 	Utilizing 	research	 and self	-learning to ensure technical credibility.	 	\n 	Work	ing	 with UI Designer to provide feasibility di	rections and lead UI development team.	 	\n 	Possess	ing 	good	 analytical, communication &amp; interpersonal skill.	 	\n 	Hands on experience in responsive designs  (Bootstrap, Telerik or any other framework)	 	\n 	Participated in meetings with Business users and with other proje	ct means to ensure that the volatile	 	\n business requirements reflecting the project dev	elopment.	 	\n 	Contributing 	to the implementation of User Stories	 	\n 	Participating 	in SCRUM process	 	\n 	Fulfilling 	the acceptance criteria with the contributed code 	(quality, unit te	sts e	tc.)	 	\n 	Adherence to architecture, design and quality guidelines	 	\n 	Maintenance, problem analysis and bug fixing within the 	application	 	\n 	Technical clarifications with other team members	 	\nEnvirionment: 	Visual 	Studio Code, 	\nAngular	,HTML5,CSS,GitHub	,JIRA	,Jenkins,	Protractor,	NodeJS,AWS,	AngularCLI	,OAuth2.0	, ,ASP.Net core 2.0	 	\n 	\nTata Consultancy Services,	 Pune	 	\nClient:NBS Bank	 	\nDuration	:Nov  2015 to March 2017	(Worked at client location Swindon,UK	 from 	Nov 2015 to Nov 2016	) 	\nThe  Nucleus  is  a  web  application that  will  enable	 the  user  to  carry out  account  and customer  related  back  office 	\nservices on the accounts stored in SAP.Nucleus consists of a number of back office services which can be invoked  \neither  from  the  Nucleus  application  or  externally	 from  other  applications  by  p	assing  appropriate  data  to 	\nNucleus.The  external  applications  can  either  invoke  the  Nucleus  application  as  a  whole  or  a  specific  Nucleus \nprocess.In  both  the  cases  the  external  application  needs  to  pass  appropriate  data  confirming  to    a  pre 	defined 	\ninterface	.Nucleus  also  contains  links  to  other  many 	applications.  The	 data  that  is  available  within  Nucleus	 is 	\npassed to 	these external systems	 using the interface.	 	\nResponsibilities:	 	\n 	Develops software solutions by studying information needs; conferring with users; 	Studying systems flow, 	\ndata usage, and work processes; investigating problem areas; Following the software development lifecycle.	 	\n 	Develop features across multiple subsystems within our applications, including collaboration in requirements \ndefinition, proto	typing, design, coding, testing and deployment.	 	\n 	Documents and demonstrates solutions by developing documentation (HLD, LLD), flowcharts, layouts, \nssss	diagrams, charts, code comments and clear code.	 	\n 	Design,  develop  and  maintain  the  Database  Schema,  Entity  r	elationship  diagrams,  Data  modeling,  Tables, 	\nStored procedures, Functions and Triggers, Constraints, Indexes, Schemas, Functions, Views, Rules, Defaults \nand complex SQL statements. 	 	\n 	Maintain a technical understanding of a component or sub	-component within 	an application / product, 	\nproviding support for technical queries, live incidents and problems. 	 	\n 	To ensure that the technical integrity and quality of the applications / products is maintained across their \nlifetime, contributing to the development of any t	echnical changes being proposed. 	 	\n 	To build knowledge of how technical strategies are defined to provide business solutions.	 	\n 	Review Technical Feasibility Studies for projects that impact applications / products within domain, and \nassess potential impact.	 	\n 	So	lve software	-related problems, providing analysis and recommendations as appropriate. 	 	\n 	Develop an awareness of new tools, processes and technical developments relevant to component area of \nexpertise.	 	\n 	Understand emerging software development methods, tools 	and standards. Look for ways to apply as 	\nappropriate	 	\n 	Provide input to end	-to-end system technical designs that involve applications / products within domain, 	\ncollaborating with other internal and supplier teams as required.	 	\n 	Understand the various phases of	 the software development lifecycle.	 	\n 	Undertake impact assessment of change requests against applications / products within domain.\n\nResume of Amol	 	 	Page 	6 of 	9 	\n 	Review test strategies to guarantee the quality of the delivered software assist in the diagnosis of system \nproblems encounte	red during testing. 	 	\n 	Collaborate with other members across teams to build technical solution. 	 	\n 	Define architecture, R&amp;D on new technologies	 	\n 	Make the framework up	-to date based on new technology or new way to implement the software solutions.	 	\n 	Documenting st	andard features, guide to integrate framework features, user manuals, versions etc.	 	\n 	Create deliverables (Packages, Configurations) using IT Strategy approved build tools (Team foundation \nservers) and standards, ensuring they meet all specific install polic	ies defined for the system.	 	\n 	Maintained the source	-code repository, developed multi	-platform product installers and developed scripts 	\nfor builds and source code automation.	 	\n 	Co	-ordination with the Technical Project Managers, Software Developers, Testers, App	lication Support, SAs 	\nand DBAs for any Deployment and Change across environments.	 	\n 	Developed and managed testing and roll	-out project plans for software releases, desktop updates and server 	\nimplementations.	 	\n 	Designing and creating the web services using WCF 	and SQL Server 2010.	 	\n 	Designing the application by using the different design pattern like creation pattern (Factory design pattern, \nMVC, Abstract Factory, and Singleton) and structural pattern (Adapter, Facade etc.).	 	\n 	Complete assignment work to budget, tim	e and quality requirements. Document all work in accordance with 	\nagreed standards, and with re	-use in mind	 	\n 	Involved in Project planning, Resource utilization &amp; Timeline estimations.	 	\n 	Estimating the tasks based on functional requirement and assign the work t	o team	 	\n 	Managed the  offshore and onshore team.	 	\nEnvirionment: 	C#,Visual Studio 2015	, WCF,	SQL Server,,AngularJS,NodeJS	,SAML	 	\n 	\nTata Consultancy Services,Pune	 	\n Client:DNB Bank	 	\nDuration	:Jan2014 to Oct 2015	 	 	\nDescription:	 DLA  (DNB  Loan  Administration)  application  i	s  used  for  Administration  of  Currency  Loan  as 	\nwell  as  tailor  made  loans  in  NOK.  DLA  is  applicable  for  large  corporate 	customer 	and  limited  group  of 	\nprivate customers (Multi Currency Loans only).	 	\n 	Zenit  Workflow  interacts  with  different  rule  engines  and  syst	ems    and  the  offer  letter  to  the  customer   	\ngenerated for the customer mentioning limit and terms and condition. DLA loan is offered to very limited \nspecial customers only, so most of the terms and condition negotiated between loan officer and customer \nout	side the system over the counter.	 	\n 	Large  Corporate:  For  large  corporate  &amp;  International  Customer,  ASAP!LC  takes  care  of  the  Credit \nProcess.  As  the large  corporate  customers involve  high value  loans,  most  of  the  agreement  has  been  set \noutside the box between	 the lawyers of customer and DNB. Details agreement prepared based on various 	\nnegotiation factors like limit, collateral, margins etc. A Credit process can be initiated in ASAP!LC for an \nexisting customer or may be for a new customer.	 	\n 	After  Credit  process 	done  and  finalization  of  the  agreement,  A  Decision  have  been  have  been  taken  to 	\ngrant  the  loan  and  Limit  have  been  decided.  After  negotiation  of  agreement  have  been  over,  a  request \nhave been sent to DLA users through mail to open a loan project in the DLA 	system.	 	\n 	For  a  DLA  Loan collateral is  being  saved  to  Felix  Depot by  the  collateral  department  and  the  Collateral \nDepartment gives the final sign off and send the agreement to DLA department for further processing.	 	\n 	After  receiving  the  credit  decision,  DLA  Ap	plication  users  open  a  new  DLA  loan  project  using  the 	\nCustomer details provided in the agreement. 	 	 	 	 	\n 	After  Credit  process  done  and  finalization  of  the  agreement,  A  Decision  have  been  have  been  taken  to \ngrant  the  loan  and  Limit  have  been  decided.  After  neg	otiation  of  agreement  have  been  over,  a  request 	\nhave been sent to DLA users through mail to open a loan project in the DLA system.	 	\n 	For  a  DLA  Loan collateral is  being  saved  to  Felix  Depot by  the  collateral  department  and  the  Collateral \nDepartment gives the 	final sign off and send the agreement to DLA department for further processing.	 	\n 	After  receiving  the  credit  decision,  DLA  Application  users  open  a  new  DLA  loan  project  using  the \nCustomer details provided in the agreement. 	 	\n 	From DLA client after creation  of 	the DLA  project  there  is  a limit  have  been  entered  for  customer  based 	\non  the  limit  set  in  the  Credit  Process.  This  DLA  limit  is  used  for  reference  and  warning  purpose  only, \nDLA limit will be changed manually based on revision of the limit from Credit Depar	tment	 	\n 	After creation project a Single Loan or Limit	-Tranche Facility have been created through DLA client and 	\nthe amount getting disbursed as per the agreement.	 	\n 	After creation of project and loan it sends information to Felix exposure.	 	\n 	Loan  disbursement  is	 a  manual  process  in  DLA.  DLA  user  need  to  disburse  the  loan  to  the  customer 	\naccount. In case of non DNB customer Disbursement will be done through a internal Global Account.\n\nResume of Amol	 	 	Page 	7 of 	9 	\nResposibilities:	 	\n 	Participated in meetings with Business users and with other pro	ject means to ensure that the volatile	 	\n      	business requirements reflecting the project 	development. Application	 development was developed was 	 	\n      	based on UML methodology.	 	\n 	Involved in the design of the Use Case Diagrams and class diagrams using Micro	soft Visio.	 	\n 	Reworked on a part of the GUI to improve interface without affecting the performance of the application.	 	\n 	Used C# as language to develop code behind business logic	 	\n 	Used C# for middle tier business logic and implementation of Web Services	 	\n 	Followe	d the MVVM design 	pattern, separating	 the 	business, presentation	 and data models.	 	\n 	Performed the conversions of existing VB Applications into WPF application.	 	\n 	Designed the WPF GUI for accessing product 	details, Comparisons	 and Client details.	 	\n 	Developed User	 Interface(UI) using WPF for the better look and feel of the Window based application.	 	\n 	Wrote Stored 	Procedures, Triggers	 and SQL Queries and LINQ in SQL Server 2008.	 	\n 	Developed and consumed WCF Web Service to access data layer components	 	\n 	Involved in Impleme	ntation of Exception handling on User Interface layer.	 	\n 	Created test cases and did basic manual testing.	 	\n 	Used TFS as a central repository and source code control.	 	\n 	Mapping the business requirement to the technical specification and detail design documents.	 	\n. 	\nEnvirionment: 	C#,Visual Studi	o 2012	, WCF,WPF,S	QL Server,Entity 	Framework., Angular	 JS,MVC.	 	\nTata Consultancy Services,Singapore	 	\nClient:Barclays Bank ,Singapore	 	\nDuration	: April 2013 to  Dec 2013.	 	\n Barclays is a major global financial services provider engag	ed in retail and commercial banking, credit cards, 	\ninvestment banking, wealth management and	 investment management services	 	\nDescription:Exposure Analysis &amp; Reporting	-Credit Risk Portal	 	\nExposure, Analysis and Reporting application in Credit Risk Portal is a	n application that supports and 	\nenhances new BASEL 	&ndash; III and SRA requirements. Changes are been introduced in new BASEL III and 	\nStrategic Risk Architecture (SRA) framework, which impact the current reporting architecture. This project \naims to build a syste	m that enable users to perform What	-if calculations and view pre	-calculated exposure 	\nmeasures, apply adjustments for any counterparty, site, product, what	-if trades, actual trades. View 	\nnumerical and graphical display of risk measures. View list of actual 	trades, trade attributes, settlement 	\nprofiles, netting agreements, Collateral arrangements etc for any CSP and Trades.	 	\nPortfolio simulations are required to generate risk measures to manage the counterparty and trading \nbusiness.This can be used to see the 	impact on a portfolio when new derivative and Securities Financing 	\ntrades are entered into by calculating several credit risk measures.	 	\nThe impact on the regulatory capital is also measured by calculating several regulatory metrics.	 	\nResponsibilities:	 	\n 	Respo	nsible for Design and Development of tactical IT solutions for Credit Risk Management System, 	\nactively involved in UI Design, WCF Services, Database Access Layer including Stored Procedures, \nCreating and maintaining Tables, Triggers, Views, Functions, Inde	xes for performance tuning. 	\nInvolvement in SRA Batches and Downstream Feeds for data to be picked up.	 	\n 	Using WPF, WCF, C#.Net 4, Visual Studio 2010, SQL Server 2008, Infragistics Controls, Xceed Grids and \nChart Controls to design and build up a multi layere	d Credit Risk System.	 	\n 	Championed using MVVM and PRISM design approach to ease separation of concerns between UX \ndesign, business logic, service back end and testing layers.	 	\n 	Involved in Performance Optimization at application and database level, Defect Fixe	s, Migration of 	\nExcel to Application and vice versa.	 	\n 	Involved in all aspects of design and development including co	-ordination of testers, BAs and business 	\nusers. Worked with business analysts to determine business rules and feature list.	 	\nEnvirionment: 	C#,	Visual Studio 2010, WCF,WPF,SQL Server,	 Multithreading	 and IIS.	 	\n Syntel. Ltd , Pune	 	\nAMEX 	 	\nClient:American Express 	 	\nDuration:	 Sept 2010  to 18 Nov 2011	 	\nRole:	 Analyst Programmer	 	\nDescription	: 	\n 	Statement  of  Work  (SOW)  Module:Users  can  create  a  request,  fill  out 	the  forms  by  selecting 	\nappropriate  request  type  and  submit  that  SOW  request,  which  notifies  respective  teams  to  take \naction  Once the request process is completed, the status will  be changed to complete      	 	\nand request can be closed. However, request wi	ll be in DB for future reference	.\n\nResume of Amol	 	 	Page 	8 of 	9 	\n 	Resource  Change  Request:Change  can  be  made  for  changing  the  request  by  leader,Requestor  only	 	\ncancel the request.After complete approvation of request,resource allocates to the requestor.	 	\n 	Work  In  Progress(WIP):This  module  i	s  used  to  manage  Project  Estimation  where  transfer  of  hours 	\nfrom projects is managed.	 	\n \n        	Responsibilities:	 	\n 	Involved  in  Requirement  Analysis,designed  and  developed  Web  application  using  C#.Net  4.0  and \nSilverlight.	 	\n 	Gathering the Client Requirements by 	participating in minute	-to-minute meetings and Analysis.	 	\n 	Design the High Level and Low Level Design of the system.	 	\n 	Programming Using Silverlight,C#	 	\n 	Developed  UI  Using  Silverlight  Controls  and  implemented  business  components  and  data  access \ncode using C#.	 	\n 	Involved in the database design and design tables,indexes and views.	 	\n 	Developed Tables,Indexes,Stored Procedures,Database Triggers and Functions.	 	\n 	Implemented WCF Web Services for database connectivity in Silverlight application.	 	\n 	Analyzed and formulated the T	est plan for requirements,created and test scenario from use cases,	 	\ntest case design from design document,regression and test automation using NUnit.	 	\n 	Involved  in  Unit  and  module  level  testing,reviewing  the  requirements  and  fixing  the  defects \nappropriately.	 	\n 	 Involved in detailed documenting of the application that was developed by me.	 	\n 	Provided production support and deployment support .	 	\n 	Project version management and code control and management was done in VSS.	 	\n 	Project was delievered following CMM methodolog	y. 	\n        	Envirionment:	 C#,Visual Studio.Net,Silverlight,WCF,WPF,SQL Server,Nunit and IIS.	 	\n Acidaes Solutions Pvt. Ltd ,Mumbai	 	\nCRMnext	 	\nClient	: HDFC Bank	 	\nDuration:	 Jul 2008 to Aug 2010	 	\nRole:	 Engineer 	- Application Development Group.	 	\nDescription	:  CRMnext  is 	a  business  application  designed  specifically  to  address  companies  wide  ranging 	\nneeds  of  managing  collaboration  and  interactions  between  vendors,  suppliers,  and  customers.  