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(310, 73, 1, NULL, NULL, '1_73_1769384504662635a49705c_Varun_Marothia_-_Director_Digital_Commerce_-_1_9.pdf', 'Varun Marothia - Director Digital Commerce - 1.9.pdf', 'EXECUTIVE	 SUMMARY	 	EXPERTISE	 	\neCommerce 	&amp; digital marketing	 	\nDigital Transformation Consulting 	 	\nPre	-Sales Solutioning	 	\nProduct Management	 	\nProgram 	Management	 	\nAround 1	8+ years of global IT industry experience in delivering digital product innovations 	\n&amp; enterprise	-level	 eCommerce transformations 	for fortune 500 clients	 across 	geographies	. 	\nA  thought  leader 	&amp; 	established 	digital 	consulting 	partner	 for 	clients 	across  digital 	\ncommerce 	&amp; marketing 	value chains 	in B2C, B2B, and D2C landscape	.  	\n  \nVerticurl	 India	 (Nov	 202	2 &ndash; Till Date)	  	\n&bull; 	Commerce  c	onsulting 	practice 	head	- Leading  overall 	eCommerce 	consulting 	\npractice	 with 	20+  resources	. Strategy  &amp;  optimization  consulting  for  technology 	\nagnostic  landscape  across	- retail,  manufacturing,  Pharma,  CPG  &amp;  BFSI  vertical. 	\nManaging 	annual 	revenue  targets 	of  $8  Mn	. Maturity  assessments, 	Consulting 	\ndelivery, p	ipeline building, sales GTM 	connect &amp; conducting webinars.	    	\n&bull; 	eCommerce  Strategy	 	Consulting	: 	Leading 	end	-to-end  digital  commerce 	\ntransformation 	consulting	 across 	value 	chains	 centered  around 	functional,  data, 	\ncustomer experience 	(CX) 	and	 technology 	landscape	. Leading strategic initiatives &amp; 	\nroadmap strategy for CMO 	organizations for content &amp; commerce market activation 	\nacross multi	-brand, multi	-geography landscapes	  	\n&bull; 	Optimization  Consulting	 &ndash; outside	-in assessments 	&amp;  strategy  roadmap 	across 	\nbusiness  imperatives.	 Market  assessment,  competitive  analysis,	 identify  sector 	\nspecific	 marketing  trends  and  growth  opportunities  across  multiple  capabilities	- 	\nomnichannel, social commerce, live commerce, hyper personalization	, etc.	,  	\n&bull; 	Driving presales solutions	- Providing solutions across	- Adobe Commerce (Magento), 	\nSAP  Hybris,  Commerce  tools	,  Shopify	 for  RFP  responses.  Leading  a	ccelerator 	\ndevelopment 	track 	and building partnerships with eCommerce product vendors. 	 	\n&bull; 	Developed 	frameworks 	&amp;  assets 	for  eCommerce  landscape 	maturity  assessment	, 	\nomnichannel	 maturity  assessment,	 platform  evaluation, 	KPI  benchmarking, 	\npersonalization maturity assessment, 	etc. 	  	\n&bull; 	Experience 	in 	managing 	enterprise	-level	 implement	ation  of	 Adobe  commerce 	\n(Magento 2.0)	- Cloud/ 	on	-premises	 solutions	 for multi	-brand, multi	-geography	. 	\n&bull; 	Extensive experience in product 	management	 across 	in multiple domains	 with Agile 	\nways of working	 and managing it	&rsquo;s PnL	 	\n&bull; 	Thought  leadership	 &ndash; driving  CMO  charters  for  practice  growth  and  market 	\nactivation.  Publishing  white  papers,  managing  capability  decks  &amp;  conducting \nwebinars. 	 	\n&bull; 	Partnership 	Management	 &ndash; managing  partnerships  with 	Shopify  Plus, 	Commerce 	\ntools, 	VTex	 to establish 	Verticurl	 as 	a service partner and define joint 	GTM	 strategy	 	\n \n \n \n 	\n 	VARUN MAROTHIA	 	\nDirector	- CX &amp; 	Digital Commerce	 	\n2004 	- 2006	 	\nMASTER OF 	BUSINESS 	\nADMINISTRATION	  	\nICFAI Business School, Hyderabad	 	\nCGPA: 8.22	 	\n \n1999 	- 2003	 	\nBACHELOR OF ENGINEERING 	(Chemical)	  	\nPanjab Engg. College, Chandigarh	 	\nCGPA: 70.2% (Honors)	 	\n 	\n 	\n 	\n \nPLATFORMS/ PRODUCTS	 	\nOVERVIEW	 	\nEDUCATION	 	\nOmnichannel Transformation \nStrategy	 	\nOmnichannel benefits for \ncustomers &amp; business	 	\n 	\nPUBLICATIONS	 	\nAdobe Commerce \n(Magento)	 	\nShopify	 	\nSAP Hybris Cloud	 	\nAdobe Target	 	\nVarun.marothia@gmail.com	       	     	     	+91 9910091820	 	\nhttps:	 //www.linkedin.com/in/varun	-marothia	-3410996/	 	\nC-245	, Pocket	-7, Kendriya Vihar	-2, Sector	-82, Noida, UP\n\nVerticurl (An Ogilvy division)	- (Nov&rsquo; 22	- Till Date	) 	\nDirector	- CX &amp; Digital Commerce	 	 	 	 	 	 	 	\n \nResponsibilities	 	\n&bull; 	Commerce practice growth in India region	 across three metro cities	- Mumbai, Delhi	 and 	Bangalore	.  	\n&bull; 	Closely working 	with Ogilvy Experience team in 	India	 to cross sell digital capabilities in addition to media ca	pabilities	 	\n&bull; 	Set up consulting framework 	for maturity assessment	s and optimization assessments. 	Capacity to be positione	d at 	\na price point 	of $200 K	 per account in 	D2C/ B2B 	space.	 	\n&bull; 	Managing team of eCommerce consultants and business development 	 	\n&bull; 	Focus on deep	-tech techn	ologies in Generative AI and Digital Humans 	space.	 	\n&bull; 	Focus on building acceler	ators 	using generative AI 	technology.	 	\n&bull; 	Strategies ideation for large D2C brands for helping in increasing online revenue share	.  	\nKey achievements	 	\n&bull; 	Successfully 	established	 consulting frameworks at price point of $200K.	 Account conversion 	&ndash; 2 in Q4	&rsquo;22 &ndash; Q1	&rsquo;22	 	\n&bull; 	Practice building from 	lean team to a 	mid	-size	 team.	 	\n \nWipro Ltd. (April 2021 	&ndash; Nov&rsquo; 22	) 	\nDigital Commerce 	&ndash; Consulting Practice Head	 	 	 	 	 	 	April 2021 	&ndash; Till Date	 	\n \nResponsibilities	 	\n&bull; 	Responsible for 	establishing myself as 	a business 	partner	 to strategic clients in 	the 	eCommerce space, with 	a 	\nfocus  on  aligning  their  vision  &amp;  roadmap  with  Wipro&rsquo;s  service  offerings  and 	helping	 a client  in  identifying  new 	\ncapabilities areas to invest	 in. Create opportunities in eCommerce consulting, implementation, support areas.	 	\n&bull; 	As a consulting practice head with	in 	eCommerce practice	, I act in capacity of 	a thought leader to identify areas of 	\nopportunity with the latest industry	-aligned trends, publishing articles, building new capabilities within practice.	 	\n&bull; 	Instrumental  role  in  building  consulting  practice  within 	BU  from  bottom  to  top  and  converting  the  incremental 	\nrevenue opportunities	 	\n&bull; 	Expertise  in 	Adobe  Commerce	 (Magento),  Commerce  Tools,  SAP  Commerce  (Hybris)	 space  for  providing 	\nsolutions to proposals, bid 	defense	. 	\n&bull; 	As a part of pre	-sales responsibilities, owning and managing end to end 	solutions	 for eCommerce implementation, 	\nmigration, upgrade and Customization proposals. Managing client presentations and bid 	defense	 	\n&bull; 	Owning  complete  service  line  of 	commerce  optimizat	ion	 &ndash; This  focuses  on  customer  experience,  AB  testing/ 	\nmulti	-variate testing, developing capabilities in Adobe Target, Google Optimize for personalization. 	 	\n&bull; 	Leading accelerator development in 	the 	eCommerce landscape by focusing on new trends in 	the 	market 	 	\nKey achievements	 	\n&bull; 	Successfully 	led enterprise level	 discovery workshops for 	4 clients 	in 	a span of 	7 months 	and proposed 	1-3 years 	\nCAREER TIMELINE	 	\nWORK EXPERIENCE	 	\nSep&rsquo; 19 	&ndash; Mar&rsquo; 21	 	\nApr	&rsquo; 0	6- Se	p&rsquo; 	19	 	Apr&rsquo; 21 	&ndash; Nov&rsquo; 22	 	\nNov&rsquo; 22 	&ndash; Till Date\n\nroadmap	. 	