It  helps \ncompanies  efficiently  manage  the  front	-end  processes,  provide  consistency  ac	ross  all  customer  interaction 	\npoints,  and  focus  on  efficiencies,  boosting  bottom  line  revenue  potential.  Implementing  CRMnext  is  a \nstrategic  initiative  for  any  company.  CRMnext  provides  the  technology  platform  required  to  implement  an \nenterprise  CRM    initi	ative.    A  typical  CRM  initiative  is  a  mix  of  strategy,  process  and  technology  CRMnext 	\nenables companies to better manage and seamlessly share information, across departments by centralizing all \ncustomer  data.  It  automates  various  processes  using  its  workfl	ow  capabilities,  provides  powerful  reporting 	\nand  analytical  capabilities  that  deliver  actionable  business  intelligence.  This  enables  CRMnext  to  help \norganizations  create  a  true  360&deg;  view  of  their  own  customers  that  spans  across  departments.  Typically,  an \nend	-to-end  CRMnext  deployment  will  cover  all  customers  facing  departments  and  manage  the  entire 	\ncustomer  lifecycle.  It  covers  the  entire  working  of  the  company  starting  from  lead  generation,  to  closure  of \nsales and from customer service to cross	-sell / up	-sell services. 	 	\n        	Responsibilities:	 	\n 	Involved  in  defining  business  and  system  requirements  and  designed  the  functional  and  technical \nspecifications.	 	\n 	Programming using ASP.Net,C#.	 	\n 	Design and Developed web Forms using ASP.Net,XML.	 	\n 	Used ASP.Net Server Con	trols and HTML controls to design and web pages.	 	\n 	Involved in writing the programming code for web pages using ASP.NET object model.	 	\n 	Used ADO.Net Object Model to Interact with SQL Server Database using C# language.	 	\n 	Used Dataset object and Data Reader object	 to get the data from Database.	 	\n 	Wrote stored procedures and triggers.	 	\n 	Developed  Reporting  and  Analysis  module  by  web  enabling  reports,Web  development  using \nHTML,ASP.Net to deploy reports for the end user to view,print and export data from analysis purposes	. 	\n 	Involved in the development of the test plan Visual Source safe used on source control tool.	 	\n 	\nEnvironment:	 C#, ASP.Net, SQL Server 2005,Javascript,WCF,AJAX  Nunit,Silverlight	 	\n Orion India Systems Pvt. Ltd., Mumbai	 	\nVector 2008	 	\nClient:	 KPMG\n\nResume of Amol	 	 	Page 	9 of 	9 	\nDuration:	 Jan 20	08 to Jul 2008	 	\nRole:	 Software Developer	 	\nPlatform: 	Windows 2003	 	\nDescription	:   This is a custom auditing tool developed for the pioneers in auditing having their footprint all 	\nover the world. The application is developed in .Net  with client component devel	oped in ASP.Net with a 	\nservice running on the server and backend being MS SQL server.  The application is designed to manage all \nthe activities involved in the auditing process. It also uses service oriented architecture for the integration of \nplug in tool	s which allows system integration through loosely coupled components. The system has also got a 	\ncustom made document management system incorporated to it which holds the information in the SQL file \nsystem.	 	\nResponsibilities	   	\n 	Developed web forms using C#,AS	P.Net and SQL Server 2005.	 	\n 	Used Data Binding to bind Servers controls with the parameter from the tables in the database.	 	\n 	Published  Web  Services  using  C#  to  interact  with  the  other  applications  and  exposed  them  using SOAP \nand HTTP.	 	\n 	Designed and Developed A	SP.Net pages including Master and Navigation pages.	 	\n 	Implemented Data Grid view adding,deleting,sorting of rows for all the contacts and addresses of clients.	 	\n 	Involved  in  unit  and  module  level  testing,reviewing  the  requirements  and  fixing  the  defects \napprop	riately.	 	\nEnvironment:	 C#, ASP.Net, SQL Server 2005,Javascript,WCF,AJAX  Nunit.	 	\n 	\n IL &amp; FS Education &amp; Technology, Mumbai	  	\n Assessment Online	 	\nClient:	 ABNAMRO Bank, ICICI Prudential	 	\nDuration: 	April 2007 to Jan 2008	 	\nRole: 	Software Developer.	 	\nDescription	: Assess	ment Online is an online testing engine, which facilitates: 	 	\nCreation of Tests	 - Tests in any domain can be created from a global question bank (owned by organization)	 	\nAdministration of Tests	 - The tests can administer on	-line question bank or any personal	 question bank of a large 	\nof employer 	.The System enables frequent and Effective evaluation of employee and provides feedback about the 	\nTest  to  the  test  administrators  in  terms  of  statistical  analysis  of  questions  and  tests.  The  Assessment  Online  is  a \npowe	rful  Application  suite  of  creating  tests  and  surveys  on  the  web.  AOL  is  designed  to  deliver  online 	\nassessments  that  can  test  not  only  standard  literacy  and  numeric  skills  but  also  avows  organizations  to  easily \ndesign  their  own  questions.  With  AOL  software,	 you  can  quickly  and  easily  create  and  administer  online  tests 	\nwith minimal effort, giving you more time to spend with learners in the classroom or the workplace. 	 	\nResponsibilities:	  	\n 	Developed and Implemented the web page interfaces	 	\n 	Created  ASP.Net  pages  u	sing  C#.Net  for  middle	-tier  processing  of  clients  requests  of  clients  requests 	\nwith ADO.NET interfaces for database and implemented stored procedures.	 	\n 	Used  ADO.NET  and  data  objects  such  as  Data  Adapter,Data  Reader,Dataset,data  table  for  consistent \naccess t	o SQL data sources.	 	\n 	Used SQL Server as RDBMS to create and maintain Tables,Procedures and Views.	 	\n 	Implemented session state management	 	\n 	Migrated the functionality from existing asp pages to  new aspx pages and also added new functionality \nto reflect the Busin	ess users requirements.	 	\nEnvironment:	 C#, ASP.Net, SQL Server 2005,Javascript,Web Services.	 	\n \nEDUCATIONAL 	QUALIFICATIONS	 	\n P.G.D.A.C (Software)	, Y.C.P.A.I.T, A.C.T.S, C.D.A.C Centre, Mumbai,(Feb,2007)	 	\n B.E (	Computer Technology	), K.I.T.S Ramtek, Nagpur,	 (June,20	02)	 	\n 	\nPERSONAL 	DETAILS	 	\n 	Date of Birth	: 1st January 1978	 	\n 	Languages Known	: English, Hindi and Marathi	 	\n 	Passport No:	 W7633055	 	\n 	Marital Status:	 Married', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 0),
(494, 117, 76, NULL, NULL, '76_117_21561509866b4bd1a5e40d_DIPALI_KSHIRSAGAR_.pdf', 'DIPALI KSHIRSAGAR .pdf', '@\nO\n,\nDIP A LI K A SH IN AT H  K SH IR SA G AR	\nkd ip ali2 001@ gm ail. c o m\n7263 015416\nT han e,  M um bai,  I n d ia	\n	O bje ctiv e\nI s e ek c h alle n g in g  o ppo rtu n it ie s w here  I  c a n  f u lly  u se  m y s kills  f o r t h e s u cce ss o f t h e\no rg an iz a tio n.	\n	E xp erie n ce\nR ohit  A sso cia te  C it ie s a n d  R ails  P vt. L td .\n03/0 7/2 023	 -  	3 1/1 0/2 023	\nIn te rn\nR esp o nsib ilit ie s in clu d e p ro je ct p la n nin g ,  b ud getin g ,  s c h ed ulin g ,  a n d  d eve lo pin g  d ra w in g s\nan d  s p eciﬁ ca tio ns f o r c o nce p t t h ro ug h ﬁ nal  d esig n.\nS ap phir e  D eve lo per&#039;s\n1 4/0 5/2 018	 -  	1 6/0 6/ 2 018	\nIn te rn\nP la n nin g ,  d esig n,  a n d  c o nstr u ctio n o f in fra str u ctu re  p ro je cts ,  g ain in g  p ra ctic a l  e xp erie n ce\nu n d er p ro fe ssio nal  s u p erv is io n. T hey c o ntr ib ute  t o  s it e  in sp ectio ns,  d ra ftin g  p la n s,  a n d\nen su rin g  p ro je ct c o m plia n ce  w it h  s a fe ty  a n d  r e g ula to ry  s ta n d ard s.	\n	E d uca tio n\nS in hg ad  C olle g e O f A rc h it e ctu re ,  P un e\n2 024\nB ach elo r O f A rc h it e ctu re\n6 .5 5\nS an t G aja n an  M ah ara j  R ura l  P oly te ch n ic ,  M ah ag ao n,  K olh ap ur\n2 019\nD ip lo m a in  C iv il  E ng in eerin g\n7 3.5 2\nN uta n  D yn an  M an d ir ,  K aly a n ,  T han e\n2 016\nS eco nd ary  S ch o ol  E d uca tio n\n75.2 0	\n	S kills\nP ro ble m  s o lv in g  s kill\nG ood m an ag em en t a n d  p la n nin g  s kill\nA cce p tin g  m y w ea kn ess a n d  t r y in g  t o  im pro ve\nC urio us t o  le a rn  n ew  t h in g s\n\nAbilit y  t o  c o pe w it h  f a ilu re s a n d  t r y  t o  le a rn  f ro m  t h em	\n	L a n g uag es\nM ara th i\nH in d i\nE ng lis h	\n	T ech n ic a l  S kills\nA uto ca d  2 D  a n d  3 D\nR evit  A rc h it e ctu re &nbsp;\nG oogle  S ke tc h u p &nbsp;\nLu m io n&nbsp;\nP ho to sh o p&nbsp;\nR hin o  ( G ra ssh o pper)\nM S O fﬁ ce &nbsp;', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 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
(495, 117, 76, NULL, NULL, '76_117_170264706966b4bd1a5e74a_Dr_Abhijeet_Resume_Industry.pdf', 'Dr.Abhijeet_Resume_Industry.pdf', 'Abhijeet	 Thakare	 	\nPhD	 (Computer	 Science)	 	\nORCID	 ID:	 http://orcid.org/0000	-0003	-1096	-6418	 	\n                     	 	\nDOB:	 24th	 May	 1979	 	\n181,	 	Jaidurga	 	Society	 	No	 	1, 	\nNarendra	 Nagar.	 Nagpur,	 India	 	(+91)	-8055044	195	 	\nabhijeetthakarevnit786@gmail.com	 	\nwww.linkedin.com/in/dr	-abhijeet	-thak	 	\nare	-33529618	 	\n                        	 	\n                        	                                                                                                                             	                                                                     	\nEXPERIENCE	 	\nTotal	 Experience:	 19 Years	 	\n \nSoftclouds	 LLC	 &mdash;	 AI	 Ar	chitect	 (R&amp;D)	 	\nSeptember	 2022	 - PRESENT	 	\n \nCurrently working as a 	 AI Architect in the Research and	 	\nDevelopment	 Division	 of Softclouds	 LLC.	 	\n \nPROJECTS	 HANDLED	 	\n● 	 Work	ed	 on Developing Enhanced Search Engine based on	 Question	-	\nAnswering	 System	-Keyword	 and	 Semantic	 Search.	 	\n \nTechnology/Tools:	 	Python	 	3.9,	 	Transformers,	 	BERT,	 	\nSentence	-Transformers,	 Spacy,	 NLTK,	 Dependency	 Parser,	 PyTorch,	 	\nPandas,	 Elasticsearch, OpenSearch	, JSON.	 	\n● 	Developed GEN AI and Predicated	 GEN AI Chatbot.	 	\nTechnology/Tools: 	JSON	,  Retrieval  Augmented 	Generation  (	RAG),  Fine 	\nTuning,  NLP,  LLM&rsquo;s,  Llama  Index,  Semantic  Search  ,  REST  API&rsquo;s,  Vector \nDB, LangChain, Prompt Engineering, NLP	 	\n \n \nShri	 Ramdeobaba	 College	 of	 Engineering	 &amp; Management	 , 	\nNagpur	, &mdash;	 Assistant	 Professor	 	\nJune	 2009	 - September	 2022	 	\n \nPROJECTS	 HANDLED	 	\n● 	Executed	 Successfully	 ﬁrst	 research	 software	 consultancy	 in the	 	\nDepartment	 (in	 2011)	 Implementation	 and	 Enhancement	 	/ 	\nTweaking  of  Synchronization  Protocol  1588v2  over  Multi  Protocol	 	\nLabel	 Switching	 (MPLS)	 Network. 	This  protocol	 enhancement  will	 	\nred	uce   data  loss  by  5%,  red	uce  tim	e  lag  by  15%,  and  red	uce  the 	\nSynch period by	 50% for	 BSNL.	 	\n● 	Developed  and  successfully  deployed	 consultancy  project  &ldquo;  Touch	 	\nScreen  Kiosks&rdquo; 	for  one  of  the 	reputed  Hotel	 clients  in  Panchgani,	 	\nMaharashtra. 	This  deploy	ment 	has  decreased	 the  efforts  of  Hotel	 	\nmanagement  Staff	 in  managing  the  orders  of  customers  by 	100%.(	 	\nTechnology:Java,	 Duration	 : 1 year)	 	\n● 	Developed	 and	 successfully  deployed  an  E	-Commerce  website 	for	 	\none  of  the  startups  in  Nagpur.	 This  has 	increased  their	 business 	in 	\nlockdown	 by	 10%	 in one	 month.	 (  Technology:  Java,Duration:  6	 	\nmonths)	 	\n● 	Successfully 	 completed	 and	 delivered	 software	 development	 project	 	\n \nLANGUAGES	 	\n \nJava,	 Python,	 C, C++,	 JSP,	 	\nServlets,	 	Spring	 	Boot,	 	\nSpring,J2EE	 	\n \n \nSKILLS	 	\n \nMachine 	 Learning,	 	Nat	ural	 	\nLanguage	 Processing,	 Deep	 	\nLearning	 	Transformers,	 	\nQuestion	-Answering	 System,	 	\nSpacy,	 	 Dependency	 	\nParser,	 Generative AI, LLM&rsquo;s, 	\nPrompt Engineering, \nElasticsearch,	 OpenSearch,	 	\nJSON,	 Named	 Entity,	 BERT	 	\nAggregated	 Search,	 Hugging	 	\nFace 	, Data Structures, Obj	ect	 	\nOriented	 Concepts.	 	\n \n \nDATA	BASES	 	\n \nOracle	 , MYSQL,	 WordNet,	 	\nOracle	 Apex.	 	\n \nPRODUCTS	 WORKED	 	\n \nEmatrix,	 Windchill	 	\n \n \nAWARDS	 	\n \n \nNPTEL	- Top	 Performing	 	\nMentor Award (	 	\nProgramming	 in Java)	 in 2021\n\n&ldquo;Development	 of 	Software for Customer Engagement Database 	\n&ldquo; for	 the	 client	 &ldquo;Sanstar	 Microsystems,Nagpur&rdquo;.	 Research	 funds	 	\nreceived	 from	 GIZ,	 Germany	 for	 development	 of this	 project.	 	\n \n \nRESEARCH	 PROJECTS	 	\n1. Project Name:Automatic Extraction of Product Entities and Attributes	 	\nfrom	 World	 Wide	 Web.(	 Status	- Completed)	 	\n \n● Development	 of a  Novel  Search  Engine 	which  automatically  extracts	 	\nentities	 and	 their	 respective	 attribute	 values	 from	 web	 pages	 and	 	\naggregates	 them	 into	 dynamic	 web	-spreadsheets.	 	\n● 100%  time  saving  of  t	he  customer,  as  no  need  to  scroll  results  and	 	\nsearch	 within	 results	 for	 choosing	 the	 right	 product.	 	\n● New  features  added  by  the  manufacturer/retailers  are  also  dynamically	 	\ncaptured	 in the	 web	 spreadsheet.	 	\n \nTechn	olo	gy/Tool	s:    Python,    NLTK    ,Java    1.7.0_80.,   JSOUP	   1.8.2   API, 	\nStanford POS tagger v.  2.0,  Java wor	dNet Interface  API,  Weka,  Mac	hine	 	\nLearning,  J48  Decision  Tree  Classiﬁers,  Natural  Language  Processing,	 	\nSearch	 Engines,	 Aggregated	 Search,	 Web	 Crawler.	 	\n \n \n2. Project  Name:Flexible  Software  Architecture for  Validation  of  Change	 	\nRequirements	 . ( Status:	 Completed	) 	\n \n● Development  of  Software  Fr	amework	 which  is  ﬂexible  enough  to	 	\nadjust	 in the	 scenario	 when	 the	 software	 requirements	 in an	 	\norganization	 continuously	 changes.	 	\n● Cost  of  implementing  change 	requirements  in  software  code  is 	reduced	 	\nby	 50%.	 	\n● Saving	 Man	-hours	 for	 writing	 code	 by	 50%.	 	\n \nTechno	logy/Tools:	 Java,	 JSP,Servlets,	 MySQL	 	\n \n3. Project	 Name:Question	-Answering	 Chatboat	 ( Status:	 Ongoing)	 	\n \n● Development  of  closed  domain	 Question	-Answering  Chatboat  on	 	\nEntertainment	 Domain.	 	\n● Development of  Open  domain Question	-Answering	 Chatboat  for Time	 	\nSeries	 Data	 using	 LSTM/BERT.	 	\n \nTechnology/Tools:	 Python,	 Machine	 Learning,	 Natural	 Language	 	\nProcessing.	 	\n \n \nITC	 InfoTech,	 Bangalore	 &mdash; Associate	 IT Consultant	 	\nOctober	 2008	 - March	 2009	 	\nProject	 Name:	 Monitoring	 Windchill	 Services,Client:	 PTC	 India	 Limited	 	\n \n● Successfully  h	andled  the  team  of  4  persons  for  conﬁguration  and	 	\nenhancement	 of &ldquo;Application	 Manager&rdquo;	 tool	 for	 reading	 different	 	\nservices	 Log	 Files	 and	 generating	 Statistical	 reports.	 This	 has	 increased	 	\navailability	 of different	 services	 of 	\nWindchill&rdquo;	 software	 by	 15%.	 	\n \nTechn	olo	gy/Tool	s: Java, JSP, Servlets, Or	acle 10g, Apache Tomcat 6.0. 	\n \nGeometric	 Limited	 &amp; 3dplmsoftware	 Solutions	 Ltd	 ( R &amp; D 	\nDivision of	 Dassault	 Systems), 	Pune	&mdash; Software	 Engineer 	 , 	\nAugust 2006 	-October	 2008	 	\n \nITC Infotech Ap	preciation	 	\nAward 	from ITC Infotech,	 	\nBangalore	 in 2014	 	\n \nInfosys Partner in Success	 	\nBronze	 Award	 from	 Infosys	 in 	\n2016	 	\n \nPATENTS	 	\n \nIndian Patent	 Published	 on	 	\n&ldquo;A Real World Object	 	\nInteraction Through Eyes: A	 	\nNovel Augmented Reality	 	\nConcept&rdquo;.	 	\n \nCERTIFICATIONS	 	\n \n● IBM	 Certiﬁed	 Database	 	\nAssociate	-DB2	 Universal	 	\nDatabase	 V8.1	 Family	 	\n● Brain	 bench	 Certiﬁed	 	\n(RDBMS,	 JSP,	 DB2	 	\nProgramming).	 	\n● Ematrix	 Application	 and	 	\nIntegration	 Certiﬁcation	 	\n(Certiﬁed by Geometric	 	\nLimited,	 Pune).	 	\n●  	MCP	 (Microsoft	 	\nCertiﬁed	 Professional).	 	\n● ANN	 and	 Deep	 Learning	 	\nCertiﬁed 	by MeitY and	 	\nIIITDMJ, Jabalpur\n\nProject Name: Enovia Matrix One Product Central, Client: LG Electronics	 	\n(South	 Korea)	 	\n●  	Successfully  delivered 	the  project  to  the	 client.  Worked  on 	\nComplete	 Software	 Lifecycle	 of the	 Project,	 Product	 Develo	pment,	 	\nFeature	 Enhancement,	 Bug	 Fixing	 , Unit	 Test	 Plan	 Creation	 and	 	\nDebugging.	 	\n● Modules 	 delivered 	 by 	 me 	 and 	 my	 team	 have  	 shown	 100%	 e    	 ciency	 	\non the client site	 when tested on	 large data	 sets.	 	