\n&bull; 	Helped in establishing 	a high	-level	 capability 	roadmap	 for 	the 	business to plan and implement. 	 	\n&bull; 	Optimization	 assessments with 4 existing clients for focusing on incremental revenue. Generated revenue pipeline 	\nof avg $ 200 K 	- $ 300 K value per 	assessment	.   	\n&bull; 	Managing large scale RFP&rsquo;s for providing 	solu	tions	 in 	the 	Adobe Commerce space	 across industries, new avenues	. 	\n 	\nDigital 	Commerce 	Strategy Consulting for 	B2B	 	 	 	 	 	 	Sept	 20	21	 &ndash; Nov 	2021	 	\n \nDetails	- The 	client	 is 	a  global  leader  in  enterprise  IT  had  a  mandate  to  accelerate  sales  among  SMB  &amp;  B2B businesses 	\nalong  with  increasing  customers&rsquo;  lifetime  value  through  their 	eCommerce	 portal.  Initiated  4  weeks 	of 	experience  led 	a 	\nconsulting workshop for 	the 	complete 	eCommer	ce	 landscape. 	 	\nRole 	&ndash; Program Transformation Head	 	\nTech Stack: 	SAP Hybris, Mirakl Marketplace, Adobe AEM	. 	\nResponsibilities	- 	\n&bull; 	Responsible for delivering complete program transformation of 	the 	existing eCommerce landscape	 	\n&bull; 	Established  as  business  partner 	post  completion  of  innovation 	consulting	-led	 assessment  (Value  realization 	\nassessment	- framework developed by myself)	 	\n&bull; 	Led	 end  to  end  CX  assessment,  eCommerce 	functional 	assessment,  Digital  analytics  assessment  and  Platform 	\nmaturity assessment	 	\n&bull; 	Managed 	discovery phase	, define	d AS IS digital capability framework for gap assessment and 	To Be 	ideation.	 	\n&bull; 	Defined short term &amp; long	-term 	roadmap strategy	 	\nOutcome	- 	\n&bull; 	17	 value chains evaluated across 	4 business imperatives	 	\n&bull; 	Score based maturity assessment	 	\n&bull; 	85+	 gaps identified across value chains	- functional/ technical	 	\n&bull; 	65+	 Ideas/ solution generated across 	45	 capability area. 	 	\n&bull; 	5 - Key strategic initiatives identification	 	\n&bull; 	2-phased strategic roadmap mapped to	 capability value matrix 	 	\n \neCommerce	- Optimization Strategy Consulting	 	 	 	 	 	 	Aug 2021 	&ndash; Sept 2021	 	\n \nDetails	- Multi	-country	, D2C commerce platform was facing challenges in providing great customer experience and were 	\nnot able to increase their average order value. High cart 	abandonment	 &amp; high dropouts at checkout. A detailed consulting 	\ndriven assessment (experience led) was co	nducted by Wipro proactively to provide an 	outside	-in view to 	the 	client	. 	\nRole 	&ndash; Program Transformation Head	 	\nTech Stack: 	SAP 	Commerce Cloud (CCV 2)	, Adobe AEM, Miro Board	 	\nResponsibilities	- 	\n&bull; 	Responsible for delivering optimization strategy to 	the 	client for their eCommerce landscape	 	\n&bull; 	Detailed assessment &amp; recommendation report, Roadmap strategy (Short/ Long term)	 	\n&bull; 	Led	 CX assessment	, eCommerce assessment	, Digital analytics assessment	 and 	Platform maturity assessment	 	\n&bull; 	Value	-based backlog	 	\n&bull; 	Defined short term &amp; long	-term 	roadmap strategy	 	\nOutcome	- 	\n&bull; 	Lower  conversion  rates  at 	1.29%,	 much  lower  than  competitors  at 	3%.	 Identified  potential  gaps  &amp;  recommended 	\nideas/	solutions	 to improve the gap. 	 	\n&bull; 	Higher checkouts drop rate at 60%, assessed the potential cause and re	-defined solution journey to achieve target 	\nreduction by 	20%.	 	\n&bull; 	Higher  bounce  rate  at 	72%.	 Recommended  landing	 page  strategy,  SWO  optimization  strategy  &amp;  Home  page 	\npersonalization strategy to improve.	 	\n&bull; 	Devised strategy to improve avg order value by increasing checkouts as 	logged	-in users	 by 	2%	 of vs guest users 	\n(current guest user checkouts were at 98%)	 	\n \nNagarro Pv	t Ltd. (Sept 2019 	&ndash; March 2021	) 	\nDigital Commerce Implementation 	&ndash; Large Retail Enterprise, EMEA	  	 	 	Jul 2020 	&ndash; March 2021\n\nProject Details	- Nagarro helped a	 large retail giant in 	the 	EMEA region in 	the 	rapid transformation of their digital 	\ncommerce landscape during COVID season. Due to 	the 	urgency of business digitization, 	Nagarro performed 	due 	\ndiligence in 	a span of just 3 weeks to take up the new implementation roadmap. 	 	\nRole 	&ndash; Principal consultant	 (Ad	obe Commerce 2.	4.2	) 	\n \nResponsibilities	- 	\n&bull; 	Perform due diligence for existing commerce digital landscape across 	the 	value chain ( Awareness, 	\nConsideration, Conversion, Retention &amp; Advocacy) and user journey	 	\n&bull; 	Define digital product roadmap strategy for 	Next	-Gen	 transformation &amp; upgrade to 	the 	latest platform	 	\n&bull; 	Functional consultant/ Product Owner for multi	-brands/ multi	-geography upgrade at program level	 	\n&bull; 	Manage functional integration/ headless architecture with CMS, PIM, Pricing System, Salesforce, SAP, etc.	 	\n&bull; 	Manage	 releases as per business priorities 	 	\n&bull; 	Manage proposals, SOW for multiple new opportunities	 	\n \neBusiness Digital Strategy Consulting for US, EMEA Clients	  	 	 	 	Dec 2019 	&ndash; June 2020	 	\n \nDetails	- As a part of digital transformation, I provide consulting services in the domain of Retail/ 	eCommerce	 space for 	a 	\nlarge enterprise in 	the 	US, EMEA, APAC regions. They need our services to perform discovery of current business 	\nlandscape and propose digital 	roadmap strategy. 	 	\nRole 	&ndash; Principal consultant	 	\n \nResponsibilities	- 	\n&bull; 	Conduct discovery phase &amp; perform AS IS assessment of enterprise for commerce domain.	 	\n&bull; 	Define AS IS digital capability framework for gap assessment and solution ideation.	 	\n&bull; 	Define client&rsquo;s TO B	E business roadmap and strategy	- define 	multi	-geography	/ brands strategy, best fit product 	\nassessment, B2B/ B2C commerce, integrations recommendation.	 	\n&bull; 	Define 	omnichannel	 strategy for commerce implementation across various channels	 	\n&bull; 	Prepare RFI, 	involved	 in 	the 	vendor selection proces	s 	\n \n \nHCL Technologies (April 2006 	&ndash; Sept 2019)	 	 	 	 	 	 	 	 	\nIoT based Mobile App for VRF Industrial AC&rsquo;s/ Residential AC&rsquo;s	 	 	 	March 2019 	&ndash; Aug 2019	 	\n(Leading Air conditioning company, Japan)	 	\n \nProject Details	-  	\nAn embedded IOT project for JCH, Japan within &ldquo;Industrial Engineering 	&ndash; HVAC Domain&rdquo;. It involved developing an IOT 	\nmobile application for their 	Residential 	air	-conditioners at 	a global level. The project involved 	IoT	 Mobile App using Azure 	\nDevOps and Cloud platform, Hardware 	Wi	-Fi Pairing with mobile app and ability to control full operations of AC units. 	 	\n \nRole 	&ndash; Senior Product Owner	 	\n \nResponsibilities	- 	\n&bull; 	Product 	AS	-IS Assessment to manage communication between hardware and remote app. 	 	\n&bull; 	Usability Study 	&ndash; Stakeholder Interviews, Affinity mapping, Technology Trends assessment.	 	\n&bull; 	Product Owner 	&ndash; Agile based Product backlog management, Develop &amp; Prioritize user stories, Using	 Design 	\nThinking approach &amp; DCO derived app requirements, User story creations, Manage acceptance criteria&rsquo;s. 	 	\n&bull; 	Product Manager 	- Managed 	region	-specific	 program backlog at global level, created product roadmap, 	\ninvolvement in defining strategy for User eng	agement, product release management, managed user engagement 	\nmetrics, involvement in 	the 	go	-to-market plan, Product Launch 	- strategic planning to Tactical activities,	 	\n&bull; 	Release Management 	&ndash; Managing overall releases to market, product version management, pl	an for usability 	\ntesting, weekly status reporting to management.	 	\n&bull; 	Resource Management 	&ndash; Manage 	a team of product owners (Approx. 5) and mentor them 	 	\n \nKey Achievement&rsquo;s	- 	\n&bull; 	Successfully managed program backlog for 5 scrum teams along with feature priority	 	\n&bull; 	Defin	ed SAAS based revenue model.', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-04-22 10:02:12', 0),