\n \nTechnology/Tools:	 Java,	 Servlets,  JSP,  MQL,  TCL,  ema	trix,  oracle  9i,	 	\noracle 10g, Tomcat 5.5 	\n \nHarrier	 Information	 Systems,	 Nagpur	&mdash;System	 Engineer 	 , 	\nOctober	 2005	 -July	 2006	 	\n \nProject	 Name:	 Capital	 Market	 5 minutes	 Delayed	 Data,	 Client:	 NSE	 	\n(National	 Stock Exchange), CRISIL	 	\n \n● Successfully	 developed	 and	 delivere	d a Java	 System	 which	 	\nautomatically   	 downloads   	 all   	 the   	 market        information        ﬁles        on	 	\nreal	 time	 from	 NSE&rsquo;s	 production	 server 	 and 	 stores    on    our    local	 	\nsystem.	 	Further	 	the	 	Java	 	System	 	,automatically	 	dumps	 	the	 	\nﬁles(depending  upon  its  structure	 and      type)  into  respective  tabl	es  in	 	\nthe	 database.	 	\n● Development  of  this  project  results  in  100%  availability  of 	market	 	\ninformation	 ﬁles	 and	 its	 future	 data	 on	 our	 local	 system	 for	 future	 	\nanalysis	 of stocks.	 	 \nTechnology/Tools: 	Java, Servlets, JSP,  MultiThr	eading, JDBC,  Tomcat  5.5,	 	\nOracle	 9i 	\n \nSimsoft	 Technologies,	 Nagpur	&mdash;	System	 Administrator	 	, 	\nJuly	 2001	 -May	 2003	 	\n \nManaging	 and	 Handling	 LAN	 &amp; WAN,	 Troubleshooting	 the	 system	 and	 	\nthe	 network	 	\n \nTechnology/Tools:	 Java,JSP,Servlets,	 MYSQL,	 Oracle	 11g.	 	\n \n \nPUBLICATION	S 	\n \n● Authors	 : Abhijeet	 	Ramesh	 	Thakare,	 	Parag	 	S. 	Deshpande	, 	Title:	 	\nComparative	 Search	 of Entities	, Journal:	 International	 Journal	 of Software	 	\nEngineering	 	and	 	Knowledge	 	Engine	ering.	 	(SCI	 	Journal)	 	. 	\nhttp://ww	w.worldscientiﬁc.com/doi/abs/10.1142/S0218194017500498	 	\n● Authors  :  Abhijeet  Ramesh  Thakare,  Parag  S.  Deshpande, 	Title: 	Automatic	 	\nExtraction  of	 Attributes  and  Entities  for  Product  Differentiation	,  Journal:	 	\nInternational	 	Journal	 	of 	Computational	 	Intelligence	 	Systems	 	(SCI	 	\nJournal),	https://doi.org/10.2991/ijcis.11.1.23	 	\n● Authors  : 	Abhijeet  Th	akare,Nilesh  Korde 	Title:	Patient  Health  Monitoring	 	\nSystem	 Using	 Blue	 Eye	 Technology	 and	 IoT	, Journal:	 Bioscience	 	\nBiotechnology	 	Research	 	Communications	 	(WoS	 	(ESCI	 	Journal),	 	\nhttp://dx.doi.org/10.21786	/bbrc/13.14/3	 	\n● Authors 	:  Nilesh  Korde,  Abhijeet  Thakare	 Title	:Recognition  of  Letters  and	 	\nLetter	 Font	 in Images	 Using	 Deep	 Learning,	 Journal:	 Bioscience	 	\nBiotechnology	 	Research	 	Communications	 	(WoS	 	(ESCI	 	Journal),	 	\nhttp://dx.doi.org/10.21786/bbrc/13.14/20	 	\n● Authors 	:  Abhijeet  Thakare	 Title	:Intelligent  Automated  Irrigation  system	 	\nBased  on  Soil  Sensors  and  Weather  Forecast  Data. 	Journal: 	International	 	\nJournal	 of Next	 Generation	 Computing	 (WoS	 ( ESCI	 Jounal	).\n\nhttps://doi.org/10.47164/ijngc.v12i5.429	 	\n● Authors 	: Preeti	-Paranajpe  Voditel, Abhijeet  Ramesh  Thakare, 	Title	:  Use  of	 	\nSampling	 and	 Ant	 Colony	 optimization	 for	 Predicting	 support	 in 	\nRecommender  System, 	Conference	:  Science  and  Information  Conference  ,	 	\nUK,	 London,	 (Scopus)	, https://ieeexplore.ieee.org/document/6661794	 ( 	\nScopus	 Indexed)	 	\n● Authors : 	Nilesh Korde, Abhijeet Thakare	, Title: 	Smart Shelve Management	 	\nSystem  using  IOT	-A  Novel  approach	,  Con	ference: 	IEEE&rsquo;s  3rd  International	 	\nConference	 	in 	Technology	 	(I2CT),	 	Pune	 	(Scopus	 	Indexed),	 	\nhttps://ieeexplore.ieee.org/abstract/document/8529415	 	\n● Authors	 : Nilesh	 Korde,	 Abhijeet	 Thaka	re, Title:	Exploration	 of Opinion	 	\nfrom	 	Twitter	 	Data	, 	Journal:	 	International	 	Journal	 	of 	\nRecent	 	 Technology	 	and	  	Engineering	 	(Scopus	 	 	Indexed).	 	\nhttps://www	.ijrte.org/wp-co	ntent/uploads/papers/v8i4/B3854078219.pd 	\nf 	\n● Authors	 : Th a ka re   A. O.	, Thakare A. R., Tembhurne O.W.,Reddy S.N	., Title:	\nNoSQL Databases	-Modern Data Systems for Big Data An	alytics	-Features, 	\nCategorization and 	Comparison, 	 Journal:	 International Journal of 	\nElectrical and Computer Engineering Systems	(WoS	 (ESCI	 Journal) and 	\nScopus	 	 Indexed)	, DOI: 	https://doi.org/10.329	85/ij	eces.14.2.10	 	\n● Authors	 : Kha n da r   P,   T ha oke r   C,  	Thakare A	, Title: Decision Tree 	\nAlgoritm: 	A Survey, 13th International Conference on Advances in 	\nComputing, Control, and Telecommunication Technologies, ACT \n2022,	 2022, 8, pp. 985	&ndash;990	(Scopus	 Indexed)	 	\n● Authors	 : Th a ka re   A.	, Vodi t e l  P.	, Title: 	Extractive Text Summarization 	\nUsing LSTM Based Encoder	-Decoder Classification	, ECS Transactions	This 	\nlink is disabled	., 2022, 107(1), pp. 11665	&ndash;11672	 (Scopus	 Indexed)	 	\n 	\n \nEDUCATION	 	\nVisvesvaraya	 National	 Institute	 of	 Techn	ology	, Nagpur	 &mdash;	 	\nPhD	- Computer	 Science &amp; Engineering, 	January	 20 13	 - December	 20 17	 	\nDefense	 Seminar	 done	 in October	 2018.	 	\nCGPA:	 9.43	 	\nResearch	 Area	- Natural	 Language	 Processing,	 Web	 Mining,	 Text	 Mining,	 	\nInformation	 Retrieval	 	\n \nWalchand College of Engineering	, Sangl	i&mdash;	 Master of	 	\nEngineering	- Computer Science &amp; Engineering, 	August	 2003 	- August	 	\n2005	 	\nFinal	 Project	 Viva	 Done	 in October	 2006	 	\nPercentage:	 66.80%	 ( First	 Division)	 	\n \nP.C.E	 &amp; A, Nagpur	&mdash;	 Bachelor	 of Engineering	- Computer	 	\nTechnology,	 August	 1996	 - August	 200	1 	\nPer	centage:	 60.00%	 ( First	 Division)	 	\n \nA.G.	 Junior	 College,	 Dapoli	&mdash;	 HSSC	 (Maharashtra	 State	 Board)	 	\nJune 1995	 - March	 1996	 	\n \nPercentage:	 71.83%	 ( First	 Division)	 	\n \n \nA.G. Highschool, 	Dapoli	&mdash;	 SSC (Maharashtra State Board) 	June	 	\n1993	 - March	 1994	 	\n \nPercentage:	 78.85%	 ( First	 Division,	 Distinction)', 2, 2, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 0),
(496, 117, 76, NULL, NULL, '76_117_75529296166b4bd1a5eade_final_aniket_cv_24.pdf', 'final_aniket_cv_24.pdf', 'aniket.sanyal@outlook.com +91-8421931940', 2, 1, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 0),
(497, 117, 76, NULL, NULL, '76_117_49901470366b4bd1a5ed1f_Gokul_Talele_CV_(1).pdf', 'Gokul_Talele_CV (1).pdf', 'Gokul	 Talele	 	\nLead Data Scientist, Doctoral Researcher at SSBM, Geneva	 	 	\nPhone:             	7347278015 / 7798708015	 	 	Address:          	Pune, Maharashtra, India	 	 	LinkedIn:        	https://www.linkedin.com/in/gokul	-talele	 	 	Email:              	deva.talele@gmail.com	 	   \nA results	-driven	 Lead	 Data	 Scientist	 with	 a deep	 conceptual	 understanding	 of enterprise	-wide	 analytical	 needs	 and	 expertise	 in  Data	 Mining	 Methods,	 	\nPattern	 Classification,	 Quantitative	 Analysis,	 and	 Data	 Analysis.	 Possessing	 an inquisitive	 and	 analytical mind	 coupled	 with	 creative	 thinking,	 I excel	 in 	\nidentifying	 patterns	 and	 deriving	 actionable	 insights.	 With	 a customer	-focused  approach,	 I effectively	 manage	 the	 business	 cycle	 process	 from	 client	 	\nconsultation 	to 	closing	, ensuring	 strategic	 program  planning	 and	 realization	 of business	 benefits.	 Thriving	 in challenging,	 fast	-paced	 environments,	 I 	\nbring a	 detail	-oriented attitude,	 organizational	 skills,	 and	 a strong	 track	 record	 of delivering	 results.	 	\nEXPERIENCE	 	 \nAccenture,	 Pune	 	\nLead Data Scientist	 	\n \n \n     	June	 202	1 - Present	\nManaged  the  end	-to-end  lifecycle  of  the  AI  Tutor 	project,  from  conception  to  deployment,  ensuring  timely  delivery  and  alignment  with 	\nstakeholder requirements.	 	\nLed  a  team  in  creating  a  Quiz  AI  system  for  automatic  question  generation  and  answer  extraction,  integrating  it  seamlessly  in	to  the  AI  Tutor 	\nplatform.	 	\nConducted  data  analysis  to  derive  actionable  insights,  evaluated  model  performance,  and  iterated  on  algorithms  to  improve  eff	ectiveness 	\ncontinuously.	 	\nFostered cross	-functional collaboration and provided technical leadership and 	mentorship to junior data scientists.	 	\nBajaj	 Finserv,	 Pune	 	\nSenior Data Scientist	 	\nJuly	 2019	 - June	 2021	\nUtilized working knowledge of EDW (SQL), Pyspark, Python, R, Tableau, and Power BI to develop 	advanced analytical solutions. 	 	\nSpearheaded 	the 	development of machine learning models for financial fraud detection, leveraging techniques such as	 random forest, gradient 	\nboosting machines (GBM), and artificial neural networks (ANN) in Pyspark.	 	\nLed the creation of NLP models for data deduplication and customer base analysis, including 	implementing	 techniques like the Locality 	\nSensitive Hashing (LSH) model and similarity scoring in Pyspark.	 	\nDeveloped a propensity model using Pyspark for assessing the risk of customers, enhancing the organization&#039;s ability to mitig	ate potential 	\nrisks.	 	\nLeveraged Azure Databricks as the model development platform, ensuring scalability, reliability, and efficiency in the	 	\ndevelopment process.	 	\nApollo	 Munich	 Health	 Insurance	 Company	 Ltd.,	 Gurgaon	 	\nAssociate Manager 	- Analytics	 	\nSeptember	 2017	 - June	 2019	\nLeveraged  working  knowledge  of  SAS,  SQL,  R,  Python,  Tableau,  and  other  statistical  software  to  identify  opportunities  for  cre	ating  value	-	\nadded solutions to enhance business operations.	 	\nProactively identified and led initiatives 	to drive business growth and improve	 operational efficiency, demonstrating a strong drive to 	\nwin and a proactive working attitude.	 	\nStandardized and optimized the production of model validation reports, ensuring accuracy, consistency, and efficiency in the 	validation process.	 	\nConducted  hands	-on  reviews  and  validations  of  model  development,  including  examining  model  assumptions,  data  quality,  mathematical 	\nformulations, and independently recoding models for validation purposes.	 	\nDeveloped  risk  models  on  claims  data  to  assess  and  mitigate  potential  risks,  contributing  to  improved  decision	-making  and  risk  management 	\nstrategies.	 	\nDesigned comorbidity score models for claims handling, providing strategic business insights to management for 	informed	 decision	-making.	 	  \nPGIMER, Chandigarh	 	\nSenior Research Fellow	 	\nApril	 2016	 - August	 2017\n\nDeveloped questionnaire	-based tools for efficient data collection, facilitating comprehensive analysis and insights generation.	 	\nGenerated tables, listings, and graphs 	by protocols and assigned them to variables in analysis datasets using	 	\nR, SPSS, and other relevant tools.	 	\nDesigned and implemented advanced statistical and predictive models, leveraging cutting	-edge algorithms and diverse data sources to extract 	\nactionable insights.	 	\nUtilized analytical applications such as SAS, Python, R, and SPSS to identify trends and relationships within datasets, drawi	ng 	\nappropriate conclusions and translating findings into actionable recommendations.	 	\nStarcom	 Information	 Technology	 Limited,	 Bengaluru	 	\nStatistical 	Analyst	 	\nJuly	 2015	 - March	 2016	\nConducted detailed and comprehensive research on various statistical tools, staying abreast of advancements and best practice	s in the field.	 	\nProvided in	-depth analysis and 	recommendations on the suitability of different statistical tools for specific analytical tasks and projects.	 	\nDeveloped algorithms for implementation in software applications, ensuring efficient and effective utilization of statistical	 tools for data analysis 	\nand modeling.	 	\nCollaborated with cross	-functional teams to integrate algorithms into software platforms, optimizing performance and	 	\nusability.	 	\nIndian	 School	 of Business,	 Hyderabad	 	\nResearch Associate	 	\nNovember	 2014	 - June	 2015	\nLed data cleaning procedures and validation of analysis datasets and reports, ensuring data accuracy and reliability. Analyze	d customer trends to 	\ngain insights into underlying data processes.	 	\nUtilized SAS, R software, MS Excel, and databases like LexisNexis, ProQuest, and Factiva to work on graphs, frequency distrib	utions, 	the 	\nBass Diffusion model, segment analysis, and survival analysis.	 	\nGenerated tables, listings, and graphs 	per protocol and assigned them to variables in analysis datasets. Provided data support by extracting 	\ndata from various data warehouses using SAS.	 	\nConducted quality checks on entered data, cross	-validated generated reports, and generated data files from the Adapt data server. Created SAS 	\ndatasets from 	the data files.	 	\nDesigned and managed reporting processes, implementing standardized execution to enhance efficiency and accuracy. Leveraged t	echnology 	\nand reporting tools to identify and address potential issues, error	-proofing the system.	 	\nEmployed cutting	-edge methodologies for data mining and optimized algorithms to summarize and communicate key performance results 	\nand practice trends.	 	\nCompleted coursework for a Doctoral Level Programme in Causal Inference and Scientific Investigation at the Indian School	 	\nof Business.	 	\nEDUCATION	 	 \nSwiss	 School	 of Business	 and	 Management	 	\nDoctor of Business Administration, Business Administration and	 	\nManagement, General	 	\n \n \nApril	 2021	 - March	 2024	\nLiverpool	 John	 Moores	 University	 	\nMaster&#039;s degree, Data Science	 	\nGrade: 6.8/10	 	\n \nInternational	 Institute	 of Information	 Technology	 Bengaluru	 	\nPost Graduate Diploma, Data Science	 	\nGrade: 3.5/4.0	 	\n \nThe	 Maharaja	 Sayajirao	 University	 of Baroda	 	\nMaster&#039;s Degree, Biostatistics	 	\nGrade: 64%	 	\n \nNorth	 Maharashtra	 University	 	\nBachelor&#039;s Degree, statistics	 	\nGrade: 72%	 	\nJanuary	 2019	 - December	 2020	 	   \n \nJanuary	 2018	 - December	 2019	 	 \n  \n \nJanuary	 2012	 - December	 2014	 	  \n \n \nJanuary	 2009	 - December	 2012\n\nLANGUAGES	 	 \nEnglish	, Hindi	, Marathi	 	\nCERTIFICATIONS	 	 \nGenerative	 AI	 with	 Large	 Language	 Models	 	\nDeepLearning.AI, Amazon Web Services	 	\n \n \nArtificial	 Intelligence	 and	 Data	 Science	 for	 Leaders	 - Accenture	 	\nUniversity of 	Chicago Professional Education	 	\n \n \nNorthwestern	 University	 101:	 Leading	 with	 Analytics	 	\nKellogg Executive Education	 	\n 	\n \n \nFebruary	 2024	 - Present	 	 \n  \n 	\nOctober	 2022	 	\n   \n 	\nSeptember	 2022	\nPUBLICATIONS	 	 \nLung	 Cancer	 Detection	 and	 Recognition	 using	 Deep	 Learning	 	\nMechanisms	 for	 Healthcare	 in IoT	 Environment	 	\nInternational Journal of Intelligent Systems and Applications in	 	\nEngineering	 	\n \n \nCost	 optimization	 in CNN	 for	 big	 data	 of share	 price	 	\nAIP Conference 	Proceedings	 	\n 	\n \n 	\nJanuary	 2024	 	 \n   \n  \n \nNovember	 2023', 2, 0, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 0),