(325, 74, 63, 29, NULL, '63_74_17842023046627648ccc73c_Abhra_Deblaskar.docx', 'Abhra Deblaskar.docx', '﻿Abhra Deblaskar\r\nPh: +91 9435514644  , 9113869569                                                                                                                  \r\nEmail: abhradeblaskar@gmail.com\r\nAddress: Flat no.110 (Block-2),                                                                                        \r\nELIL Abode Apartments,\r\nVenkateshwara Layout, Mahadevapura,\r\nBangalore, Pincode-560048\r\nSummary\r\nManagement Graduate with a total of over 11 years of diversified experience in Engineering and Data science domain. Career experience ranging from Industrial Project Management to Data Science including Statistical modeling and Model evaluation, experienced in Finance domain as well in FMCG/Retail domain.\r\nSkill Highlights\r\n&bull;Project Management\r\n&bull;Stakeholder Management\r\n&bull;Business Analytics\r\n&bull;Data Science\r\n&bull;Statistical Modeling\r\n&bull;Machine Learning\r\n&bull;Natural Language Processing\r\nProfessional Experiences\r\nLoonyCorn QuantMedia Pvt. Ltd. (July 2020-till date)\r\nDesignation: Data Science Analyst\r\nRoles and Responsibilities:\r\n&bull;Extracted and collected macro-economic indicators such as interest rates, bond yields , Liquidity data, volatility indices from Financial data sources using APIs and then creating visualizations to identify trends.\r\n&bull;Conducted exploratory data analysis to identify patterns and trends in data related to macro-economic indicators.\r\n&bull;Created Visualizations for displaying financial KPIs and correlation heatmaps in order to make informed decisions for effective risk management by ensuring portfolio diversification.\r\n&bull;Developed Machine learning models for Volatility prediction for maintaining consistent level of risk exposure.\r\n&bull;Developed Machine learning models for Anomaly detection on indicators related to F&amp;amp;O stocks.\r\n&bull;Conducted time series analysis on indicators related to indices, stocks , ETFs.\r\n&bull;Analyzed open interest and volume at different strike prices for taking positions related to trading.\r\n&bull;Built Sentiment analysis Models on financial news and social media using Natural language processing tools.\r\n&bull;Collaborated with trading team  to conduct stock specific analysis\r\nViaprom Technologies Pvt. Ltd. (July 2018-Sep 2018)\r\nDesignation: Business Analyst \r\nRoles and Responsibilities:\r\n&bull;Gathered requirements and important figures from clients.\r\n&bull;Built dashboards for better visualization of Business KPIs.\r\n&bull;Created customized reports for data visualization.\r\n&bull;Designed and developed data-driven exploratory analysis \r\nKantar IMRB (Mar 2017-July 2018)                                                                                                   [1 year 4 months]\r\nDesignation: Project Consultant \r\nRoles and Responsibilities:\r\n&bull;Gathered requirements and important figures from clients.\r\n&bull;Identified and interpreted client problems into actionable analysis.\r\n&bull;Managed Client objectives, expectations, and timelines.\r\n&bull;Managed and supported different stakeholders.\r\n&bull;Communicated changes to internal team members.\r\n&bull;Ensured insights and advanced analytical outputs are delivered through quality data sources.\r\n&bull;Worked with a team responsible for preprocessing of the data collected from the Market survey.\r\n&bull;Created customized reports for data visualization.\r\n&bull;Built statistical models for generating business insights based on the analysis of Consumer survey data using Statistical techniques and machine learning algorithms \r\n&bull;Evaluated Brand Potential through Proprietary tools.\r\nProject Portfolio/Client summary\r\nRetail Sales Data Analysis for Retail Client&ndash; India\r\nProject Description: The objective of the project was to analyze multi-dimensional retail sales data to uncover hidden trends and anomalies and develop a predictive model that helps business make proactive decisions. \r\nInvolvement Duration: ​2 months\r\nProject Role: ​Business Analyst\r\nResponsibilities:\r\n&bull;Exploratory data analysis\r\n&bull;Data Visualization\r\n&bull;Data Cleaning\r\n&bull;Statistical Modeling\r\nProject Team Size: ​3 members\r\nTools &amp;amp; Technologies:\r\n&bull;Time-series analysis\r\n&bull;Linear Regression\r\n&bull;Logistic Regression, SVM, Random Forest algorithms\r\n&bull;Python (pandas, matplotlib, seaborn)\r\n&bull;Power-BI for Data Visualization\r\nCustomer Segmentation for e-commerce Client &ndash; India\r\nProject Description: The objective of the project was to create customer segments among online consumers in order to reach them as per the interests of the profiles. \r\nInvolvement Duration: ​3 months\r\nProject Role: ​Consultant\r\nResponsibilities:\r\n&bull;Exploratory data analysis\r\n&bull;Data Visualization\r\n&bull;Data Cleaning\r\n&bull;Statistical Modeling\r\n&bull;Model Evaluation\r\nProject Team Size:​4 members\r\nTools &amp;amp; Technologies:\r\n&bull;K-means clustering algorithm\r\n&bull;Python (pandas, matplotlib, seaborn)\r\n&bull;Power-BI for Data Visualization\r\nDriving factors for food sample for FMCG Client &ndash; India\r\nProject Description: The objective of the project was to find out principal factors for driving likeability of the product among sample respondents. \r\nInvolvement Duration: ​2 months\r\nProject Role:​Consultant\r\nResponsibilities:\r\n&bull;Exploratory data analysis\r\n&bull;Data Visualization\r\n&bull;Data Cleaning\r\n&bull;Statistical Modeling\r\n&bull;Model Evaluation\r\nProject Team Size:​4 members\r\nTools &amp;amp; Technologies:\r\n&bull;Logistic Regression, Support Vector Machine, Random forest\r\n&bull;Python (pandas, sklearn )\r\n&bull;Power-BI for Data Visualization\r\nIndian Oil Tanking Engineering Project Pvt. Ltd. (July 2009- November 2014)                           [5 years 4 months]\r\nDesignation: Junior Manager\r\nRoles and Responsibilities:\r\n&bull;Managed Scheduling and monitoring of construction activities in Project Site.\r\n&bull;Worked on Supplier development, processing quotations, and also proper coordination with management for material procurement.\r\n&bull;Coordinated with vendors for cost negotiation and evaluation of Techno-commercial offers before finalization of Purchase Orders.\r\n&bull;Managed different stakeholders of the Projects.\r\n&bull;Managed resources i.e.  