(498, 117, 76, NULL, NULL, '76_117_196072348766b4bd1a5eea6_G-Prashanthi5.docx', 'G-Prashanthi5.docx', '\r\nPrashanthi GannavarapuPrompt Engineer / Generative AI Engineer \r\nBengaluru, IndiaPhone: (+91)-8106907575Email: gprashanthi05@gmail.com/ prashanthi.gannavarapu22@iimb.ac.inProfessional Summary\r\nA seasoned Generative AI Engineer and Natural Language Processing (NLP) Expert, with a proven track record in leading teams to pioneer and implement cutting-edge AI solutions. Specializes in crafting compelling prompts using Open AI&rsquo;s GPT technology, enhancing user interactions with AI. Proficient in advanced machine learning techniques, adept at refining content and driving operational efficiency. Possesses a strategic mindset and employs a data-driven approach to consistently deliver transformative results, elevating stakeholder satisfaction.\r\nSKILLS \r\n&bull; Data Science Toolbox: Python, NumPy, pandas, seaborn, matplotlib, scipy, scikit- learn, Spacy, NLTK, Pytorch, Keras, TensorFlow, SQL, PySpark, GitHub, Docker, Tableau, Power BI, MS Azure Open AI \r\n&bull; Machine Learning Algorithm: Supervised: Linear Regression, Ridge/Lasso, Logistic Regression, Naive Bayes, Support Vector Machine, Decision Tree, Bagging - Random Forest, Boosting- XGBoost, AdaBoost.Unsupervised: K-Means, DBSCAN, Clustering. Topic Modelling : LSA, NMF, LDA. \r\n&bull; Deep Learning and Generative ai: ANN, CNN, RNN, LSTM, Transformer, Hugging Face, LLM. NLP - Embedding, Classification, Summarization, Sentiment Analysis ,Topic Modelling, Document Intelligence, Knowledge Mining, BERT, GPT-4, Llama, Langchain, Prompt Engineering , Generative AI  Microsoft Azure AI , Cognitive AI , Computational Linguistics, GPT-3/4, ChatGPT, Gemini, Microsoft Co-pilot, Decision Trees, LLM&rsquo;s , RAG Architecture , Computer Vision, DALL-E, MidJourney, Sora.Project Management: Jira , Git , ITSM Suite, Agile , ServiceNow , Miro, ServiceNow Reporting, Performance Analytics, Microsoft Excel, Lean Six Sigma.\r\nLicenses &amp;amp; certifications\r\nPrompt Engineering for ChatGPT , Vanderbilt University -  Issued Jul 2023\r\nGenerative AI with Microsoft Azure Open AI from Great Learning\r\nMicrosoft Azure AI Fundamentals (AI 900) Certification\r\nSix Sigma with Python - Green Belt Certified &ndash; Indian Statistical Institute(ISI) &ndash; Issued Nov 2023\r\nSAFe.5 Practitioner\r\nITIL 4\r\nServiceNow Performance Analytics &ndash; Micro Certification\r\n  EDUCATION:\r\nMicrosoft Azure Generative AI &ndash; Great Learning (Mar&rsquo;24 &ndash; June&rsquo;24)\r\nExecutive Programme in Business Analytics and Intelligence (BAI), IIM Bangalore (2022-2023)\r\nExecutive Program in Business Management (part-time) , IIM Lucknow (2016-2017)\r\nB. Tech, Electronics Communication Engineering- BPUT Rourkela, Odisha (CGPA- 7.4/10) \r\nWork Experience\r\nGenerative AI Engineer, Wadhwani AI(contract)      Aug 2023 &ndash; PresentProject Description:\r\nImplemented advanced generative AI techniques to develop an AI tutor tailored for students enrolled in entrepreneurship courses on the Moodle platform. Leveraged GPT-3/4, BERT, T5, and NLP models to create personalized learning experiences, offering guidance, resources, and feedback to enhance students&#039; understanding of entrepreneurship concepts and skills.\r\nTechnologies Used:\r\nGenerative Models: GPT-3/4, BERT, T5\r\nNatural Language Processing (NLP) Techniques: LLaMa, GEMINI, Named Entity Recognition (NER), Sentiment Analysis, Topic Modelling, Word Embeddings (Word2Vec, GloVe), Part-of-Speech Tagging\r\nLearning Management System: Moodle\r\nResponsibilities:\r\nDeveloped and fine-tuned AI-driven educational content, aligning with entrepreneurship curriculum objectives and student learning styles.\r\nTailored AI tutor prompts to individual student needs and preferences, optimizing engagement and comprehension.\r\nApplied generative AI techniques such as GPT models to dynamically generate personalized learning material, including explanations, examples, and quizzes.\r\nUtilized NLP techniques such as sentiment analysis and named entity recognition (NER) to ensure the content&#039;s conversational accuracy and relevance, categorizing responses into Red-Amber-Green (RAG) status for student progress tracking.\r\nCollaborated cross-functionally to integrate the AI tutor seamlessly into the Moodle platform, ensuring alignment with educational goals.\r\nConducted iterative refinement of content and prompts based on user feedback, leveraging NLP insights for continuous improvement.\r\nImplemented the Retrieval-Augmented Generation (RAG) architecture, integrating retrieval models with generative AI techniques such as GPT models and Large Language Models (LLMs) like T5 and Langchain for content generation.\r\nEnhanced content relevance and coherence by leveraging LLMs within the Retrieval-Augmented Generation (RAG) framework, facilitating the generation of contextualized responses, including explanations, examples, and quizzes.\r\nEnsured the AI tutor dynamically adapts to individual student needs using the Retrieval-Augmented Generation (RAG) approach, optimizing engagement and learning outcomes.\r\nCollaborated cross-functionally to integrate the RAG architecture seamlessly into the Moodle platform, ensuring alignment with educational goals and student requirements.\r\nConducted iterative refinement of content and prompts based on user feedback and RAG insights, maximizing learning outcomes and student satisfaction.\r\nEducational Break &amp;amp; Skill Enhancement (Jul &lsquo;22 &ndash; Jul &lsquo;23)\r\nUtilized a career break for educational pursuits and skill enhancement. Pursued Certification Programme in Business Analytics from IIM ,Bangalore.\r\nAcademic Projects:\r\nAccident Risk Score Prediction for Swiss Re: Led a project to develop a predictive machine learning model for determining accident risk scores at Swiss Re. Collaborated with actuarial teams and achieved improvement in prediction accuracy compared to existing methods.\r\nSenior Business Insights Analyst , Citrix Jan&rsquo; 21 &ndash; Jun&rsquo; 22\r\nTechnologies used: SQL, ServiceNow Performance Analytics, Naive Bayes, Logistic Regression, BERT ,  Tensorlfow, Keras , NLP &ndash; TF-IDF , NLTK, Pandas libraries\r\nProject: Revolutionized service desk operations through advanced analytics, predictive modelling, and NLP, significantly enhancing efficiency and customer satisfaction..\r\nBusiness Impact: Achieved measurable improvements in operational efficiency and customer satisfaction by identifying bottlenecks and predicting future support needs.\r\nResponsibilities: \r\nDeveloped and led a BERT-based Automated Ticketing System, significantly enhancing ticket categorization accuracy and user satisfaction.\r\nEmployed advanced NLP techniques for data pre-processing and model fine-tuning, achieving a 15% improvement in categorization accuracy over traditional models.\r\nManaged large datasets for model training, employing data cleaning, and augmentation to improve model performance and effectiveness.\r\nReduced ticket resolution times by 20%, directly impacting service efficiency and contributing to a 10% increase in customer satisfaction scores.\r\nCollaborated with cross-functional teams for seamless integration, optimizing the model for computational efficiency and establishing a continuous improvement feedback loop.\r\nSenior Consultant, CapgeminiJul &lsquo;20 &ndash; Dec &lsquo;20\r\nInnovated Ticket Categorization Process: Spearheaded a lean project to redesign the ticket categorization process, employing machine learning algorithms to automate and improve accuracy. This initiative resulted in a 30% reduction in ticket resolution time and significantly decreased manual categorization errors, enhancing overall service delivery efficiency and customer satisfaction.\r\nAgile Project Management: Managed cross-functional teams in a fast-paced, agile environment to deliver project milestones ahead of schedule, demonstrating exceptional leadership in driving project success and team synergy.\r\nStakeholder Collaboration: Worked closely with IT, quality assurance, and customer service teams to ensure the new ticketing process aligned with business needs and customer expectations, fostering an environment of continuous feedback and improvement.\r\nSenior Business Analyst, Compugain Solutions  Nov &lsquo;17 &ndash; Oct &lsquo;19\r\nLed a team of 10-15 associates using agile methodologies to optimize project delivery.\r\nDeveloped performance metrics, driving improvements in project delivery times and quality.\r\nExecuted talent development initiatives, enhancing team capabilities and project outcomes.\r\nAssistant Service Delivery Manager , Unisys Sep &lsquo;15 &ndash; Nov &lsquo;17\r\nManaged shift operations and team engagement using lean principles, focusing on continuous improvement.\r\nSpearheaded data analysis projects, enhancing decision-making processes and operational efficiency.\r\nOwned change management, leading the team through agile practice adoption to increase responsiveness.\r\nService Manager , Tech Mahindra Jan &lsquo;12 &ndash; Sep &lsquo;15\r\nIdentified and implemented improvements in team performance and service delivery using lean and agile frameworks.\r\nBuilt and executed initiatives for hiring and developing top talent, improving team capabilities.\r\nUtilized databases for data extraction and analysis, providing insights to inform business strategies.\r\n', 2, 0, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 0),
(499, 117, 76, NULL, NULL, '76_117_12709312566b4bd1a5f07d_Gulshan_Kumar_MLEngineer.pdf', 'Gulshan_Kumar_MLEngineer.pdf', 'Guls h an  K um ar	\nMach in e l e a rn in g  e n g in eer	\n9103091562	 	g u ls h an ku m ar1 00g @ gm ail .c o m	 	lin ke d in .c o m /in /g u ls h an 100	 	Ja m mu, I n d ia	 	\ng it h ub.c o m /g u ls h an -1 00	 	\nE D U CAT IO N	\nBach elo r 	o f 	E n gin eerin g 	in  	C om pute r 	S cie n ce	\nU niv e rs it y  	o f 	J a m mu	\n12/2 020 &ndash;  0 7/2 024	 |  J a m mu,	 I n d ia	\nI N TER N SH IP S	\nM ach in e 	Le a rn in g 	In te rn	\nT a le n flo w\n06/2 024 &ndash;  p re se n t	\n&bull;D eve lo p ed  a  c h atb ot u sin g N LP  a n d  R AG	 	\nte ch n iq ues f o r r e sp on siv e  q uery  r e so lu tio n  o n  t h e	 	\nco m pan y&#039;s  w eb sit e .\n&bull;U til iz e d  O pen AI A P I, P yth on , a n d  P in eco n e D B.	\nD ata  	S cie n ce  	In te rn	\nZ id io  	D eve lo p m en t	\n02/2 024 &ndash;  0 3/2 024	\n&bull;C re a te d  a n d  e va lu ate d  p re d ic tiv e  a n aly tic s a n d	 	\npatt e rn  r e co gn it io n  m od els .\n&bull;Im ple m en te d  f e a tu re  e n gin eerin g, c la ssif ic a tio n ,	 	\nan d  r e g re ssio n  f o r p erfo rm an ce  o ptim iz a tio n .	\nP R O JE C TS	\nAI 	P ow ere d  	C alo rie  	B urn  	P re d ic tio n  	an d  	\nM an age m en t 	T o ol	\n05/2 024 &ndash;  0 6/2 024	\n&bull;D eve lo p ed  a  F la sk  w eb  a p p u sin g X G Boost t o	 	\np re d ic t e xe rc is e  c a lo rie  b urn  f r o m  a  K aggle	 	\nd ata se t.\n&bull;In te g ra te d  a  u se r-fr ie n d ly  i n te rfa ce  w it h  B oots tra p	 	\nfo r r e a l- t im e p re d ic tio n s.	\nP la n t 	D is e a se  	P re d ic tio n  	usin g 	C on vo lu tio n  	\nN eu ra l 	N etw ork s	\n04/2 024 &ndash;  0 5/2 024	\n&bull;D esig n ed  a  C on vo lu tio n al N eu ra l N etw ork  ( C N N)	 	\nm od el t o  c la ssif y  p la n t d is e a se s f r o m  l e a f i m age s.\n&bull;Im ple m en te d  a  w eb  a p plic a tio n  f o r i n sta n t d is e a se	 	\nd ia gn osis  u sin g u p lo ad ed  i m age s.	\nA I 	p ow ere d  	ch atb ot 	fo r 	T a le n flo w  	sta rtu p	\n06/2 024 &ndash;  p re se n t	\n&bull;B uil d in g a n  A I- d riv e n  c h atb ot w it h  R AG  a n d	 	\nO pen AI A P I t o  s tre a m lin e c u sto m er i n q uir ie s.\n&bull;E n han cin g u se r e xp erie n ce  t h ro u gh  i n tu it iv e ,	 	\na u to m ate d  r e sp on se s a n d  r e a l- t im e a ssis ta n ce .	\nS K IL LS	\nD ata  s c ie n ce , M ach in e l e a rn in g a n d  D eep  l e a rn in g\nPyth on , S u p erv is e d  a n d  u n su p erv is e d  a lg o rit h m s,	 	\nN eu ra l N etw ork s, A N N, C N N, R N N, L S T M , F e a tu re	 	\ne n gin eerin g, F e a tu re  s e le ctio n , N atu ra l L a n gu age	 	\nP ro ce ssin g e tc .\nP yth on  P ack age s a n d  F ra m ew ork s\nScik it -le a rn , T e n so rflo w , K era s, N um py, P an d as,	 	\nM atp lo tlib , N LT K , O pen C V\nLa n gu age s\nH TM L, C SS , J a va sc rip t, J q uery , N od e.js , F la sk\nD ata B ase s\nS Q L, P o stg re S Q L\nGen era tiv e  A I\nG PT, R AG , G em in i,  P in eco n e, H uggin g F a ce ,	 	\nLa n gch ain\nM LO PS\nG CP, G it , D ock e r, S tre a m lit	\nC ER TIF IC AT IO NS	\nMach in e l e a rn in g s p ecia liz a tio n\nD eep  l e a rn in g s p ecia liz a tio n\nLa n gch ain  f o r L LM  A p plic a tio n  d eve lo p m en t\nLa n gch ain  -  C hat w it h  y o u r d ata  ( d eep le a rn in g.a i)\nP ro m pt e n gin eerin g f o r d eve lo p ers\nS Q L f o r D ata  A n aly sis  -  I n te rn sh ala	\nO RG AN IZ AT IO NS	\nCheg g 	In d ia	\nS u b je ct 	M atte r 	E xp ert	\n0 5/2 023 &ndash;  p re se n t	\n&bull;Part t im e S u b je ct M att e r E xp ert a t C heg g,	 	\np ro fic ie n tly  a d dre sse d  o ve r 3 20 p ro bab il it y  a n d	 	\nsta tis tic s q uestio n s.	\nG eek sfo rG eek s\nTe ch n ic a l 	w rit e r	\n0 1/2 023 &ndash;  0 5/2 023	\n&bull;C on tr ib ute d  2 3 c le a r a n d  r e a d er-fr ie n d ly  t e ch n ic a l	 	\nartic le s t o  G FG , r e a ch in g o ve r 1 00,0 00 r e a d ers .', 2, 0, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 0),
(500, 117, 76, NULL, NULL, '76_117_142130915366b4bd1a5f225_HAMZA_SHAKEEL_IBM.pdf', 'HAMZA_SHAKEEL_IBM.pdf', 'HAM ZA  S H AK EEL	\nPYT H O N D EVE LO PER	\nham za .9 595@ gm ail .c o m	 	8808916347	 	Lu ck n ow	 	lin ke d in .c o m /in /h am za -s h ake el- 5 21b 36135	 	\nP ro fil e\nE xp erie n ce d  P yth on  D eve lo p er w it h  e xp ertis e  in  d esig n in g a n d  m ain ta in in g P yth on  s c rip ts  fo r s y ste m  t a sk s a n d  d ata\np ro ce ssin g.  P ro ve n  a b il it y  t o  im ple m en t b est p ra ctic e s f o r c o d e r e a d ab il it y ,  m ain ta in ab il it y ,  a n d  p erfo rm an ce .  S kil le d\nin  d eve lo p in g a n d  d ep lo yin g m ach in e le a rn in g m od els ,  s p ecia liz in g in  n atu ra l  la n gu age  p ro ce ssin g a n d  p re d ic tiv e\na n aly tic s.\nE d uca tio n\nBach elo r 	o f 	T e ch n olo gy, 	S R M CEM	05/2 014 &ndash;  0 8/2 018	 |  	L u ck n ow ,	 , I n d ia	\nP ro fe ssio n al E x p erie n ce\nD ata  	A I 	D ev e lo p er, 	K yn d ry l	0 2/2 022 &ndash;  p re se n t	 |  	G urg a o n ,	 I n d ia	\n&bull;P ro fic ie n t i n  i m ple m en tin g a n d  f in e-t u n in g m on it o rin g s o lu tio n s u sin g P ro m eth eu s a n d  G ra fa n a.\n&bull;D ep lo ye d  a n d  C on fig u re d  P ro m eth eu s m on it o rin g f o r B harti A ir te l E n han cin g 5 g  r e a d in ess o f t h e c lie n t\n&bull;Exte n siv e  i n vo lv e m en t i n  L in ux/U nix  s y ste m  a d m in is tra tio n , t ro u b le sh ootin g a n d  n etw ork in g i n  L in ux e n vir o n m en t\n&bull;VM s/p ro je ct d ep lo ym en t a n d  h an d ove r t o  t h e c u sto m er, o th er t a sk  i n clu d e V M  r e b uil d , m an agin g c o m pute s,	 	\nc o n tro lle r a s w ell a s a p plic a tio n  h ea lt h  a n d  s e rv ic e s.\n&bull;C on tr ib ute d  i n  d eve lo p m en t o f a n  A I- d riv e n  c h atb ot l e ve ra gin g P yth on  a n d  H uggin g F a ce &#039;s  L LM  m od els , i n clu d in g	 	\nG oogle P alm 2 t o  p ro fic ie n tly  m an age  c u sto m er i n q uir ie s c o n ce rn in g A ir te l&#039;s  5 G  s e rv ic e s. I n te g ra te d  L a n gC hain  f o r	 	\nad va n ce d  l a n gu age  p ro ce ssin g, f o ste rin g c o n tin ual e n han ce m en ts  i n  c o m pre h en sio n  a n d  r e sp on se  q ualit y	\nS yste m  	En gin eer(P yth on  	d ev e lo p er), 	T a ta  	C on su lt a ncy  	S erv ic e s	1 0/2 018 &ndash;  1 1/2 021	 |  	B an ga lo re ,	 I n d ia	\n&bull;I m ple m en te d  a d va n ce d  a lg o rit h m s i n  P IX E R  t o  o ptim iz e  c o p y i t e m  s e le ctio n  b y i n te g ra tin g f e a tu re s l ik e  P C  c h ars ,	 	\nW eig h t C hars , a n d  d eta il e d  r e ta il e r i m age s, s ig n if ic a n tly  e n han cin g o p era tio n al e ffic ie n cy  a n d  a cc u ra cy  t o  d riv e	 	\no ve ra ll b usin ess s u cce ss.\n&bull;In it ia te d  w it h  d ata  c le a n in g, h an d lin g m is sin g v a lu es a n d  o u tlie r d ete ctio n  t o  e n su re  h ig h  d ata  q ualit y  a n d  r e lia b il it y .	  	\n&bull;A p plie d  a d va n ce d  N LP  p re p ro ce ssin g t e ch n iq ues i n clu d in g l o w erc a sin g, a lp han um eric  f il t e rin g, s te m min g,	 	\nto ke n iz a tio n , a n d  s to p  w ord s r e m ova l t o  p re p are  t e xtu al d ata  i n  P IX E R  f o r s u b se q uen t m od elin g s ta ge s.\n&bull;P erfo rm  f e a tu re  e n gin eerin g t o  d eriv e  n ew  f e a tu re s t h at m ig h t e n han ce  m od el p erfo rm an ce  ( n um ber_ ch ara cte r,	 	\nn um ber_ se n te n ce , n um ber_ w ord s).\n&bull;U til iz e d  B ag o f W ord s a n d  T F-ID F f o r t e xt d ata  v e cto riz a tio n , w it h  h yp erp ara m ete r t u n in g s p ecif ic a lly  t o  T F-ID F t o	 	\no ptim iz e  p ara m ete rs  s u ch  a s m ax_ fe a tu re s a n d  n gra m _ra n ge\n&bull;E n han ce d  m od el p erfo rm an ce  t h ro u gh  a d va n ce d  t e ch n iq ues l ik e  S M OTE ( S yn th etic  M in orit y  O ve r-s a m plin g	 	\nTe ch n iq ue) a n d  A D ASYN  t o  a d dre ss d ata  i m bala n ce  i s su es, c ru cia l f o r a cc u ra te  p re d ic tio n s i n  s k e w ed  d ata se ts .\n&bull;U til iz e d  m ach in e l e a rn in g a lg o rit h m s i n clu d in g R an d om  F o re st, L in ea r S VC  ( S u p port V ecto r C la ssif ie r), L o gis tic	 	\nR eg re ssio n , a n d  M ult in om ia l N aiv e  B aye s ( M NB),  f o r m od elin g a n d  p re d ic tio n  t a sk s.\n&bull;Im ple m en te d  h yp erp ara m ete r t u n in g u sin g g rid  s e a rc h  w it h  c ro ss -v a lid atio n  t o  s y ste m atic a ll y  o ptim iz e  m od el	 	\np ara m ete rs , e n su rin g r o b ustn ess a n d  g e n era liz a b il it y .\n&bull;U til iz e d  e va lu atio n  m etr ic s s u ch  a s p re cis io n -r e ca ll c u rv e s a n d  F 1  s c o re s t o  a ss e ss m od el p erfo rm an ce	 	\nc o m pre h en siv e ly .	\nS kil ls\nP yth on , M ach in e L e a rn in g, P an d as, M yS Q L, L LM , L a n gC hain , G en  A I, P ro m eth eu s, G ra fa n a, L in ux, E xc e l, D ock e r, A W S', 2, 0, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 0);