Manpower and Equipment, required to carry out Construction activities.\r\n&bull;Worked closely with Project Design team for any design specifications related issues, and B.O.Q estimation.\r\nEnercon India Limited (June 2007 &ndash; August 2008)                                                                          [1 year 2 months]\r\nDesignation: Graduate Engineer Trainee (Incoming Quality assurance)\r\nRoles and Responsibilities:\r\n&bull;Worked as a part of QA team doing Inspection &amp;amp; testing of power cables, electric motors, enameled copper wire as per IS, IEC and DIN standards.\r\n&bull;Handled the supplier quality improvement and commercial activities concerned with Electronics and electrical components for the Production Assembly Department.\r\n&bull;Worked on Identification and development of   dedicated and alternate vendor sources for achieving cost effective purchases of raw materials and reduction in delivery time.\r\nAcademics\r\nCourse\r\nInstitute &amp;amp; University\r\nYear of Passing\r\nCGPA/%\r\nPGDM EBIZ in Operations\r\nWelingkar Institute of Management Development and Research, Bangalore\r\n2017\r\n5.33/7\r\nB.Tech (Electrical Engg.)\r\nNational Institute of Technology, Silchar(Assam)\r\n2007\r\n6.42/10\r\nCertifications\r\n&bull;Certifications in Introduction to Deep Learning from Coursera (National Research University Higher school of Economics).\r\n&bull;Certifications in R programming ,Getting &amp;amp; Cleaning Data, Exploratory Data Analysis , Statistical Inference, Reproducible Research, Regression Models, Practical Machine learning, and Developing Data Products from Coursera (John Hopkins University).\r\n&bull;Certifications in SQL for Data Science and Data Wrangling, Analysis &amp;amp; AB Testing with SQL&nbsp;from Coursera (University of California, Davis).\r\nSoftware/Tools\r\n&bull;Python , SQL, OpenAI, Power-BI,  Azure AI,  Azure Machine Learning,  Azure Databricks\r\nI hereby state and acknowledge that the information provided is true and complete to the best of my knowledge and agree that any inaccurate and misleading information is solely my responsibility.\r\n(Signature)\r\n\r\n\r\n\r\n', 2, 2, 1, 'Recruiter', 'Assigned', 'SL', 1, 'N', 14, '2024-04-23 09:10:09', NULL, '2024-04-25 09:10:09', 0, NULL, '2024-04-23 07:34:36', 0),
(326, 74, 63, NULL, NULL, '63_74_10231661746627648cd26b7_RAMENCHETIA.docx', 'RAMENCHETIA.docx', '\r\nSenior data scientist\r\nRamen Chetia \r\nProfile Summary\r\n11 years of experience as IT professional with experience in ETL, Machine Learning, Deep Learning, Natural Language processing, Computer Vision and Campaign management\r\nTotal 6 years of relevant experience in Machine learning and deep learning.\r\nHaving good knowledge in Azure data factory, used it to extract the data from different sources and created one final dataset.\r\nInvolved in projects from data extraction, data manipulation, EDA, Model building and deployment.\r\nHelped stakeholders in decision making by providing insights from the data. Pre-processing, EDA and Feature engineering\r\nmethods are used to develop models.\r\nStrong hands-on experience with Python and Pyspark in applying Machine learning algorithms to prepare a model.\r\nHard working, highly motivated, and reliable individual with a constructive approach to the business, client and to other team members.\r\nGood experience in developing data pipelines in Azure Data Factory to extract the data from source and apply transformations in the extracted data and store it in Blob storage.\r\nExperience in predictive analytics, campaign management analytics and Fraud detection.\r\nExperience on the implementation and maintenance of ML model, regular Hyper-parameter tuning is applied.\r\nWell verse with Code version control systems like Git.\r\nWorked with MLFlow architecture and it components, building a training pipeline with MLFlow.\r\nExpertise on creating ML model with advanced algorithms like Random forest, XGBoost, LightGBM, OpenCV.\r\nExperience in end to end ML model solution design, from extraction till model deployment.\r\nTechnical Skills\r\nApplication ADF, Databricks, Snowflake, Databricks AutoML\r\nProgramming Languages Python, Pyspark, R\r\nIDE Databricks notebook, Jupyter Notebook, PyCharm\r\nDatabase My SQL, Oracle DB\r\nCVC, Container Git, Docker\r\nAlgorithms &amp;amp; Concepts Logistics regression, CART, Bagging, Boosting, NLP, CV\r\nTech in ML Regression, Classification analysis, NLP, CV, Recommender engine, Campaign management, CNN, 2D-LSTM, Tensorflow\r\nPROFESSIONAL EXPERIENCE\r\nMonth-Year Designation or Role/Company name Role Responsibilities\r\nMar 2022\r\n(Currently Working) Technical analyst (Data science)\r\n(Coforge Pvt Ltd) Worked for Voya Financial to implement ML solutions\r\nDay started with analysing the data and devising a solution to retrieve the hidden insights from data.\r\nBuild ML model, handling end to end process. Created pipeline to extract the data, work on the data, build a model and deploy the model in production\r\nenvironment.\r\nMigrating SPSS pipelines to python and Pyspark codes in Azure cloud and test it.\r\nHandled Fraud detection and Customer engagement capabilities, implemented ML solutions in different use-case\r\nNov 2019 -Mar 2022 Data Scientist (Capgemini Malaysia Bhd.) Worked for RHB bank and implemented ML solutions to replace the rule based legacy systems.\r\nDeveloping solutions for various departments where we have\r\nimplemented advance analytics and tried to find optimal solutions to boost the revenue growth.\r\nFrom machine learning to deep learning, developed predictive ML solutions for different use-cases.\r\nDiscussion with stakeholders to understand the rule based systems that are being used and finding solutions to replace it with smart ML model.\r\nWorked in advanced AI algorithms like Pytessaract to develop a model for OCR using OpenCV.\r\nWorked in end to end solution development, data extraction to model deployment.\r\nETL Developer Creating data pipelines to extract, transform and load data into data warehousing environment\r\nDesigned and maintained data pipelines and debugged if any issue arises\r\nWorked with different teams to deploy enhancement works.\r\nWorked on POC&rsquo;s to apply machine learning algorithms to different data\r\nGained knowledge on Data pre-processing, exploratory data analysis, extracting valuable insights from data.\r\nApplying Hyper-parameter tuning to re-train old models and update it.\r\nSep 2012&ndash; Oct 2017 (IBM India Pvt. ltd) Junior Data Scientist Dec 2017 &ndash; Nov 2019 (IBM India pvt. ltd) PROJECT EXPERIENCE\r\nProject name: Managed account adoption for Voya Financial\r\nDuration Feb , 2023, to Nov, 2023 Role Data Scientist\r\nProject Type ML solution to replace legacy system Technology ML, Python, Pyspark, Azure, Databricks, SQL\r\nMy\r\nResponsibilities Work with stakeholders to understand the work, devise some plan with client to apply ML solutions to it to make it smart and effective\r\nExtract data from different sources, massage the data and create a final dataset, save it in blob storage or create a table to store the data.\r\nImport the data to Databricks notebook and write python codes to pre-process, EDA and model development.