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(502, 117, 76, NULL, NULL, '76_117_170586192166b4bd1a5f912_Maniganda.pdf', 'Maniganda.pdf', 'Maniganda R.K	 	\n \n 	\nE-Mail:	 rmaniganda@gmail.com	 	\n 	 	 	 	 	 	Mobile:	 91	-9916688811	 / 8073190432	 	\n \n \nSynopsis	 	\n \nResults	-driven professional with 19 years of experience leading AI/ML	, MLOps, LLM, Gen AI, NLP, 	\nand Data Science init iatives across mult iple industries. Proven track record in buildin g and \nma	nagin g high	-performin g teams, driving innovation, and delivering impactfu l solution s. Expertise 	\nin leveragin g advanced analytics and machin e learning to solve complex business challenges.	 	\n \n \nSkills	:    Technical:	 AI &amp; ML, MLOps, Natural Language Processing (NLP), Large Language Models 	\n(LLM), Predictive Modeling, Data Engineering, Statistical Analysis	 	\n Management:	 Team Leadersh	ip &amp; Management, Agile/Scrum Methodology, Project Management, 	\nStrategic Planning, Stakeholder Communication	 	\n Tools &amp; Platforms:	 Business Intelligence Tools, Cloud Platforms (AWS, Azure), 	SQL	, Teradata, Aster, 	\nHadoop, Adobe Test &amp; Target, Tableau, Raw, ch	art.js, Numpy, Pandas, Scikit	-Learn, TensorFlow, 	\nGoogle Colab, DVC, Image Tagger, CVAT, MLFlow	 	\n \nTechnical Proficiencies	 	\n 	Proficiency in Spark, 	SQL	, Python, and Scala	 	\n 	Experience with data warehousing, E TL/ELT processes, and data modeling	 	\n 	Knowledge of CI/CD practices and tools, particularly Azure DevOps	 	\n \n 	\nORGANIZATIONA L EXPERIENCE	 	\n \nLead 	(Jan&rsquo;23	 &ndash;Mar&rsquo;24)	 	\n \nTransunion Global Technology Center	 	\n 	\n&bull; 	Led cross	-functional projects using advanced data modeling and analysis techniques to discover 	\ninsights that guided strategic decisions and 	uncovered optimization opportunities.	 	\n&bull; 	Implemented AI/ML	 initiatives, employing MLOps practices to enhance model development and 	\ndeployment.	 	\n&bull; 	Spearheaded projects in LLM and Gen AI, driving advancements in natural language understanding \nand generation.	 	\n&bull; 	Managed a team of data scientists and engi	neers, ensuring alignment with business goals and 	\ndelivering high	-quality solutions.	 	\n&bull; 	Established close working relationships with other technology teams and business users to \nunderstand requirements and execute projects.	 	\n&bull; 	Improved mortgage risk assess	ment accuracy by 20%, reducing defaults and optimizing loan 	\nportfolio performance.\n\nKey Achievements	 	\n- 	Design and Development:	 Developed and	 optimized large	-scale data processing pipelines 	\nusing Databricks on Azure, including ETL processes and scalable data models. 	 	\n- 	Azure Integration:	 Integrated Databricks with Azure services like Azure Data Lake, Azure 	SQL	 	\nDatabase, Azure Synapse Analyti	cs, and Azure Machine Learning, utilizing Azure DevOps for 	\nCI/CD.	 	\n- 	SaaS Product Exposure:	 Collaborated with product teams to understand data requirements 	\nand integrate SaaS product data into the data platform. 	 	\n- 	Performance Optimization:	  Monitored	 and optimized data pipelines and queries, 	\nimplementing best practices for data governance, security, and compliance.	 	\n- 	Collaboration and Leadership:	 Worked closely with data scientists, analysts, and other 	\nstakeholders, mentoring junior engineers and 	promoting best practices. 	 	\n- 	Documentation and Reporting:	 Maintained comprehensive documentation of data 	\nengineering processes, designs, and solutions, generating reports and dashboards for \ninsights.	 	\n- 	BPM Solution Architecture	: Pr	oven expertise in architecting, designing, and implementing 	\nscalable and efficient BPM solutions for diverse business processes.	 	\n \nAssistant Manager Operations	 (Aug&rsquo;21	- Dec&rsquo;22	) 	\n \nArchwell Operations India Pvt Ltd, Bangalore	 	\n 	\n&bull; 	Designed and implemented data strategies to drive business outcomes.	 	\n&bull; 	Developed and deployed machine learning models, optimizing decision	-making processes.	 	\n&bull; 	Collaborated with cross	-functional teams to integrate AI solutions into business operations.	 	\n&bull; 	Mentored 	team members, fostering professional growth and develop	ment.	 	\n&bull; 	Ensured data accuracy and consistent reporting by designing and creating optimal processes and \nprocedures.	 	\n&bull; 	Client Collaboration and Requirements Translation	: Skilled in understanding client business 	\nrequirements and translating them	 into technical BPM solutions.	 	\n \n \nAssistant Manager Operations	 (Oct	 &#039;19 	- May&#039;21)	 	\n \nFirst	source	 Solutions Ltd, Bangalore	 	\n 	\n&bull; 	Proficient in 	SQL	, Teradata, Aster, Hadoop, Adobe Test &amp; Target, Tableau, Raw, chart.js.	 	\n&bull; 	Led AI/ML projects, focusing on NLP and predicti	ve modeling to enhance business intelligence.	 	\n&bull; 	Managed stakeholder relationships and delivered insights	-driven solutions.	 	\n&bull; 	Built, developed, and maintained dashboards and performance metrics to support key business \ndecisions.	 	\n&bull; 	Technical Leadership	: Experienced in providing technical leadership and guidance to development 	\nteams, ensuring adherence to coding standards and best practices.	 	\n&bull; 	Snowflake Data Warehousing	: Proficient in Snowflake with hand	s-on experience in implementing 	\nmodels via DBT.	 	\n \nTeam Leader	 - Operations (Sep &#039;1	8 - Sep	 &#039;19	) 	\n \nFirstsource Solutions Ltd, Bangalore\n\n&bull; 	Utilized Numpy, Pandas, Scikit	-Learn, TensorFlow 1 &amp; 2, Google Colab,	 DVC, Image Tagger, CVAT, 	\nand MLFlow.	 	\n&bull; 	Directed a team of data scientists, overseeing project execution and ensuring deliverables met \nquality standards.	 	\n&bull; 	Conducted R&amp;D to develop new algorithms, assessing the cost	-benefit of models and approaches.	 	\n&bull; 	Pre	-Sales and Technical Expertise	: Strong background in supporting pre	-sales activities, including 	\ntechnical presentations, client demonstrations, and proposal development.	 	\n 	 	\nTeam Leader 	&ndash; Operations	 (Dec &rsquo;13 	- Sep &#039;18)	 	\n \nRockedge solutions Pvt Ltd n/k/a American Core Title Services	 	\n 	 	\n&bull; 	Led data science and analytics projects, driving innovation and operational efficiencies.	 	\n&bull; 	Developed machine	 learning algorithms and predictive models for business applications.	 	\n&bull; 	Managed data with 	SQL	, key	-value stores, columnar databases, and graph databases.	 	\n&bull; 	Communicated insights and business impacts to stakeholders in leadership, technology, sales, \nmarketing, and product teams.	 	\n&bull; 	BPM Standards and Tools	: Proficient in BPMN 2.0 standards and hands	-on experience with BPM 	\nplatforms like Camunda,	 IBM BPM, and programming languages	 	\n \n \n \nSenior Quality Analyst 	&ndash; Operations	 (Dec	&rsquo;10 	- Dec &rsquo;13)	 	\n \nISG Novosoft Technologies PVT. L	td. , Bangalore	 	\n 	\n&bull; 	Applied advanced statistics, computer vision, and time	-series analysis using 	 TensorFlow and 	\nPyTorch.	 	\n&bull; 	Conducted advanced data analysis to support business decisions.	 	\n&bull; 	Collaborated with business stakeholders to identify analytical requirements and deliver \nactionable insights.	 	\n&bull; 	Communication and Mentorship	: Excellent communication and interpersonal skills, with 	\nexperience in leading workshops, training sessions, and mentoring development teams.	 	\n&bull; 	Data Visualization	: Proficient in using data v	isualization tools like Power BI to create 	\ninsightful reports.	 	\n \nProcess Executive 	&ndash; Operations	 (Sep &rsquo;05 	- Dec&rsquo;10	) 	\n \nIntertitle AKA First American India	 	 	\n 	\n&bull; 	Analyzed business processes and data to optimize operational performanc	e. 	\n&bull; 	Prepared reports and presentations to communicate findings and recommendations.	 	\n&bull; 	Developed skills in data handling and analysis, laying the foundation for career 	growth in analytics.	 	\n&bull; 	Analytical and Problem	-Solvin g Skills	: Strong analytical skills to tackle complex data problems and 	\nderive meaningful insights.', 2, 0, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 0),
(503, 117, 76, NULL, NULL, '76_117_52495310266b4bd1a5fc53_Mohit_Agrawal_DATA_SCIENCE.pdf', 'Mohit Agrawal_DATA SCIENCE.pdf', 'Mohit Agrawal	 	\nagrawalmohit.ma@gmail.com 	| 901	-124	-4748 |	 	\n 	\nEDUCATION AND	 HONORS	  	\n 	\n&bull; 	International University of Applied 	Sciences	     	                  	Berlin, Germany	                                                                          	 	\n&bull; 	Master	&rsquo;s in Computer Science	 (MScs)                                                                        	              	\nJAN2023	-Present	  	\n&bull; 	Relevant Coursework: 	Machine Learning, Data Science	, Statistics, Big Data 	\nAnalytics, Probability &amp; 	   Advanced	 Mathematics	 	\n 	\n&bull; 	Sant Gadge Baba Amravati University	                    	          	Amravati, Maharashtra	                                                                	 	\n&bull; 	Bachelor&rsquo;s of Engineering	 (B.E.)	                                                                                       	                                               	 	\nRelevant Coursework :	- Computer Science and Engineering	 	\nR	ELEVANT 	SKILLS 	 	\n 	\n&bull; 	Programming Languages	: Python, Java, C, HTML, 	CSS	, My	SQL	 	\n&bull; 	Statistics	: Various Hypothesis Testing, Time Series, Probability Theory	 	\n&bull; 	Machine Learning	: Algorithms for Regression (Linear, Logistic), Classification (Decision Trees, 	\nRandom	-Forest, XG	 Boost, SVM, Na&iuml;ve Bayes, k	-NN), PCA, Clustering 	(k	-means, Hierarchical)	 	\n&bull; 	NLP	: Text Processing, Web Scrapping, Sentiment Analysis, Unigram, Bigram	 	\n&bull; 	Deep Learning	: ANN, CNN,	 RNN, Text mining	 	\n&bull; 	Data Visualization	: Tableau,	 Power BI	, Ms Excel	 	\n&bull; 	Advanced Mathematics	: Linear Algebra,	 Calculus,	 Vectors	 	\n&bull; 	Basic Knowledge of 	Big Data	 (Apache Hadoop Frame	-Work	) 	\n  \n \nPROJECTS	 	\n \nNetflix Subscriptions Forecasting using Python	 	\n 	\n&bull; 	Designed 	and implemented a Python	-based Netflix subscription forecasting system, utilizing advanced 	\ndata analysis and predictive model	ling techniques.	 	\n&bull; 	Leveraged historical subscription data to develop accurate forecasts, facilitating data	-driven decision	-	\nmaking for strategic planning.	 	\n&bull; 	En	hanced subscriber growth and retention strategies by providing insightful predictions through the 	\napplication of advanced analytical tools.	 	\n&bull; 	Contributed to informed decision	-making processes, empowering the team with actionable insights for 	\noptimizing Netflix subscription management.	 	\n \nReal or Fake 	&ndash; NLP with Disaster Tweets	:  	\n&bull; Implemented Natural Language Processing techniques to the 	Disaster Tweets classifying them either 	\nReal or Fake. Achieved a public score of 0.79681 on Kaggle. (NLP, Text Pre	-processing, Python	)\n\nCredit 	Score c	lassi	fication 	using Maching L	earning	 	\n 	\n&bull; 	Spearheaded a comprehensive project on credit score classification utilizing a variety of machine \nlearning algorithms including Logistic Regression, Random Forest, Decision Tree, Gaussian Naive \nBayes, KNN, and SVM.	 	\n&bull; 	Applied advanced statistical models to analyze diverse credit data, enhancing predictive accuracy and \nrisk assessment for creditworthiness.	 	\n&bull; 	Successfully implemented a multi	-model approach, showcasing proficiency in algorithm selection and 	\nfine	-       	tuning to achieve optimal classification performance.	 	\n&bull; 	Contributed to the development of a robust credit scoring system, showcasing a deep understanding of \nmachine learning techniques and their application in financial risk assessment.	 	\n \n \n \nC	ERTIF	ICATIONS	 	\n   	\n&bull; 	Certified in 	Google data Analytics	 Specialization course by 	Google	 	\n&bull; 	Certified in 	Data Analytics and Visualization Job Simulation	 by	 Accenture	 North America	 	\n&bull; 	Certified in 	Data Analytics Consulting	 Virtual Internship by 	KPMG	 	\n&bull; 	Certified in 	Artificial 	Intelligence	 virtual	 Experience Internship by 	Cognizant	 	\n&bull; 	Certified in 	Software engineering	 virtual experience program by 	JP Morgan	 and 	Goldman Sachs	 	\n \n 	\nACTIVITIES	 	\n  	\n&bull; 	Participated in 	Workshop 	&lsquo;TECHTRUNK VENTURES&rsquo; on Android Application 	\nDevelopment	 2018	 	\n&bull; 	Participated in 	college events	 &ldquo;Blind C	 and 	Error Handling	&rdquo;. 	\n&bull; 	Participated in Workshop, 1 day of 	GUVI AI For INDIA	, online 2021	 	\n&bull; 	Core Member of 	PACE 	(Pioneers Association of Computer Engineers) Club.	 	\n&bull; 	Core Member of 	EUPHORIA	 Committee 2019	-20, 2020	-21.	 	\n&bull; 	Worked in Pooja Committee at College Ganesh	 Festival	. 	\n \n \n 	\nPROFILE LINKS	 	\n         	 	\nLinkedIn Profile:	 https://www.linkedin.com/in/mohit	-agrawal45	 	\n \n \nGitHub Profile:	   	https://github.com/	Mohhitt45', 2, 0, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 0),
(504, 117, 76, NULL, NULL, '76_117_140896490066b4bd1a5fe3c_Mohit_Resume_IA.pdf', 'Mohit_Resume_IA.pdf', '&bull; 	Techno	-Functional professional with 17 years of experience	 in IT Digital Transformation (IT Strategy + Digital Enterprise 	 	\nArchitecture), AI	-ML+ Generative AI, Data Science, RPA, DevOps, Cloud Computing Migration, Microservices, API, Agile, 	CRM, E	-comm., Change Management	). Possess good knowledge about IT service delivery management and managing IT projects 	in global delivery model	       	\n&bull; 	Digital Transformation Strategy &amp; Architecture	- develop a digital strategy, aligned with the overall business strategy, promote digital 	\ntransformation, the business value of technology and specific digitalization initiatives. Actively and continuously consult C	-level stakeholders 	\non digitalization. Defi	ne and steer digitalization projects and proof of concepts. In	-depth knowledge of cloud technologies, GENAI technology, 	\nML tools, data modelling, data warehousing, data integration, and data management best p	ractices.	      	\n&bull; 	AI-ML Implementation	- Strong Understanding of the AI Ecosystem: Comprehensive knowledge of AI ML, Deep Learning Frameworks, 	\nGenerative AI, including LLMs, 	Prompt Engineering Techniques	, MLOps, LLMOps, RAG frameworks Llama Index, Lang Chain, 	Gemini	, 	\nOpenAI	, Vertex	 AI. Hands on experience in AWS ML Services like SageMaker, OpenSearch, TensorFlow, PyTorch, and Kubernetes. 	Python, 	\nPower BI.	  	\n&bull; 	Data Management	- Knowledge of design and implement of the robust data integration strategies, including ETL processes, 	Data Analysis &amp; 	\nVisualization	, APIs, real	-time data pipelines, data governance, data quality, Data Warehouses, Data Lakes and Data Modelling techniques. 	 	\n&bull; 	Cloud Computing Transformation	- Expert level experience in Cloud 	Migration (	AWS	, GCP	, Azure)	, Virtualization, Automation, Infrastructure	-	\nas-Code, Application Transformation,	 integration into existing IT environments and proficient in multiple service areas and technologies.    	 	\n&bull; 	Pre	-Sales 	- Coordinating in Pre	-Sales objectives and assignments with project teams, directing strategies leading to successful outcomes and 	\nexecution. Worked with vendors to produce anticipated outcomes. Ensured product demonstrations fully functional and ready to 	address 	\ncustomer queries.	 Documentation for various artifacts and collaterals, RFIs/RFPs.    	 	\n&bull; 	Domains Knowledge	: - BFSI(Cards and Payments, Digital Banking), Supply Chain, Telecom.     	 	\n&bull; 	Able to manage large Agile project teams	, providing vision and direction to the Agile development team and stakeholders throughout the 	\nproject and conducting proper story point estimation, Scrum ceremonies respectively and for the Product and translating requi	rements into 	\nUser Stories and to ens	ure that Release.	      	\n&bull; 	Extensive international experience across APAC, Europe, EMEA and USA.     	 	\n  	&bull; 	PG Program in Management from IMT Ghaziabad     	 	\n&bull; 	Master of Business Administration from DEAKIN University, Australia (Pursing)     	 	\n&bull; 	Bachelor of Technology in Electronic &amp; Telecommunications.     	 	\n&bull; 	Post Graduate Program in Digital Transformation	- Purdue University     	 	\n&bull; 	Digital Transformation Certification	- BCG (University of Virginia)     	 	\n&bull; 	Digital Disruption &amp; Strategies for a Digital Transformation     	 	\n&bull; 	Generative AI Fundamentals    	 	\n&bull; 	Generative AI for Everyone     	 	\n&bull; 	Generative AI for Sales and Services Professionals    	 	\n&bull; 	Introduction to Responsible AI	- Google   	 	\n&bull; 	DP	-203 Data Engineering on Microsoft Azure    	 	\n&bull; 	AI-900	 Microsoft Azure AI    	 	\n&bull; 	AZ	-900 Microsoft Azure Fundamental    	 	\n&bull; 	Google Certified Professional Machine Learning Engineer    	 	\n&bull; 	Generative AI with Large Language Models by Deeplearning.ai    	 	\n&bull; 	Post Graduate Diploma in Advanced Computing (CDAC, Pune)     	 	\n&bull; 	Data Science, Analytics &amp; AI for Business     	 	\n&bull; 	EXIN 	- Certified Agile Scrum Master (ASM)     	 	\n&bull; 	AWS Certified Solutions Architect     	 	\n    	\n             	ORGANISATIONAL &amp; EMPLOYMENT EXPERIENCE	      	\n      	  INFOSYS CONSULTING, Singapore (via Technopals)  	 	               	Jun 2022 	&ndash; May 2024 	     	\nResponsibilities: 	 Principal 	Consultant 	- AI ML + Gen AI 	Architect	 	\n&bull; 	Responsible for the End	-to-end Digital Transformation Strategy, IT Architecture, planning and implementation, IT roadmap development, 	\nCreation and maintenance. 	 	\n&bull; 	Provide architect solution and strategy of an AI+Data and GenAI, including the identification and qualification of its use ca	ses, and the 	\ndefinition of a Target Operating Model for the refactoring of its technology platform and implemented Generative AI so	lutions within a bank, to 	\ntransform IT businesses.    	 	\n&bull; 	Collaborate with stakeholders to comprehend business requirements and convert them into technical solutions utilizing AI and 	Generative AI 	\ntechnologies on the AWS	/Azure/GCP	 stack.    	 	\n            	   EDUCATIONAL QUALIFICATION and CERTIFICATIONS\n\n&bull; 	Play a key role in collaborating with clients and internal teams to comprehend business requirements, challenges, and opportu	nities. 	\nDesigned scalable and efficient AI/ML/GenAI solutions that align with client needs and strategic goals, considering deploym	ent models and 	\nintegration with existing tools.  	 	\n&bull; 	As PM of CoE Digital Transformation Agile Team of 2 Largest Banks of SG and PH for their Customer journey on Retail Digital B	anking, Card 	\nand Payments, CASA and Credit Card. Manage several Technology partners and Vendors from local and various countries. T	he coordination 	\nfor the Development, Testing, Deployment, Full Delivery management and providing the Innovative strategic solutions to modern	ize 	\ntechnology architecture.     	 	\n&bull; 	Implemented 	3 AI ML projects in AIML + LLM	- ChatGPT Question Answering (ChatGPT respond to customer questions from custom 	\nknowledge base. Few shot learning methodologies used) and Hyper Automation 	- Enquiry Categorization (A customer submits his enquiry on 	\nwebsite, the	 goal is to identify sales specific enquiries, it boosted the sales by 45	%) and	 a Payment 	Syste	m Automated	 Fraud 	detection 	\n(improve	 the efficiency, security, and user experience of the payment system	).   	\n&bull; 	Manage a team of MLOPs, looking into model deployment, containerization, and orchestration (Kubernetes), cloud platforms AWS,	 GCP,	 	\nAzure) for model deployment and	 management	. 	\n&bull; 	Co	nduct 	Pre	-Sales product	 demonstrations, presentations, and workshops to showcase the capabilities and benefits of our AI/ML offerin	g. 	\nAssist	ing	 in the preparation of proposals, RFP responses, and other technical documentatio	n. P	rovide technical expertise and guidance 	\nduring the sales process to ensure alignment with customer needs and expectati	on.	 	\n&bull; 	Conduct in	-depth consultations with businesses to understand their objectives, challenges, and opportunities for AI and converts data se	rvice 	\nand analytics requirements into effective solutions using cloud or on	-premise analytics and relevant design patter	ns, incorporating Generative 	\nAI techniques when advantageous. Establishes technical scope and objectives by conducting research and collaborating with the	 project team 	\nduring the solutioning phase, integrating Generative AI concepts where appropriate.   	 	\n&bull; 	Research and explore different data sources, work with data and system experts to understand the data and also take care of t	he data 	\nintegration strategies, including ETL processes, APIs, real	-time data pipelines, data governance, data quality, Data Wareho	uses, Data Lakes 	\nand Data Modelling techniques. Perform data cleaning, pre	-processing, feature engineering and build relevant models and algorithms to 	\nconduct meaningful analysis.    	 	\n&bull; 	Work within a cross	-functional matrix team comprising data analyst, business users, data engineers etc., and guide the team in developing 	\nartificial intelligence and machine learning models to extract insights, from structured and unstructured data, that o	ptimize business outcomes.    	 	\n&bull; 	Principal Consultant for AI+ML+Gen_AI(LLM) Practice; managed the execution of Pilots projects &amp; Proof of concepts (POCs), Poi	nt of Views 	\n(POVs), converted them to long term projects, defining success criteria. Help clients embed innovation into their busin	ess model by 	\nconceiving and delivering digital innovations and solutions.     	 	\n&bull; 	Manage the adoption, and operationalization of Cloud Platforms Migration, Hybrid cloud and Data Flow and Data Lake. Responsib	le for 	\ndesigning, implementing, and managing cloud migration environments as per customer requirements.     	 	\n&bull; 	Delivered the AI solution for which results in FTE and Cost saving.      	 	\n    \n    	\n  	\n     UST Global, BlueConch, Pune	- Sr Program Manager 	     	Jan 2022 	&ndash; May 2022 	     	\nResponsibilities 	&ndash;     	 	\n&bull; 	Understanding and synthesizing the latest trends and breakthroughs in emerging technologies; offerings solutions, integrating	 and 	\nimplementing relevant (CMS, AWS, AI	-ML, RPA, Payment Systems) innovations with clients. Providing all new opportunities conver	sion 	\nofferings.     	 	\n&bull; 	Experience leading engineering discussions around technology decisions and strategy related to a product     	 	\n     	\n  \nCMA CGM SSC, Chennai 	&ndash; Deputy General Manager	     	\n  \nJun 2020 	&ndash; Jan	-2022	     	\nResponsibilities 	&ndash;     	 	\n&bull; 	Leading the 	COE Digital Transformation &amp; Innovation	- (Workflow Solution + AI/ML + RPA	-OCR + Move2Cloud Migration) as Sr. Manager 	\nIT - taking care of delivery in Digital Transformation to GBS while supporting seamless operations and compliance IT activity (i.e	., SOX, 	\nGDPR) in Corporate IT environment	      	\n&bull; 	Providing solutions to bridge the gap between business and technology with expertise in managing complex programs and multipl	e concurrent 	\nprojects.	      	\n&bull; 	Support &amp; develop customized AI and automation strategies aligned with business goals and industry best practices.    	 	\n&bull; 	Accountable for creating project deliverables that meet or exceed the expectations of the project stakeholders. Co	-ordinates with team 	\nmembers, including those from suppliers and external vendors     	 	\n&bull; 	Research and explore different data sources, work with data and system experts to understand the data and what it represents.	 Perform data 	\ncleaning, pre	-processing, feature engineering and build relevant models and algorithms to conduct meaningful analysis	.   &bull;  	 	Overall 	\naccountability and end	-to-end delivery management for a set of technology related initiatives as defined by our business and portfolio 	\nframework.     	 	\n&bull; 	Work within a cross	-functional matrix team comprising data analyst, business users, data engineers etc., and guide the team in developing 	\nartificial intelligence and machine learning models to extract insights, from structured and unstructured data, that o	ptimize business outcomes.    	 	\n&bull; 	Coordinate and organize planning, design retrospective meetings with the teams during the agile development cycle.	      	\n&bull; 	Understand and synthesize latest trends and breakthroughs in technology; offerings solutions, integrating and implementing re	levant 	\ninnovations with clients. Discuss all new opportunities conversion offerings.	      	\n&bull; 	Manage the adoption, and operationalization of Cloud Platforms (Amazon Web Services (AWS) during Move2Cloud project, apply De	vOps 	\n(CI	-CD Pipeline), Automation CI/CI.\n\n&bull; 	High	-tech SaaS product management experience, including taking products from concept to market	      	\n&bull; 	Business requirements definition and business process design for the digitization of operational processes	      	\n&bull; 	Manage the team&rsquo;s productivity to achieve the set KPIs and service levels	      	\nIBM India Pvt Ltd (Collabera	- Sr Program 	 	\nManager)  	    	\n                                       	Jan 2018 	&ndash; Jun 2020	     	\n   	  Responsibilities: 	-            	      	\n&bull; 	Provide Solutions to bridge the gap between business and technology with expertise in managing complex programs and multiple 	concurrent 	\nprojects.     	 	\n&bull; 	Solve business problems and provide tangible results for enterprise	-level systems and legacy workflow systems.     	 	\n&bull; 	Coordinate and organize planning, design retrospective meetings with the teams during the agile development cycle.     	 	\n&bull; 	Implemented Agile methodologies with SaaS application development projects and tool use like JIRA     	 	\n&bull; 	Executed end to end total 3 Digital Transformation projects using RPA, AI	-ML and DevOps Technology for Vodafone client.     	 	\n&bull; 	Develop transformation road maps describing evolution of enterprise solution portfolios from as is state to future digital st	ate.     	 	\n&bull; 	Coordinate sprints, retrospective meetings, and daily stand	-ups. Coach team members in SRUM 	- Agile frameworks.    &bull;  	 	Work closely 	\nwith Program Management Office, Delivery Organizations to align to transformation roadmaps and delivery plans.     	 	\n   	\n   	Responsibilities: 	-      	\n&bull; 	Understanding and synthesizing the latest trends and breakthroughs in emerging technologies; offerings solutions, integrating	 and 	\nimplementing relevant API driven Open Banking, Innovations with CITI Bank. Providing all new opportunities conversion offerin	gs.     	 	\n&bull; 	Architected the API driven financial ecosystems Open Banking, Banking as a Service, PSD2 compliance, Fintech and delivered th	e digital 	\ncapabilities for the CITI Bank.     	 	\n&bull; 	Implementing infrastructure support and management in Tibco (Middleware) grails development &amp; integration projects.     	 	\n&bull; 	Manage the adoption, and operationalization of Cloud Platforms (Amazon Web Services (AWS), apply DevOps (CI	-CD Pipeline).	      	\n&bull; 	Experience in Payment System &amp; Card	- Mobile Wallet, Credit Card, Payment Gateway, SWIFT.     	 	\n&bull; 	Project management, design, requirements definition and specification, budgeting, and project control with ability to support	 multiple 	\nsimultaneous projects.     	 	\n      \nSYNECHRON Tech Pvt td 	&ndash; Sr Associate SW 	     	Nov 2009 	&ndash; Mar 2011 	     	\nResponsibilities: 	     	\n&bull; 	Deployment and Maintenance using Tibco Administration. Used Tibco Administrator to upload the created Deployment packages 	&amp; deplo	y  	\nit..     	 	\n&bull; 	Deployment, Administration &amp; Support of for multiple applications across DEV/QA/Prod environment.     	 	\n&bull; 	Assist with implementation, upgrades application migrations &amp; support of applications in all environments.     	 	\n&bull; 	Identification and resolution of application/environment related outages/problems or escalate to vendor.     	 	\n&bull; 	Monitoring and setting up environmental on multiple platforms across the enterprise.     	 	\n      \nEATON Pvt. Ltd., Noida 	&ndash; IT Analyst  	    	    	   	May 2007 	&ndash; Nov 2009 	     	\n&bull; 	Defect Management through REMEDY/ Quality Centre tickets. Requirements Analysis and all Support Activities. Preparation of  d	esign 	\ndocument.     	 	\n&bull; 	Installation of various basic Tibco components to add new server.     	 	\n&bull; 	Configuration and troubleshooting of environments.     	 	\n&bull; 	Involved in Unit and Integration testing, bug fixing and acceptance testing.     	 	\n&bull; 	Involved in Production Support &amp; Enhancement.	      	\nMOKSH Consultancy (ZENSAR Technologies) 	&ndash; SW 	 	\nEngineer 	     	\n    	\nApril 2006 	&ndash; May 2007 	     	\n&bull; 	Design the business process according to the business rule at TIBCO BW Designer.	      	\n&bull; 	Interaction with the client for the purpose of planning and reporting.	      	\n&bull; 	Interaction with the external parties involved for the purpose of Design, Unit Testing (Test Team) and coordination and issue	 resolution', 2, 0, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 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
(505, 117, 76, NULL, NULL, '76_117_53243829666b4bd1a6007b_PANKAJ_KUMAR_GUPTA-CV.pdf', 'PANKAJ KUMAR GUPTA-CV.pdf', 'PANKAJ KUMAR GUPTA	 	\nVice President | Gen AI CoE Lead	 	\npankaj.iitr30@gmail.com | +919552131400 | Pune &ndash; 411027 |  http://www.linkedin.com/in/pankaj-gupta-71931315	 	\nSummary	 	\nExperienced professional with 18 years of experience, specializing in Generative AI, Machine Learning, Deep Learning, Java, \nECM,  and  BPM.  Expert  in  creating  AI  solutions,  robust  Java  applications,  and  optimizing  processes  with  ECM  and  BPM. \nStrong analytical, problem-solving, and project management skills, committed to delivering impactful business results. \nSkills	 	\nProgramming Languages:	 Java, Python	       	Database:	 Oracle, MS SQL, DB2	 	\nMachine Learning:	 Scikit-Learn   	        	Deep Learning Frameworks:	 TensorFlow, Keras 	\nBusiness process management:	 IBM BPM 7.5 / 8.x 	    	Content Management:	 IBM FileNet P8 4.x / 5.x	 	\nCase Management:	 IBM Case Manager 5.x	 , IBM BAW	   	Cloud:	 AWS	 	\n \nSoft Skills	 	\nAgile Methodologies	   	Leadership	   	Stakeholder Management	   	Collaboration	   	\nClient communication	   	Problem Solving	   	Adaptability	 	\n  \nExperience  	 	\nAxis Bank	                     	      Mumbai, MH	 	\nVice President | AWS Kendra, Microsoft Azure Open AI	     	             	   	             Jul 2023 &ndash; Present	 	\n&bull; 	Delivered a Gen AI-powered resume screening system that increased revenue by 12 crore through optimizing recruitment \nprocesses and identifying top talent with 40% greater efficiency. 	\n&bull; 	Collaborate  with  10  business  units  to  analyze  processes  and  identify  opportunities  for  implementing  Gen  AI  solutions, \nleading to improved operational efficiency. 	\n&bull; 	Propose  and  assess  technical  strategies  to  seamlessly  integrate  Gen  AI  into  business  operations,  aligning  with \norganizational objectives. 	\n&bull; 	Led  comprehensive  evaluations  of  vendor  solutions,  meticulously  assessing  capabilities,  scalability,  and  alignment  with \norganizational objectives. 	\n&bull; 	Successfully  deployed  a  Gen  AI-based  Chatbot  for  Retail  Business  Operations,  leading  to  10%  increase  in  workforce \nproductivity by automating tasks and facilitating information access. \n 	\nPrompt Personnel - Intellective	                  	            Pune, MH 	 	\nTechnical Architect | Java, Spring boot, Python, Scikit-Learn, IBM BAW, IBM FileNet	   	         Nov 2018 &ndash; Jul 2023	 	\n&bull; 	Developed a machine learning algorithm utilizing supervised learning techniques to predict risk in property and casualty \ninsurance during corporate customer onboarding.	 	\n&bull; 	Designed and implemented a technical architecture for an underwriting portal aimed at corporate customers&#039; property and \ncasualty insurance, focusing on streamlining risk identification processes through comprehensive requirement gathering, \nsolution design, and documentation.	 	\n&bull; 	Designed and successfully executed three additional projects for the UK based insurance client, including Global Market \nUnderwriting, EMEA Finance, and APAC Finance.	 	\n&bull; 	Responded  RFIs  and  RFPs  for  BPM,  ECM,  RPA,  and  Unity,  secured  $1.5M  in  new  contracts  by  showcasing  tailored \ntechnological solutions	 	\n&bull; 	Contributed to securing a multimillion-dollar deal with a leading insurance company in the USA by delivering technical \npresentations and addressing client inquiries effectively.