\r\nUse MLFlow to create pipeline and by using Docker to deploy the model.\r\nAutomate and integrate the process by using ADF pipeline.\r\nWhile extracting the data, quality of the data are checked and verified. Source target mismatch, Invalid values, Null values, non-standard date formats are some of the examples of checks done.\r\nAfter completing the pre-process, analysis of data is done, if any hidden patterns are found then they are visualized with different graphs to share it with client.\r\nFeature selection is done with the help of business knowledge, ML algorithms. These features are extensively studied, new features are created with feature engineering if required.\r\nTableau is used to generate different graphs to analyse the pattern and distribution of data.\r\nDifferent ML algorithms are used to develop the model and compare the performance, cross validation and hyper-parameter tuning is used to improve the performance of the model.\r\nAfter multiple runs in production, the performance of the model is monitored and if any depletion of performance happen then re-training of the model is done.\r\nProject name: Cross sell of health benefit products\r\nDuration Mar 2022 to Dec 2023 Role Data Scientist\r\nProject Type ML solution to replace legacy system Technology ML, Python, Pyspark, Azure, Databricks, SPSS\r\nMy\r\nResponsibilities This is a migration project from SPSS to cloud.\r\nWhile extracting the data, the quality of the data are checked and verified. Source target mismatch, Invalid values, Null values, non-standard date formats are some of the examples of checks done.\r\nComparing the source of the SPSS pipeline and dataset made in ADF to extract the data.\r\nCreated ML model after completing the pre-processing and exploratory data analysis, this model mimics the SPSS model, but performance is enhanced in cloud.\r\nTableau is used to generate different graphs to analyse the pattern and distribution of data.\r\nAn Auto ML model is created in data bricks to compare the performances of the ML model, along with that parameter, features are also compared.\r\nName of the Project: - Money mule detection (Fraud detection)\r\nDuration Sep 2021&ndash; Feb 2022 Role Data Scientist\r\nProject Type Fraud detection Analytics Technology ML, Python, Pyspark, Azure, SAS, SQL\r\nMy\r\nResponsibilities This is a use-case for Anti money laundering department, money mules are the account holders of the bank which are being used to launder money. From the customer base, this use-case is to find the accounts which can be used as money mules.\r\nBy using ML solutions I have created a model to identify those money mule accounts which can be used to launder money.\r\nLegacy system is used to study the features being used in it, the different source systems are identified.\r\nWhile extracting the data, quality of the data are checked and verified. Source target mismatch, Invalid values, Null values, non-standard date formats are some of the examples of checks done.\r\nUsing SAS the required data is extracted and saved as blob storage files.\r\nAfter completing the pre-process, analysis of data is done, if any hidden pattern are found then they are visualized with different graphs to share it with client.\r\nFeature selection is done with the help of business knowledge, ML algorithms. These features are extensively studied, new features are created with feature engineering if required.\r\nPython Matplotlib and Seaborn libraries is used to generate different graphs to analyse the pattern and distribution of data.\r\nDifferent ML algorithms are used to develop the model and compare the performance, cross validation and hyper-parameter tuning is used to improve the performance of the model.\r\nAfter modelling the model is deployed using Docker, MLFlow\r\nName of the Project: -Credit card forms scan\r\nDuration Mar 2021&ndash; Aug 2021 Role Data Scientist\r\nProject Type Handwritten character recognition Technology ML, Python, OpenCV, Tensorflow, CNN, 2D-LSTM\r\nMy\r\nResponsibilities Project is for the department of GIA (Group Internal audit), task is to read and extract required information from scanned documents of credit card.\r\nSome of the fields such as DoB, application number which is present in the credit card application form need to be extracted and saved in a table.\r\nFor this task Numpy, OpenCV, Tensorflow is used to pre-process the images, making it ready for Pytesseract to read the image file.\r\nThe data that is being extracted by Pytesseract is then processed from regex to extract the required information.\r\nThis task is also tried using CNN and 2D-LSTM, the result of this task is compared with the Pytesseract results.\r\nAll the image pre-processing like image threshold, changing image angle to remove the noise that are.\r\npresent in the images, also Augmentation process is followed during training.\r\nNational Institute of Engineering, Mysore\r\nIIT - Kharagpur\r\nMCA\r\nBusiness Analytics and AI certification\r\nEDUCATION\r\nNational Institute of Engineering, Mysore\r\nIIT - Kharagpur\r\nMCA\r\nBusiness Analytics and AI certification\r\nEDUCATION\r\n\r\nDetailed IT Skills\r\nSkill Name Exp. in Years Skill Name Exp. in Years Skills Exp. in Years\r\nLanguages Languages Operating Systems\r\nService Now ITSM Python 5 windows 10\r\nService Now ITOM Pyspark 3 Unix 1\r\nService now ITIL R 1 Big Data Platform Cloud Development Digital\r\nPyspark 2 Azure 2 DataBricks 2 Tools/ Platforms S/w Configuration tools Hardware\r\nGit Hub 2 Azure Data Factory 2 --\r\nJenkins DataBricks AutoML 2 MLFlow 1 Testing Practice Domain\r\nBanking &amp;amp; Finance 7\r\nInsurance 2\r\nDatabases Retail 1\r\nOracle 6 SQL 6 ', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-04-23 07:34:36', 0),
(327, 74, 63, NULL, NULL, '63_74_13605921576627648cd362c_Sonu_Kumar.pdf', 'Sonu Kumar.pdf', 'Sonu Kumar	 	\n 	\nPython Expert, Machine \nLearning, AI, NLP, SQL 	\nServer	 	 9319263940	 	\nenggsonugupta01@gmail.com \nNew Delhi	 	 https://www.linkedin.com/in/s onu	-	\nkumar	-a587ab16b/	 	 \nSUMMARY	 	  \n4.7	 years  experienced  data  analytics 	\nprofessional  possessing  proven  track \nrecord  of  successfully  applying \neconometric  modelling,  algorithm \ndevelopment  &amp;  machine  learning \ntechniques  to  solve  key  business \nproblems.  Highly  skilled  in  applying \nadvanced  machine  le	arning/statistical 	\nalgorithms  such  as  Gradient  Boosted \nTrees,  Random  Forests,  Ensemble \nModels,  Clustering  etc.  to  real  world \nproblems  using  Python.  Looking \nforward  to  applying the acquired  gamut \nof skills to a challenging role in the data \nanalytics and mac	hine learning space.	 	\n \n           	KEY SKILLS	 	\n   Data &amp; Quantitative Analysis	 	\n \n  Data Science &bull; Big Data Analytics	 	 &bull; Predictive/Statistical Modelling	 	 &bull; Data Mining &bull; Data Visualization	 	 &bull; Machine Learning Algorithms	 	 	&bull; Business Intelligence &bull; Data \nWrangling &bull; 	Optimization	 	\n 	Techniques	 	\n 	\n&bull; Project Monitoring &amp; 	\nManagement	 	\n&bull; Coordination &amp; Liaison	 	 &bull; Client Relationship Management	 	 	&bull; Strategic Planning	 	\n \nTECHNICAL SKILLS	 	 	Tools	: Python, 	JIRA, 	PostgreSQL, 	\nAWS EC2, Azure, MongoDB, Spark, \nML, AI, Python,SQL, Numpy,	 	\nPandas, 	Seaborne,	 Matplotlib, Azure 	\nData Factory, Azure Datalake, Azure \nCodmosdb, Data bricks ,NLP, \nARIMA,TIme series Analysis,	 	 	\nPROFESSIONAL EXPERIENCE	 	  \nLead Consultant                                                       	Aug 2022 to Current	 	\nLearning Links 	Foundation	 	\n(Women in Data) Project	. 	