\n\nDatamatics Global Services Ltd	                         Mumbai, MH 	\nTechnical Architect | RPA, OCR, IBM BPM, IBM BAW	                    	Jan 2016 &ndash; Oct 2018	 	\n&bull; 	Established  and  led  the  Robotic  Process Automation  (RPA)  Center  of  Excellence  (CoE)  from  inception  to  operation, \nensuring alignment with organizational goals and objectives. 	\n&bull; 	Successfully delivered 6 RPA projects for top-tier clients in the banking and insurance sectors. 	\n&bull; 	Collaborated with cross-functional teams including sales, technical, and legal departments to gather information and craft \ncomprehensive responses tailored to client requirements. 	\n&bull; 	Played  a  key  role  in  securing two  crore  rupees  deal  with  one  of  India&#039;s  top  private  banks  by  conceptualizing  a  proof  of \nconcept (POC) within a short timeframe. 	\n&bull; 	Designed a Loan Against Property application that makes it easy to introduce similar products on the same platform without \nneeding major changes. 	\n&bull; 	Assumed  responsibility  for  a  project  at  risk  of  closure  by  the  client,  and  with  thorough  negotiations  with  client  and \nteamwork, effectively delivered and completed the project within timeline. 	\n \nIBM India Pvt. Ltd	                                 Pune, MH 	\nAdvisory System Analyst | Java, IBM FileNet	                                       	Oct 2015 &ndash; Jan 2016	 	\n&bull; 	Provide technical training to teams when required and serve as a technical mentor to team members  	\n&bull; 	Architecting and designing software solutions for various problem types. 	\n \nTieto Software Pvt Ltd	                                 Pune, MH 	\nLead Software Architect | Java, IBM Case Manager, IBM BAW	                 	Sep 2010 &ndash; Oct 2015	 	\n&bull; 	Analyzed user needs and software requirements to determine the feasibility of design within time and cost constraints. 	\n&bull; 	Led multiple projects from POC to production deployments, delivering scalable and modular software products. 	\nIBM India Pvt. Ltd 	                              Pune, MH 	\nSenior System Engineer | Java, BPF, IBM FileNet	                     	Jul 2007 to Sep 2010	 	\n&bull; 	Developed tools and applications, providing innovative solutions to complex business problems. 	\n&bull; 	Planned, developed, and implemented large-scale projects  from conception to completion,  focusing on performance and \nscalability improvements. 	\n \nDatamatics Global Services Ltd	                         Mumbai, MH  	\nAssociate Consultant | Java, IBM FileNet	                         	Jan 2006 &ndash; Jul 2007	 	\n&bull; 	Troubleshot and resolved issues in existing software, coding and testing based on software specifications and design. 	\n&bull; 	Wrote  and  maintained  technical  documentation  to  describe  program  development,  logic,  coding,  testing,  changes,  and \ncorrection.  	\n \nKey Projects   \nAxis Bank \nHR Resume Screener	 | Microsoft Azure Open AI | Solution Architect 	\n&bull; 	Collaborate with stakeholders to gather and analyze system requirements, translating them into actionable technical \nspecifications. 	\n&bull; 	Work closely with HR stakeholders to understand integration requirements and address any compatibility or \ninteroperability issues. 	\n&bull; 	Provide regular updates and progress reports to project sponsors and key stakeholders, addressing any concerns or issues \nproactively. 	\n&bull; 	Direct the development and implementation phases of the project, coordinating tasks and ensuring strict adherence to \nproject timelines and quality standards for optimal project outcomes\n\nADI (Gen AI based chatbot)	 | AWS Kendra, Microsoft Azure Open AI | Solution Architect 	\n&bull; 	Designed the architecture for the Generation AI based chatbot, incorporating AI and natural language processing (NLP) \ntechnologies to enable intelligent conversational interactions.  	\n&bull; 	Conducted proof-of-concept (POC) tests and technical assessments to validate technology choices and identify potential \nintegration challenges. &bull; Implemented robust security measures to protect user data and ensure compliance with privacy \nregulations. 	\n&bull; 	Collaborated with cross-functional teams, including product managers, developers, UX designers, and business \nstakeholders, to align technical solutions with business objectives. 	\n \nPrompt Personnel &ndash; Intellective \nRisk Assessment for Property and Casualty Insurance	 | Machine Learning, Python, Scikit-Learn | Technical architect 	\n 	Developed a machine learning algorithm utilizing supervised learning techniques such as classification and regression to \npredict risk in property and casualty insurance during customer onboarding. 	\n 	Utilized historical data to train the model, ensuring robustness and accuracy in risk assessment. 	\n 	Collaborated closely with domain experts to discern the significance of each feature, ensuring that relevant features were \nselected for model implementation based on their importance in the insurance domain. 	\n 	Documented the development process, including methodologies and results, for stakeholders and regulatory compliance. 	\nWorkView	 | IBM BAW, ExtJS, Java, Spring Boot | Technical Architect 	\n&bull; 	Led project planning activities in collaboration with the process owner to establish process goals and project success \ncriteria, clarify process scope and the relative value of process activities, and define the work plan. 	\n&bull; 	Ensured project completion within allocated budget and timelines. 	\n&bull; 	Designed the application architecture. 	\n&bull; 	Conducted requirement gathering and analysis 	\nEducation \nM.Sc. (Applied Mathematics) from IIT Roorkee, Roorkee - 2005', 2, 0, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 0),
(506, 117, 76, NULL, NULL, '76_117_166731796766b4bd1a602ce_Pawan_Pohani_Sr_Lead_Data_Scientist_Sr_Architect.pdf', 'Pawan Pohani_Sr Lead Data Scientist_Sr Architect.pdf', '1 | P a g e 	 	\nPHONE:	+9195459	 89457	 www.linkedin.com/in/pawan	-pohani 	EMAIL:	 pawan	.pohani	@gmail.com	 	\n     	  	 Pawan	 Pohani	  	\nSr.	 Lead Data Scientist	/Sr. Architect	 	 \n 	\n 	A  multifaceted  Certified 	Technical  Thought  Data  Analytics  Leader	,  carrying  rich 	\nexperience  of 	17+  Years	,  with  a  demonstrated	 ability  in  mining  insightful  thought 	\nleadership,  strategic  problem  solving,  consulting,	 gauging  the  business  requirements 	\nand objec	tives, and be able to transform them into	 use cases as	 projects/business	 pitch	. 	\n 	7+	 Years&rsquo;	 hands	-on	 experience	 in	 designing	 data	 driven	 solutions,	 leading	 E2E	 Data	 	\nScience/Analytics projects, on prem as well as on cloud, 	and building data solutions	 	\nin collaboration,	 with	 different	 stakeholders	 which	 includes,	 but	 not	 limited	 to,	 Product	 	\nTeam,	 Pre	-sales	 team	 and	 Risk	 Management	 Team.	 	\n 	10+	 Years&rsquo;	 experience	 in	 leading	 and	 managing	 multiple	 engineering	 teams	 as	 	\nSolution	 Architect	 across	 Waterfall	 &amp; Agile	 Methodology	 and	 various	 technical	 stacks.	 	\n \n 	\n 	Leadership	 &amp; Strategy	 	\n 	Project	 Management	 	\n 	Banking	 &amp; Finance	 Domain	 	\n 	Cards	 &amp; Payment	 Products	 	\n 	Generative AI/LLMs	 	\n 	Predictive	 Analysis	 	\n 	Collection Analytics	 	\n 	Waterfall	 &amp; Agile Methodologies	 	\n 	Cognitive Solution	 	\n 	Machine	 Learning	 	\n 	Artificial	 Neural	 Network	 	\n 	Model	 Deployment	 	\n 	Azure	/Databricks	 	\n 	Deep	 Learning	 	\n 	Big	 Data	 Analytics	 	\n 	Risk	 &amp; Fraud	 Analytics	 	\n 	\n 	 	Machine	 Learning	 Techniques	 &ndash; Linear	 Regression,	 Logistic	 Regression, SVM,	 	\nNa&iuml;ve	-Bayes, Decision Tree, KNN, Ensemble 	Techniques, PCA, Forecasting, K	 	\nMeans	 Cluster	 and	 Apriori.	 	\n 	NLP	, LLM, Generative AI, 	Deep	 Learning	 &amp; 	Azure 	AI Services	. 	\n 	Azure Services 	&ndash; ADF, Databricks, AML, Synapse, Azure AI Services &amp; 	\nADLS.	 	\n 	\n 	Advance	 Program	 in Data Science	&rsquo; by	 Indian	 Institute	 of Management,	 Calcutta	 	\n 	Bachelor of Engineering 	by R.G.P.V. University	 in &lsquo;	Information Technology	&rsquo; 	\nbranch.	 	\n \n \n \n 	\nOf	 Note	 	\nExperience	 Summary	 	\nQualifications/Core	 Competencies	 	\nEducational	 Background\n\n2 | P a g e 	 	\n  	Professional	 Work	 Experience	 	 	\nLTI	Mindtree	                                                                                      	Oct/2021	 - Till	 Date	 	\nAs 	Sr. 	Lead Data Scientist	, provide a technical, consulting and domain	 leadership	 to a team	 	\nof Business	 Analysts	, Data Modelling, Data Engineers	 and	 Data	 Scientists	 with	 an	 aim	 of	 	\nproviding analytical	 solution, to a BFSI client, across various Line of Business. My Roles 	\nand	 Responsibilities	 include	 - 	\n Coordinating	 with	 different	 stakeholders	 to identify	 the	 opportunities	 for	 Data	 	\nScience/Analytics which	 can	 drive	 relevant	 insights	 for	 Business.	 	\n Brainstorm	 with	 stakeholders	 to derive	 the	 &lsquo;Value	 Realization&rsquo;	/&rsquo;ROI&rsquo;	 	\nfrom	 Data Science use cases	. 	\n Lead the team on requirement gathering, data understanding, defining scope,	 	\nbuilding,	 and	 implementing	 solutions	. 	\n Leverage	 different	 Data	 Science	 (Machine	 Learning,	 Deep	 Learning	, NLP	, 	\nGenAI &amp; LLM	) &amp; Azure&rsquo;s	 AI	 capabilities to	 build	 the	 solution	/POCs	.  	\n Work with Data Engineering, Data Modelling, Cloud Admin and Power BI team \nto design an end	-to-end solution	, which includes, but not limited to, facilitating 	\ndata in form of DataMart at cloud and designing PowerBI Dashboards	. 	\nSnapshots	 of Projects	 handled	 - 	\n Voice Analytics 	- This use case aims to build an 	Azure Cognitive Solution	 on 	\nUnstructured Data to generat	e pre	-defined KPI on English language calls taken place 	\nbetween Relationship Manager (RM) &amp; Customer. With this Business can keep \nclose tab on quality of calls from RMs&#039; perspective as well as gauge the pulse of \ncustomer in terms of products and competitor	s mentioned by Customer.	 	\n Transaction Classification	 &ndash; Leveraging 	LLM (	BERT	) &amp; FastText library	, t	his use 	\ncase aims 	to categorize	 transactions originating from different sources (NEFT &amp; 	\nRTGS) so that Business can gain insights which will subsequently	 help in decision 	\nmaking process.	 	\n Image Processing	 - This use case aims to 	find discrepancies in images of 	\nCommercial setup uploaded by Relationship Managers. It leverages the 	LLMs of 	\nAzure AI Service	 along with supervised ML techniques.	 	\n Customer Segmentat	ion 	- This use case aims to do Retail Customer Segmentation 	\non different data points, so that Business can have granular details before pitching \nproducts to customer.	 	\n \n   Attra	 Infotech	 	May/2019	 - Oct/2021	 	\nAs a 	Lead Data Scientist/Architect, have been 	responsible for end	-to	-end Project 	\nManagement and for Developing a roadmap to tech development in consultation with our \nclient teams suggesting solutions to challenges using AI and ML. Roles &amp; Responsibilities \nincluded	 	\n Lead a team of data scientists &amp; data	 engineers for multiple products/applications. 	 	\n Collaborating with different stakeholders to understand problem statements and \nproviding data driven solutions. 	 	\n Lead team on all aspects of Data Mining &amp; Model building. These aspects include, but \nnot limite	d to, preparation of Use Cases/POCs (Proof of Concept), Requirement 	\nGathering, Data Acquisition, Data Cleaning, EDA, Data Transformation, Data \nModelling, Data Visualization, Statistical Reporting, Deployment and Model evaluation \nin production.	 	\nSnapshot	 of AI/ML Projects/POCs	 work	ed:	 -\n\n3 | P a g e 	 	\n Transactions Fraud Prediction Model	: - A 	Classification predictive model 	was	 	\nprepared	 to predict	 frauds	 in Banking	 transactions	 (Debit	 Card	 &amp; Credit	 Card).	 	\nChatbot: 	- Presented	 a POC	 of Chatbot,	 using	 IBM	 Watson, at	 Issuing	 &amp; Acquiring	 	\nInterface for	 B2B	 Communication. This	 Chatbot	 aimed	 to answer	 queries, give	 status	 	\nof Production	 Incidents	 and	 Batches to	 Bank/Financial	 Institute	 representatives.	 	\n Campaign Strategy	: -Historical data shows a healthy conversion rate of Retail	 	\nCustomers into Credit Card customers. To boost 	the campaign	 strategy of 	the 	\nMarketing	 Team,	 a Predictive	 Model	 was	 prepared	 to predict	 potential	 Credit	 Card	 	\ncustomers.	 	\n Product	 Incident	 Analysis	: -Developed	 a model	 to bifurcate	 Production	 Incidents	 	\ninto	 logical	 groups.	 Group	 Names	 are	 provided	 with	 Logical	 Description	 in synch	 	\nwith	 the	 respective	 cluster.	 	\n 	Data Cleaning, K Means Clustering 	and 	NLP techniques 	were used along with	 	\nPython	 3 as programming	 language.	 	\n Card &amp; Payment Data Analysis	: - Client 	provided a data of Indian Banks&rsquo; ATM,	 	\nPOS,	 Credit	 Cards	 and	 Debit	 Cards,	 with	 an	 objective	 to analyze	 the	 data	 and	 fine	 	\npatterns.	 	\n 	Data	 Engineering,	 Data	 Cleaning	 and	 EDA	 were	 used as	 framework with	 Python	 3 	\nas Programming Language, along with Python 	Libraries 	- Seaborn &amp; Matplotlib 	- 	\nused	 for	 Data	 Visualization.	 	\n Ageing	 Categorization	 of	 Production Incidents	: - 	\n 	All	 Production	 Incidents	 were	 mapped	 either	 to L1	 Team	 or	 L2	 team.	 System	 didn&rsquo;t	 	\nhave	 intelligence to	 bifurcate	 ageing of	 Incidents	 with	 respect	 to L1	 &amp; L2	 team.	 	\n 	An	 Automated	 process,	 based	 on	 Python,	 was	 developed to	 give	 Ageing	 	\nCategorization	 along	 with	 SLA	 and	 Data	 Visualization information	 through	 Tableau.	 	\n Loan EMI Defaulter Prediction 	- This 	use case	 aimed to do Predictive Analysis to	 	\nfind	 the	 Loan	 EMI	 Defaulters. The	 prediction	 helped	 Risk	 Management	 to strategize	 	\nbetter.	 	\n 	Multilayer Perceptron/Artificial Neural Network, Data Cleaning and EDA 	were	 	\nused	 as framework	 with	 Python	 3 as programming	 language.	 	\n \nWipro	 	Feb/2015	 &ndash;May/2019	 	\n 	\nAs	 Data Scientist/Architect	, had	 been	 responsible	 for driving	 the	 project	 end	 to end.	 Roles	 &amp; 	\nResponsibilities	 include:	 - 	\n E2E Solution Designing of digital and data driven 	projects, which includes close	 	\ncollaboration	 with	 different	 business and	 tech	 teams.	 	\n Working	 closely	 with	 Business	 &amp; tech	 teams	 to define	 a streamlines	 roadmap	 for	 	\ndigital	 and	 data	 driven	 projects.	 	\n Served	 an	 onsite	 tenure	 of 6 months	 to ensure	 Data	 Analytics	 project	 gets a	 smooth	 	\nstart.	 	\nSnapshot	 of projects handled:	 - 	\n Risk Strategy Model 	&ndash; Based on historical data, a Classification Model was	 	\ndeveloped	 to predict	 which	 all	 Active	 Accounts	 (Debit	 Cards	 as well	 as	 Credit	 Card)	 	\ncan	 be	 delinquent	 and	 move	 to Collection	 Module. This	 prediction	 was	 be	 used as	 an	 	\ninput	 by	 the 	Risk	 Management	 Team	 for	 strategizing.	 	\n 	Classification	 Algorithm,	 SMOTE,	 Data	 Cleaning	 and	 EDA	 were	 used	 as 	\nframeworks	 with	 Python	 3 as programming	 language.	 	\n Cloud Transformation of Legacy Applications	: - With an objective of &lsquo;Application	 	\nModernization&rsquo; 	Capital One has decided to migrate Cards Historical Vision Plus tape\n\n4 | P a g e 	 	\ndata from 	Legacy System (Mainframe) to Cloud (AWS) 	in encrypted form and create	 	\na Data	 Lake.	 	\n 	Coordinated	 with	 Architecture,	 Client,	 and	 different	 teams	 (spanned	 across	 various	 	\ntechnologies	 - Mainframe,	 JAVA, Unix, Python	 &amp; AWS)	 to finalize	 the	 design.	 	\n 	Project&rsquo;s	 scope	 includes	 &ndash; Development	 of tools	 required	 for migration,	 infrastructure	 	\nsetup and support at Mainframe as well as at AWS, consumption of data at cloud,	 	\nautomation of	 processes (using DevOps), and continuous rationalization of data to be	 	\nmigrated.	 	\n 	With	 application	 of Data	 Analytics,	 &ldquo;data	 to be	 migrated&rdquo;	 was	 reduced	 by	 30%,	 	\nwhich	 had	 a huge	 impact	 of project	 plan	 (specially	 estimation	 of time	 and	 cost).	 	\n 	\nHSBC	 GLT	 	Nov/2006	 - Feb/2015	 	\n 	\n As	 a Project	 Lead/Onsite	 Coordinator	 for	 HSBC	 Cards	 &amp; Payment	 Portfolio, was	 	\nresponsible for analysis, estimation, planning, reporting, development, supporting	 	\nSIT/UAT	 and	 supporting	 implementation.	 	\n 	Worked	 in Vision	 Plus	 Product,	 predominantly	 in CMS	 (Card	 Management	 Service)	 	\n&amp; CTA	 (Collection	 Tracking &amp;	 Analysis)	 modules,	 across	 Development	 &amp; 	\nProduction	 Support	 team.	 	\n 	Worked on different functionalities, such as 	Payment Application, Payment	 	\nHierarchy, Payment Processing, Fees 	Processing, Interest Processing and	 	\nCollection	 Strategies.	 	\n 	Worked as 	&quot;Onsite Coordinator&quot; 	for close to 14 Months across different locations	 	\ni.e.,	 USA	 &amp; Brazil	. 	\n 	\n  	Certification	 &amp;	 Training	 	 	\n 	PMP	: Project	 Management	 Professional	 Certification, 2016		\n Databricks	 Accredited Generative AI Fundamentals, 2023	 	\n 	Information Technology Infrastructure Library (ITIL) 	Foundation	 ', 2, 0, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 0),