\n 	Project Management: As a lead consultant, you&#039;ll be responsible for managing data \nanalysis projects from initiation to completion. This involves defining	 the project 	\nscope, setting timelines, allocating resources, and ensuring that the project meets \nits objectives.	 	\n 	Data Collection and Preparation: You&#039;ll lead the process of gathering relevant data \nfrom various sources, ensuring data quality, cleaning it, a	nd transforming it into a 	\nusable format for analysis.	 	\n 	Data Analysis: Utilizing your expertise in statistical methods, machine learning, and \ndata visualization, you&#039;ll conduct in	-depth data analysis to extract valuable insights, 	\nidentify patterns, and make 	data	-driven recommendations.	 	\n 	Problem Solving: As a lead consultant, you&#039;ll be expected to tackle complex data	-	\nrelated challenges and provide innovative solutions to business problems using data \nanalysis techniques.	 	\nData Scientist	 	Aug &#039;20	- Aug &#039;22	 	\nOffice Solution Inc.	 	Gurugram, IN	 	 Office Solution Inc is the top consulting, advisory &amp; implementation organization, microsoft partner \nlead by Mckinsey and EX BCG in India	 	\n 	\nExpertise in cu	tting edge technologies in applied deep learning, Machine learning 	\nand AI in one or more of the following fields	 	 	Manufacturing analytics : Root cause analysis, scrap reduction, cycle time \nreduction, warranty analytics	 	 	Supply chain analytics: Inventory 	control, demand forecasting	 	  	Sales Domain : Recommendation systems, Customer Segmentation, Price Elasticity \nComputer Vision	 	 	Strong expertise in coding languages;	 Python	 	  	Work experience in preparing data which includes preprocessing, feature 	selection, 	\nimputation, cleansing, transformation using Python	 	 	Work experience in data exploration techniques, such as, mean	-variance, k	-means, 	\nnearest	-neighbor, outlier techniques, and correlate anomalous sequences of events.	 	  	Proven track record and e	xperience with machine learning algorithms such as 	\nMultivariate Regression, classification models, clustering algorithms, support vector \nmachine, decision tree, random forest, neural network etc. DOE, Forecasting, \nSegmentation, Uncertainty Analysis etc.	 	 	Working with stake holders from different business units in Bosch to identify the \nbusiness opportunities for leveraging the data to drive business solutions. good \nknowledge of advanced statistical methods (automotive or manufacturing domain). \nMine and an	alyze data, applying statistical methods discover the hidden patterns and 	\nviewing experiences to identify critical data insights.	 	 	Experience in creating statistical models and/or optimization frameworks for \nimproving processes/products/profits	 	 	Proacti	vely develop new metrics and studies to quantify the value of different 	\naspects of product.	 	 	Translate analytic insights into concrete, actionable recommendations for business or \nproduct improvement.	 	 	Develop customized Data models and algorithms for the	 customer data so that 	\nthey are suited 100% to the specific requirements	 	 	Partner closely with product and engineering leaders throughout the lifecycle of \nproject. Ensure that necessary data is captured; analytic needs are well	-defined up 	\nfront and coordi	nate the analytic needs.	 	   Data Collection &amp; Web Scraping	 	 	Conducted extensive research on revenue management and pricing analytics in \nthe hospitality sector	 	 	Gathered pricing data from diff	erent aggregators by performing 	web scraping in 	\nPython	 for competitive analysis\n\nTableau/MS 	power BI, Alteryx	 	Applied various 	machine learning techniques using Python	 to build 	dynamic	 	\n 	pricing models	 and maximize profits	 	 	\nPackages:	 Scikit	-Learn, Numpy,	 	Developed segmentation models using 	K-means Clustering	 for exploring new	 	\nScipy, Pandas, 	NLTK,	 	user segments	 	 	\nBeautifulSoup, Matplotlib,	 	Predicted a cus	tomer&rsquo;s likelihood to book hotel	s at a given point in time based	 	\nStatsmodels, Jupyter Notebook	 	on the booking points	 	 	\n 	Designed a 	recommendation engine	 to suggest an ideal cluster price for various	 	\nStatistics/Machine Learning:	 	identified hotel segments	 	 	\nStatistical Analysis, Linear/Logistic	 	Conceptualized and implemented a 	sentiment analysis	 tool to rate hotels based	 	\nRegression, SVM, PCA, Ensemble	 	on 	subjective customer reviews	 	 	\nTrees, Random Forests, Clustering,	 	Created 	multivariate regression	-based attribution models using ad stock analysis	 	\nGraph Theory, Recommenders,	 	from digital marketing data	 	 	\nRegularisations	 	 	 	\n 	Algorithm Development &amp; 	Optimization	 	 	\nCERTIFICATIONS	 	Developed an algorithm for yield management using the concept of price elasticity	 	\nof demand	 	 	\nData Science Certification Training	 	\n 	\nDeployed multiple 	loss minimization &amp; optimization techniques	 	\n| Jspyder | May &#039;18	 	Led the	 development of a hotel performance assessment and pricing analysis	 	\n 	platform created via 	k-NN Algorithm	 	 	\n 	Key Achievements	 	 	\n 	Achieved a MoM 	14% increase	 in revenue through the application of dynamic	 	\n 	pricing	 	 	\n 	Successful in an overall 	loss reduction 	of 10%	 on monthly revenue by	 	\n 	implementing the loss minimisation techniques	 	 	\n 	Data Analyst	 	Sep &#039;18	- Aug &#039;20	 	\n 	ETPL Inc (Nokia Associate Partner)	 	Gurugram, IN	 	  	ETPL is one of the largest software development and Network companies in the world	 	 	Regression Modelling	 	 	Directed 	model development, validation, testing	 and implementation of 	\nanalytical products and applications	 	 	Developed an 	additive scoring model	 for QSM &amp; a logistic regression model to 	\nyield a 	K-S statistic of 51.5	 	 	Tested and imple	mented 	decision trees	, random forests	 and 	ensemble	 models via 	\nbagging and boosting	 	  	Data Management &amp; Data Mining	 	 	Deployed advanced 	text mining	 algorithms to identify search intent latent in 	\nindividual keywords	 	 	Employed 	Principle Component Analysis	 to analyse collinearity and reduce the 	\ndimensionality of datasets	 	 	Applied 	Bayesian Model Averaging (BMA)	 to combine individual keyword	-level 	\nmodels	 	 	\nEDUCATION	 	  	\nMachine Learning Certification	 	Sep &#039;19	- Dec &#039;20	 	 	\nTraining using Python	 	 	\nJspyder	 	Bengaluru,	 IN	 	 	Course Modules:	 	  	Introduction to Data Science | Data Extraction, Wrangling &amp; Visualization \nIntroduction to ML with Python | Supervised Learning I &amp; II Dimensionality \nReduction | Reinforcement Learning | Time Series Analysis	 	 	\nBachelor of 	Technology in Data Science	 	Jul &#039;14	- Jul &#039;18	 	 	\nPunjab Teachnical University	 	New Delhi, IN	 	 	Secured 	87%', 2, 2, 1, 'Recruiter', 'Un-assigned', 'SL', 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-04-23 07:34:36', 0);
INSERT INTO `resume` (`id`, `screeningId`, `adminId`, `candidateId`, `candidateDetailsId`, `resumeName`, `resumeOriginalName`, `resumeContent`, `isSkillScreened`, `isResumeScreened`, `isCron`, `isCandidate`, `isStatus`, `candidateShortlist`, `isInterviewAssign`, `enableInterviewReport`, `gptLanguageId`, `interviewAssignDate`, `psychoAssignDate`, `interviewValidity`, `isPsychoAssign`, `psychoValidity`, `created`, `createdBy`) VALUES
(328, 74, 63, NULL, NULL, '63_74_19730389056627648cd4925_Suryapratap_Sunahra.docx', 'Suryapratap Sunahra.docx', '﻿SURYAPRATAP SUNAHRA\r\nDetail-oriented professional, pursuing a dynamic role in Data Science in an organization of high repute for mutual growth and success.\r\ns.sunahra@gmail.com | +91-898-316-8114 | LinkedIn | GitHub | Pune, MH &ndash; 411014\r\n226695869950\r\nPROFESSIONAL SUMMARY: \r\nWorked as a Data Science Intern at Intellipaat Software Solutions Pvt. Ltd., representing practical skills in utilizing the MS SQL Server Database through SQL Server Management Studio (SSMS).\r\nComprehensive understanding of the concept of Data Science - Advanced Analytics, Predictive Modeler, Machine Learning algorithm in technical and functional domains.  \r\nSkilled in providing data-driven, action-oriented solutions to challenging business problems.          \r\nExcel in Python, NumPy, Pandas, Azure Cloud Services and Power BI, with a robust understanding of Deep Learning, NLP and Neural Networks, ANN, RNN, CNN. \r\nProficient in leveraging advanced statistical analysis techniques and machine learning algorithms to extract actionable insights and drive data-driven decision-making processes effectively.\r\nCapable of applying deep learning techniques to analyze and interpret complex datasets.\r\nStay well-informed of the latest advancements in data science and technology, incorporating innovative approaches into existing work-flows.\r\nPossess strong soft skills including communication, analytical thinking, adaptability, time-management and more.\r\nGood understanding of current market trend - Generative AI (GenAI), Large Language Models (LLMs), Transformers, Encoder/Decoder.\r\nCORE COMPETENCIES: Data Science, Data Analysis, Predictive Modelling, Machine Learning , Data Modelling, Python Programming, MLOps, Natural Language Processing (NLP), Deep Learning, Artificial Intelligence\r\nSKILLS: Jupyter Notebook, Google Colab, VS Code, MS SQL Server, Python, NumPy, Pandas, Azure Cloud Services, Power BI, DAX, Git/GitHub, Keras, TensorFlow, Statistics, NLP, Kaggle, Neural Networks, Flask, Data Visualization &amp;amp; Reporting. \r\nEXPERIENCE: \r\nIntellipaat &ndash; Edtech firm                                                          02/23 &ndash; 02/24\r\nData Science Intern\r\nKey Result Areas: \r\nSpearheaded projects in Jupyter &amp;amp; Google Colab environment, utilizing MS SQL Server Database for efficient decision-making.\r\nLeveraged Python &amp;amp; Machine Learning &ndash; AI Algorithms to derive meaningful insights for numerous projects.\r\nManaged cloud operations on Azure environment, including AutoML, Virtual machines &amp;amp; Azure SQL.\r\nEstablished expertise in NLP projects and Deep Learning frameworks for enhanced forecasts &amp;amp; AI executions utilizing TensorFlow, Keras and Neural networks.\r\nEngaged in Kaggle competitions to enhance predictive models and global reach.\r\nUtilized NLP for projects with a focus on NLU &amp;amp; NLG and derived insights through visualizations using PowerBI &amp;amp; DAX.\r\nPerformed Exploratory Data Analysis (EDA) on large small &amp;amp; medium data sets.\r\nCollaborated with cross-functional teams to enhance project outcomes and drive innovation. \r\nAnalyzing and processing complex data sets using advanced querying, visualization and analytics tools.\r\nPractical experience with ETL, data processing, database programming and data analytics.\r\nAnalyzed the pre trained model like VGG16, VGG19, Resnet50, Imagenet, etc. &amp;amp; predicted the images at output. Strong experience with Neural networks, ANN, RNN, CNN.\r\nGood experience with MLOps - Statistical modeling, NLP - Named Entity Recognition (NER), Sentiment Analysis, etc.\r\nPerformed data analysis and extracted meaningful insight for an enhanced Decision making. \r\nTools and packages: Pandas, Matplotlib, Seaborn, Plotly, Numpy, OpenCV, Flask, Sci-Kit Learn, Tensorflow, Keras, Facebook Prophet, NLP &ndash; Beautiful Soup, Spacy. \r\nHighlights: \r\nImplemented a data visualization dashboard using PowerBI, resulting in a 25% increase in data accessibility and insights for stakeholders, improving decision-making processes.\r\nSpearheaded a project resulting in a 20% increase in predictive model accuracy, optimizing decision-making processes and enhancing operational efficiency.\r\nPREVIOUS FULL TIME EXPERIENCE:\r\nInfojini Consulting Pvt. Ltd. | Senior Recruiter - US Staffing | Thane, MH | May, 22 &ndash; Jan, 24\r\nCompunnel Software Group | Account Manager | Goa, IN (Remote) | Feb, 21 &ndash; April, 22\r\nElevax Technologies | Senior Bench Sales Recruiter | Hyderabad (Remote) | June, 20 &ndash; Feb, 21\r\nVeracity Softwares Pvt. Ltd. | Bench Sales Recruiter | Pune, MH | June, 19 &ndash; March, 20\r\nPROJECTS: \r\nWalmart Inventory Management: Resolved inventory management challenges for a national retail chain at Walmart, optimizing supply chain dynamics.\r\nNetflix Recommendation Engine: Enhanced user experience on Netflix by developing a recommendation engine centered on customer viewing and rating data.\r\nAI Customer Churn Classification using Keras: Implemented a Keras-based AI model for binary classification to predict customer churn, leveraging company data for proactive retention.\r\nFace Recognition: Employed Python with OpenCV and haarcascade classifier to identify faces in multiple images for face recognition.\r\nAI Chatbot Implementation: Applied an AI chatbot utilizing IBM Watson Chatbot technology. \r\nNLP &ndash; Implementing LSTM: Utilized NLP and LSTM modeling to analyze Twitter data, determining conversation context and topics.\r\nBio-Signal Analysis for Smoking: Conducted bio-signal analysis to identify smoking behavior based on multiple biological parameters, employing bagging algorithms for high precision.\r\nWeb &ndash; Scrapping: Executed web scraping and crawling utilizing Python, NLP, BeautifulSoup-Requests to extract content and context from Wikipedia pages.\r\nEDUCATION:\r\nMBA&ndash; Human Resource | Savitribai Phule Pune University | Pune | 2019 \r\nB.E. Electronics &amp;amp; Telecommunication | Dr. Babasaheb Ambedkar Marathwada University | Aurangabad | 2017\r\nCERTIFICATIONS: \r\nCertified Data Scientist | Intellipaat\r\nAdvance Data Science &amp;amp; AI | IITM Pravartak\r\nPython for Data Science | IBM\r\nDeep Learning with TensorFlow | IBM\r\n\r\n\r\n\r\n', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-04-23 07:34:36', 0),