(507, 117, 76, NULL, NULL, '76_117_154330002966b4bd1a60703_PradeepTyagi-Resume.pdf', 'PradeepTyagi-Resume.pdf', 'P ra d eep	\nT ya gi	\n( P yth o n	\nF u ll	\nS ta ck	\nD eve lo per)	\nE m ail:	\np ra d eep ty a gi2 3@ gm ail. c o m	\nG it H ub:	\nP ra d eep	\nT ya gi	\n|	\nG it H ub	\nl in ke d IN :	\nP ra d eep	\nT ya gi	\n|	\nL in ke d In	\nA bo ut	\nm e	\nW it h	\n1 5	\ny e ars	\no f	\nI T	\ni n dustr y	\ne xp erie n ce ,	\ni n clu din g	\no ve r	\n1 0	\ny e ars	\no f	\ni n te rn atio nal	\ne xp o su re	\ni n	\nS in ga p o re ,	\nI\na m	\na	\ns e aso ned	\ns o ft w are	\nd eve lo per	\nw it h	\nf u ll- s ta ck	\nd eve lo pm en t	\ne xp ertis e .	\nI\nh ave	\nl e d	\nt e am s	\na s	\na	\nt e ch nic a l	\nl e ad	\na n d	\nr e ce n tly	\nd eve lo ped	\na n	\nA I	\nc h atb o t	\nu sin g	\nR A G	\nc o nce p ts .	\nM y	\nb acke n d	\ns k ills	\ni n clu de	\nP yth o n,	\nF a stA PI,	\nN ode.js ,	\na n d	\nU nix	\ns h ell	\ns c rip tin g,	\nw hile	\nm y	\nf r o nte n d	\ns k ills	\ne n co m pass	\nR eact.js ,	\nH TM L,	\nJ a va Scrip t,	\nC SS,	\na n d	\nB oots tra p .	\nI\na m	\np ro fic ie n t	\nw it h	\nd ata b ase s	\ns u ch	\na s	\nE la stic se arc h ,	\nM yS Q L,	\nM SSQ L,	\na n d	\nP o stg re SQ L,	\na n d	\na d ep t	\nw it h	\nD evO ps	\nt o ols	\nl ik e	\nO pen Sh if t ,	\nA rg o C D ,	\nD ocke r,	\nG it ,	\nC V S,	\na n d	\nJ ir a .	\nT e ch nic a l	\nC om pete n ce s	\nA I	\nT e ch no lo gie s(R ece n t	\nE xp erie n ce )	\nA pplic a tio ns\nL a n gch ain\nC re ate d	\na	\nc h atb o t	\nu sin g	\np yth o n	\nl a n gch ain	\nt o	\nd eve lo p	\nR A G	\nA pplic a tio ns\nC hro m aD B,	\nF A IS S	\nT o	\nc re ate	\nv e cto r	\ne m bed din gs	\nf o r	\nt h e	\nR A G	\na p plic a tio ns	\nO pen A I	\n,\nH uggin gFa ce ,	\nO lla m a	\nT o	\ng e t	\na ccu ra te	\nr e su lt s	\nb ase d	\no n	\ne m bed din gs	\nf r o m	\nR A G .	\nS tr e am lit\nT o	\ni m ple m en t	\nC hatB ot&rsquo;s	\nu se r	\ni n te rfa ce	\nt h at	\ni s	\nu se r	\nf r ie n dly	\na n d	\ne ff ic ie n t\nC om pete n ce\nL e ve l\nR em ark s\nP yth o n\nA dva n ce\nA dva n ce	\nl e ve l	\np ro fic ie n cy	\ni n to	\np yth o n	\np ro gra m min g.	\nU sa ge	\nr a n ge s	\nf r o m	\nw rit in g	\ns c rip ts ,	\nt o	\nd eve lo pin g	\nb acke n d	\nA PI	\ns e rv e rs .	\nF la sk /F a stA PI\nA dva n ce\nD eve lo ped	\nb acke n d	\nA PI	\ns e rv e rs	\nf o r	\np ro vid in g	\nc o nfig	\ns e arc h	\nc a p ab ilit ie s	\nf o r	\no ve r	\n6 k	\nn etw ork	\nd evic e s.D eve lo ped	\na sy n c	\nb ase d	\nb acke n d	\nA PI	\ns e rv e rs	\nf o r	\np ro vid in g	\nR eal	\nT im e	\nc a p ab ilit ie s	\nt o	\ng e t	\nd ata ce n te r	\ns it e	\nd ata	\nw it h in	\ns e co nds.	\nE la stic se arc h\nP ro fic ie n t\nI m ple m en te d	\nM id dle w are	\nu sin g	\nE la stic se arc h	\nt o	\ns e rv e	\nd yn am ic	\nw eb page s	\nc a te rin g	\nf o r	\nr e al	\nt im e	\nd ata	\nu pdate s.	\nA nd	\nq uic k	\nv ie w s	\no ve r	\nt h e	\nd ata ce n te r	\ns it e	\nd ata .\nR D BM S\nP ro fic ie n t\nI n te ra ct	\nw it h	\nR D BM S	\nv ia	\nA PI	\ns e rv e rs ,	\ns c rip ts	\nt o	\ng e n era te	\nd ata	\nr e ad y	\nt o	\nb e	\nc o nsu m ed	\nb y	\nt h e	\nf r o nte n ds.	\nR eactJS /N odeJS\nP ro fic ie n t\nT o	\nd eve lo p	\na sy n c	\nb ase d	\nb acke n d	\nA PIs	\nv e rs io n1	\nt h at	\nw as	\nl a te r	\nr e w rit t e n	\ni n to	\nF a stA PI. D eve lo ped	\nS in gle	\np age\n\na p plic a tio ns	\nf o r	\nq uic k	\nD O M	\nu pdate s	\nb ase d	\no n	\nt h e	\nd ata	\nu pdate s	\na t	\nt h e	\nd ata ce n te r	\ns it e s.	\nD ocke r\nP ro fic ie n t\nU se d	\nf o r	\nt ra n sit io nin g	\nf r o m	\nm ono lit h	\nt o	\nm ic ro se rv ic e s	\na rc h it e ctu re .\nK u bern ete s/O pen sh if t /\nA rg o C D\nP ro fic ie n t\nU se d	\na s	\na n	\no rc h estra tio n	\np la tfo rm	\nf o r	\nm an agin g	\nc o nta in ers	\nf o r	\nt h e	\nm ic ro se rv ic e s.	\nA rg o C D	\ni s	\nu se d	\nt o	\na u to	\nr e co ncile	\nt h e	\nc o nta in er	\nu pdate s	\ni n to	\no pen sh if t	\nc lu ste rs\nA W S	\nL a m bda	\nI n te rm ed ia te\nD ep lo ye d	\nA W S	\nl a m bda	\nf u nctio n	\nt o	\nt r ig ge r	\no n	\ns e rv e r	\ne ve n ts	\na n d	\nc re ate	\nt ic ke ts	\ni n to	\ns e rv ic e	\nn ow .	\nH TM L/C SS/Ja va sc rip t\nP ro fic ie n t\nU se d	\nV an illa	\nj a va sc rip t	\nw it h	\nt ra d it io nal	\nw eb	\nt e ch no lo gie s	\nt o	\nd eve lo p	\ni n ho use	\nI n fr a str u ctu re	\nR eq uest	\nP o rta l	\n\nP ro fe ssio nal	\nE xp erie n ce s	\nF u ll	\nS ta ck	\nD eve lo per	\na t	\nL u m en	\nT e ch no lo gie s,	\nS in ga p o re ,	\n(\nM arc h	\n2 016	\nt o	\nJ u ne	\n2 024)	\nT e ch no lo gie s/ P la tfo rm s	\nP yth o n	\n, F A ST	\nA PI	\n, O pen A I,	\nL a n gch ain ,	\nV ecto rD B,	\np yte st,	\nn o dejs	\n, r e actJS ,	\nw eb so cke ts ,	\nE la stic se arc h ,	\nR ed is ,	\nD ocke r,K u bern ete s/o pen sh if t	\nR esp o nsib ilit ie s	\n●	\nI m ple m en t	\ni n nova tiv e	\ns o lu tio ns	\na s	\nv a lu e	\na d ded	\ns e rv ic e s	\nf o r	\no rg a n iz a tio ns	\nw it h in	\nt h e	\nc o m pan y,w it h	\nr e ce n t	\ne xp erie n ce	\no f	\np ro to ty p in g	\nc h atb o t	\ns o lu tio ns.	\n●	\nD eve lo p	\ne n d	\nt o	\ne n d	\ns o lu tio ns	\nt o	\nm an age	\nd ata ce n te rs	\no w ned	\nb y	\nt h e	\nc o m pan y	\n●	\nG ath er	\nr e q uir e m en ts	\nf r o m	\no th er	\ns ta ke h o ld ers	\nt o	\nc re ate	\na	\nh ig h	\nl e ve l	\nd esig n	\no f	\nt h e	\nr e q uir e m en t	\n●	\nT ra n sla te	\nr e q uir e m en ts	\nt o	\nl o w	\nl e ve l	\nd esig n s	\n●	\nM en to r	\nj u nio r	\nt e am	\nm em bers	\ni n	\ns u cce ssfu lly	\ni m ple m en tin g	\nt h e	\nr e q uir e m en ts .	\n●	\nI m ple m en t	\na u to m ate d	\nt e sts	\nt h at	\na re	\ne xe cu te d	\na s	\np art	\no f	\nC I/ C D	\np ip elin es.	\n●	\nM ain ta in	\nd ep lo ym en ts	\no ve r	\no pen sh if t	\nf o r	\nn ew	\na n d	\ne xis tin g	\na p plic a tio ns.	\nC o ntr ib utio ns/A cco m plis h m en ts	\n●	\nI m ple m en te d	\nc h atb o t	\ni n te gra tin g	\nR A G	\nc o nce p ts	\nt o	\nh elp	\ns u ppo rt	\nt e am s	\nn avig a te	\nc o m ple x	\nt e ch nic a l	\nd o cu m en ts	\na n d	\np ro vid e	\ne ff ic ie n t	\n1 st	\nl e ve l	\no f	\ns u ppo rt	\n●	\nI m ple m en te d	\na n	\ne n d	\nt o	\ne n d	\ns o lu tio n	\nt o	\ne n ab le	\nu se rs	\nt o	\ns e arc h	\na cro ss	\nm ore	\nt h an	\n6 000	\nS D W AN	\nA pplia n ce s	\nv ia	\na	\np o rta l	\nr a n gin g	\nf r o m	\nk e yw ord	\ns e arc h	\nt o	\nc o nfig u ra tio n	\ns e arc h es.	\n●	\nD eve lo ped	\na p plic a tio n	\nf o r	\np ro vis io nin g	\nl e ga cy	\nc u sto m ers	\nt o	\nn ew	\nS o ft w are	\nd efin ed	\nn etw ork s	\np ow ere d	\nb y	\nC is c o	\n( C is c o	\nA CI) .	\nA ddin g	\nr e al	\nt im e	\nu pdate s	\nc a p ab ilit y	\nt o	\ns y n c	\nd ata	\nb etw een	\ni n ho use	\np o rta ls	\nw it h	\nC is c o	\nA CI	\nc o ntro lle rs ,	\nr e d ucin g	\nl o ad	\nt im e	\nf r o m	\n2	\nm in ute s	\nt o	\n7	\ns e co nds	\np er	\nr e q uest.	\n●	\nI m ple m en te d	\nu nit	\nt e sts	\nf o r	\ne ve n t	\na u to m atio n	\nw ork flo w s	\nu sin g	\nP yTe st	\n●	\nI m ple m en te d	\na	\nb acke n d	\nA PI	\nu sin g	\nF a stA PI	\nt o	\ns tre am	\nb ack	\nr e alt im e	\no utp ut	\no f	\nc o m man ds	\nt h at	\ne xe cu te	\na s	\np art	\no f	\nn etw ork	\na u to m atio n	\n●	\nI m ple m en te d	\ni n ho use	\nI n fr a str u ctu re	\nP o rta l	\nh elp in g	\nt e am s	\nt o	\nr e co rd	\nt a sk s	\na n d	\na ssig n	\nt a sk s	\nt o	\no th er	\ns ta ke h o ld ers\n\nS e n io r	\nP yth o n	\nD eve lo per	\na t	\nN TT	\nC o m munic a tio ns,	\nS in ga p o re ,	\n( D ece m ber	\n2 013	\nt o	\nM arc h	\n2 016)	\nT e ch no lo gie s/ P la tfo rm s	\nP yth o n	\n,\nM yS Q L	\n,\nn o SQ L	\n( M ongo D B),	\nS h ell	\nS crip tin g	\n,\nP e rl,	\nO P5	\n( N agio s),lin ux\nR esp o nsib ilit ie s	\n●	\nD eve lo p	\na n d	\nm ain ta in	\nb acke n d	\nc o m po nen ts	\no f	\na	\nm an age d	\ns e cu rit y	\ns e rv ic e s	\np la tfo rm .	\n●	\nM eet	\nw it h	\nc u sto m ers	\nt o	\ng a th er	\nf u nctio nal	\nr e q uir e m en ts	\na n d	\nt ra n sla te	\nt h o se	\ni n to	\nt e ch nic a l	\nr e q uir e m en ts	\n●	\nL e ad	\nt e am	\no f	\ns o ft w are	\nd eve lo pers	\nt o	\ni m ple m en t	\nt e ch nic a l	\nr e q uir e m en ts .	\n●	\nD eve lo p	\nP O C	\nt o	\np ro po se	\nn ew	\ns o lu tio ns	\nt o	\nt h e	\nc u sto m ers .	\nC o ntr ib utio ns/A cco m plis h m en ts	\n●	\nD eve lo p	\na p plic a tio ns	\ni n sta lle d	\no n	\nC PE	\nd evic e s	\nt o	\nh elp	\nc u sto m ers	\np ro vis io n	\nt o	\nt h e	\nm an age d	\ns e cu rit y	\ns e rv ic e s	\np la tfo rm	\nw it h o ut	\nt h e	\nn eed	\no f	\nh avin g	\np ublic	\nI P .	\n●	\nD eve lo p	\nU tilit y	\nt o	\nb ack u p	\np o lic y	\ns e cu rit y	\np o lic ie s	\nf r o m	\nf ir e w all	\nd evic e s	\nf r o m	\nd if fe re n t	\nv e n do rs	\n.	\n●	\nB acke n d	\na p plic a tio n	\nd eve lo pm en t	\nt o	\ns u ppo rt	\nt ic ke tin g	\nf o r	\nt h e	\nm an age d	\ns e cu rit y	\ns e rv ic e s	\np la tfo rm .	\n●	\nD eve lo p	\np lu gin	\ns c rip ts	\no n	\nO P5	\nf o r	\ne n han cin g	\nt h e	\np ro duct	\nc o m po nen t	\nm onit o rin g	\nA sso cia te	\nP ro duct	\nD eve lo per	\na t	\nB M C	\nS o ft w are ,	\nP u ne,I n dia	\n( A ugu st	\n2 011	\nt o	\nD ece m ber	\n2 013)	\nT e ch no lo gie s/ P la tfo rm s	\nP yth o n	\n,\nS h ell	\nS crip tin g	\n,\nT P L,	\nl in ux	\nt o	\nd eve lo p	\np att e rn	\ns c rip ts	\nf o r	\nB M C	\nA D DM	\nP ro duct	\nf o r	\nd is c o ve rin g	\ns o ft w are	\nv e rs io ns	\no n	\nc u sto m er	\ns it e .	\nR esp o nsib ilit ie s	\n●	\nD eve lo p	\ni n ho use	\np att e rn s	\nt o	\nc o ntr ib ute	\nt o	\ns o ft w are	\nd is c o ve ry	\na s	\np art	\no f	\nB M C	\nA D DM	\np ro duct	\n●	\nC ontr ib ute	\nt o	\nt e st	\nh arn ess	\nf o r	\nr u nnin g	\na u to m ate d	\nt e sts	\nC o ntr ib utio ns/A cco m plis h m en ts	\n●	\nI m ple m en te d	\nm odule s	\nw it h in	\nt h e	\nB M C	\nA D DM	\nP ro duct	\nt o	\nd is c o ve r	\ns o ft w are s	\no n	\nC usto m er	\np re m is e s.	\n●	\nI m pro ve d	\nt e st	\nc o ve ra ge	\nb y	\na d din g	\nn ew	\nt e sts	\nt o	\nt h e	\nt e st	\nh arn ess	\no f	\nt h e	\np ro duct	\nS o ft w are	\nE n gin eer	\na t	\nN it y a O bje ct	\nS o ft w are	\nS o lu tio ns,	\nP u ne,	\nI n dia .	\n( M arc h	\n2 009-M ay	\n2 010)	\nT e ch no lo gie s/ P la tfo rm s	\nP e rl	\n,\nS h ell	\nS crip tin g	\n,\nl in ux	\nt o	\nd eve lo p	\ni n sta ll	\ns c rip ts	\nf o r	\nt h e	\np ro duct	\nR esp o nsib ilit e s	\n●	\nM ain ta in	\ni n sta ll	\ns c rip t	\nf o r	\nt h e	\np ro duct	\nC o ntr ib utio ns/A cco m plis h m en ts	\n●	\nI m ple m en t	\nb unch	\no f	\ns c rip ts	\nt o	\ns u ppo rt	\ni n sta ll	\nb acke n d	\nc o m po nen t	\no f	\nt h e	\np ro duct.	\nE d uca tio n	\nM aste rs	\ni n	\nC om pute r	\nS cie n ce	\n( P u ne	\nU niv e rs it y )	\n2 006	\n&ndash;	\n2 008	\nB ach elo rs	\ni n	\nC om pute r	\nS cie n ce	\n( P u ne	\nU niv e rs it y )	\n2 003	\n-\n2 006', 2, 0, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 0),
(508, 117, 76, NULL, NULL, '76_117_64742223366b4bd1a608ad_Rahul_Kanojiya_Resume.docx', 'Rahul_Kanojiya_Resume.docx', '\r\nRahul KanojiyaSpecialist 2 | Solutions ArchitectPune, India+91 6264030729 | Kanojiya85@gmail.com | LinkedIn\r\nProfessional Summary\r\nHighly skilled and TOGAF Certified Solutions Architect with over 17 years of expertise in system design, development, analysis, and implementation, specializing in Microsoft technologies for enterprise applications. Recognized for leading large-scale enterprise architecture transformation programs, with a significant focus on the banking sector. Certified in TOGAF, LeanIX, and Microsoft Azure, with hands-on experience in AWS and GCP. Adept at creating complex, integrated solutions that align with organizational goals and maximize client value. Proficient in cloud architecture assessment, strategic transformation, risk management, and stakeholder collaboration. Committed to continuous learning and staying abreast of industry trends and best practices.\r\n\r\nCore Competencies\r\nEnterprise Architecture Transformation: Extensive experience in leading end-to-end enterprise architecture transformation programs, leveraging TOGAF principles and frameworks.\r\nCloud Architecture and Strategy: Deep expertise in cloud architecture assessment, transformation, and strategy development, with a focus on Microsoft Azure.\r\nStakeholder Management: Strong ability to collaborate with stakeholders, ensuring alignment of solutions with business objectives and driving consensus across diverse teams.\r\nRisk Management and Compliance: Proficient in identifying, managing risks, and ensuring compliance in cloud transformation projects, adhering to industry standards and regulations.\r\nContinuous Learning: Committed to staying updated with industry trends, emerging technologies, and best practices to maintain a competitive edge.\r\nTechnical Proficiency\r\nCloud Platforms: Microsoft Azure, AWS, GCP\r\nAzure Services: IaaS, PaaS, SaaS, Azure Functions, Logic Apps, Azure SQL, Service Bus, Azure Storage Account, Web Apps, ARM Templates, Azure Active Directory, App Service, REST API, Microservices, Containers, Kubernetes, Docker, Databricks\r\nProgramming Languages: C#.NET, Web API, ASP.NET, JavaScript\r\nCI/CD Tools: Azure DevOps\r\nDatabase Management: SQL Server, Cosmos DB\r\nAgile Practices: Test-Driven Development, Agile Development, SAFe 5\r\n\r\nProfessional Experience\r\nSpecialist 2 | Solutions ArchitectAlfa Laval, Pune, IndiaAugust 2022 - Present\r\nLed the design and implementation of cloud solutions on Azure, improving scalability and reducing operational costs by 30%.\r\nDeveloped enterprise architecture frameworks aligning with TOGAF standards.\r\nCollaborated with cross-functional teams to translate business requirements into technical solutions. \r\nCollaborated with various departments to ensure IT solutions met diverse business needs.\r\nSpearheaded the integration of various ERP systems.\r\nEstablished governance models and IT standards to ensure consistency, compliance, and security across the organization.\r\nIdentified and executed cost-saving opportunities through optimized IT operations and resource management.\r\nProvided training and mentorship to IT staff, fostering a culture of continuous improvement and innovation.\r\nFacilitated change management processes to ensure smooth adoption of new systems and technologies.\r\nTech Lead | System AnalystCognizant Technology SolutionsPune, India (2006-2013, 2018-August 2022) | Charlotte, NC (2013-2014) | Pittsburgh, PA (2015-2018)\r\nLed the successful migration of BizTalk applications to Azure, optimizing performance, scalability, and cost-efficiency by 30%.\r\nDeveloped Logic Apps and Azure Functions for EDI file processing and  improving data accuracy and operational efficiency by 40%..\r\nActed as Tech Lead, responsible for implementing approved technologies that align with technical architecture, business plans, and long-term strategy.\r\nMentored staff to develop software systems development capabilities and led a team of 8 developers.\r\nServed as onsite coordinator and single point of contact between customer and Cognizant team.\r\nCreated requirement and design documents for application development.\r\nManaged all phases of the project lifecycle from requirements through design, coding, testing, and maintenance.\r\nSupervised a team of 5-8 offshore developers for enhancement and application support.\r\nServed as SME and technical liaison between IT developers and business partners.\r\n\r\nCertifications\r\nTOGAF&reg; Enterprise Architecture Practitioner\r\nLeanIX Certified Practitioner (Level 1 and 2)\r\nAZ-305 Designing Microsoft Azure Infrastructure Solutions\r\nAZ-204 Developing Solutions for Microsoft Azure\r\nAZ-900 Microsoft Azure Fundamentals\r\nOCI 2023 Certified Foundations Associate\r\nOCI 2023 Multicloud Architect Certified Associate\r\n', 2, 0, 1, 'Recruiter', NULL, 'N', 14, 0, NULL, NULL, 0, NULL, NULL, '2024-08-08 12:42:02', 0);