(329, 74, 63, NULL, NULL, '63_74_9945932356627648cd50f8_Sushant_Kumar_Tyagi.pdf', 'Sushant Kumar Tyagi.pdf', 'SUSHANT KUMAR TYAGI       \nDATA SCIENTIST     \nData  Scientist  with  5+  year  of  Industry  Experience,  Where  I  translated  various  Business  problems  into  Analytical \nsolutions  using  Machine  learning  and  Deep  learning.  I  dealt  with  clients  And   catered  optimized  real  data  science \nsolutions  \n   thesushantkumartyagi@gmail.com                                                                            +91 - 7417788010           \n          Delhi , India   \nTOOLS/TECHNIQUES     \n \nPYTHON ,NUMPY,PANDAS,MATPLOTLIB  \n \n   Machine learning     Feature Engineering,Selection   ,EDA    \n        \nNLP         SQL    \n        \nImage Processing , OpenCV  \n \n Statistical ,Predictive Analytics\nSKILLS\nData Mining,  Exploratory Data Analysis,  Clustering, \nClassification,  Linear Regression,  Logistics Regression, \nPredictive Modeling,  Artificial Neural Network, \nMachine Learning,  Optimization Techniques,  GAP \nAnalysis,  Sentiment Analysis,  Reporting &amp; Dashboard \ncreation\n-Rsystems Pvt. Ltd (June 2017 -Present)\n\n\n \n Experience in Developing Statistical/ML/Deep\nlearning model using varies techniques was also \ninvolved in requirement gathering and Client \ninteraction&amp; created model pipelined\n\n \n Pacific Global Pvt. Ltd (Aug 2016  &ndash;May 2017)\n\n\n \n Worked on healthcare Domain project ,Provided EDA\nto uncover meaningful pattern out data by \nvisualization tool like Tableau,Excel\n\nNthrive Global Solutions (Nov 201 5 &ndash; June 2016)\n*  Analyzing Insurance data and creating the Reports\n\nA.S Institute( DS-Trainer) (Aug 2021 -Present)\n-\n Developing and Delievering Training \nprograms,Providing guidance,Evaluation of Training \neffectiveness\n\n    EDUCATION\n  B.Tech in  Computer Science  from UPTU(2008-\n2012)\n    M.B.A in  Finance &amp; Marketing  from Subharti\nUniversity(Pursuing)\n  \n   \n  \n\n  \n  \n\nPROJECTS\n  \n  \n\n   \n \n \n FRAUDULENT \n MEDICAL \n PROVIDER DETECTION\n  \n  \n\nProvider  Fraud  is  one  of  the  biggest  problems  facing \n\nmedicare.  The  total \n medicare  spending  increased \n\nexponentially  due  to  medicare  frauds  and  the  goal  of \n\nthis  project  is  to  predict  the  potentially  fraudulent \n\nproviders based on the claims filed by them\n  \n so built a \n\nbinary classification model\n .\n  \n\n \n\nTABULAR DATA EXTRACTION \n  \n  \n\n\n \n I\n n  this \n project  we  built\n  \n an  end\n -\n to\n -\n end  Deep  l\n earning \n\narchitecture which has \n not only localize\n d\n  \n the Table in \n\nan  image,  but \n  \n also  generate\n d\n  \n structure  of  Table  by \n\nsegmenting  columns  in  that  Table.\n  \n After  detecting \n\nTable  structure  from  the  image,  we  use\n d\n  \n Pytesseract\n  \n\nOCR package to read the contents of the Table\n  \n\n \n\n    \n CUSTOMER CHURN PREDICTION\n  \n\n \n Predicted \n  \n the \n cu\n s\n to\n m\n er \n chu\n r\n n for a \n Tele\n c\n om \n Company\n  \n\nfor\n  \n a\n  \n period\n  \n of\n  \n 5\n  \n years\n  \n with\n  \n the\n  \n primary \n objectiv\n e\n  \n of \n\ninve\n s\n t\n i\n gating \n the \n parameters  contributing\n  \n for \n\ncu\n s\n tomer  churn. \n A \n L\n ogistic  Regression\n  \n Model  was \n\ndeveloped  and  val\n i\n dat\n e\n d \n with  test\n  \n d\n a\n ta  to  predict \n\ncu\n s\n tomer churn\n  \n\n \n  \n\n\n  \n Master SQL for Data Science Certification Course \n\nb\n y\n  \n Udemy\n  \n\n\n  \n AWS foundation (ML Basics)course certificate\n  \n\nHobbies\n   \n  \n\nMeditation, Cricket, Running         \n  \n\n \n  \nDeep Learning\n  \n\n,Tensorflow,Keras\n  \n\n   \n  \n', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-04-23 07:34:36', 0),
(330, 75, 63, NULL, NULL, '63_75_11908362346627775e0ad32_Abhra_Deblaskar.docx', 'Abhra Deblaskar.docx', '﻿Abhra Deblaskar\r\nPh: +91 9435514644  , 9113869569                                                                                                                  \r\nEmail: abhradeblaskar@gmail.com\r\nAddress: Flat no.110 (Block-2),                                                                                        \r\nELIL Abode Apartments,\r\nVenkateshwara Layout, Mahadevapura,\r\nBangalore, Pincode-560048\r\nSummary\r\nManagement Graduate with a total of over 11 years of diversified experience in Engineering and Data science domain. Career experience ranging from Industrial Project Management to Data Science including Statistical modeling and Model evaluation, experienced in Finance domain as well in FMCG/Retail domain.\r\nSkill Highlights\r\n&bull;Project Management\r\n&bull;Stakeholder Management\r\n&bull;Business Analytics\r\n&bull;Data Science\r\n&bull;Statistical Modeling\r\n&bull;Machine Learning\r\n&bull;Natural Language Processing\r\nProfessional Experiences\r\nLoonyCorn QuantMedia Pvt. Ltd. (July 2020-till date)\r\nDesignation: Data Science Analyst\r\nRoles and Responsibilities:\r\n&bull;Extracted and collected macro-economic indicators such as interest rates, bond yields , Liquidity data, volatility indices from Financial data sources using APIs and then creating visualizations to identify trends.\r\n&bull;Conducted exploratory data analysis to identify patterns and trends in data related to macro-economic indicators.\r\n&bull;Created Visualizations for displaying financial KPIs and correlation heatmaps in order to make informed decisions for effective risk management by ensuring portfolio diversification.\r\n&bull;Developed Machine learning models for Volatility prediction for maintaining consistent level of risk exposure.\r\n&bull;Developed Machine learning models for Anomaly detection on indicators related to F&amp;amp;O stocks.\r\n&bull;Conducted time series analysis on indicators related to indices, stocks , ETFs.\r\n&bull;Analyzed open interest and volume at different strike prices for taking positions related to trading.\r\n&bull;Built Sentiment analysis Models on financial news and social media using Natural language processing tools.\r\n&bull;Collaborated with trading team  to conduct stock specific analysis\r\nViaprom Technologies Pvt. Ltd. (July 2018-Sep 2018)\r\nDesignation: Business Analyst \r\nRoles and Responsibilities:\r\n&bull;Gathered requirements and important figures from clients.\r\n&bull;Built dashboards for better visualization of Business KPIs.\r\n&bull;Created customized reports for data visualization.\r\n&bull;Designed and developed data-driven exploratory analysis \r\nKantar IMRB (Mar 2017-July 2018)                                                                                                   [1 year 4 months]\r\nDesignation: Project Consultant \r\nRoles and Responsibilities:\r\n&bull;Gathered requirements and important figures from clients.\r\n&bull;Identified and interpreted client problems into actionable analysis.\r\n&bull;Managed Client objectives, expectations, and timelines.\r\n&bull;Managed and supported different stakeholders.\r\n&bull;Communicated changes to internal team members.\r\n&bull;Ensured insights and advanced analytical outputs are delivered through quality data sources.\r\n&bull;Worked with a team responsible for preprocessing of the data collected from the Market survey.\r\n&bull;Created customized reports for data visualization.\r\n&bull;Built statistical models for generating business insights based on the analysis of Consumer survey data using Statistical techniques and machine learning algorithms \r\n&bull;Evaluated Brand Potential through Proprietary tools.\r\nProject Portfolio/Client summary\r\nRetail Sales Data Analysis for Retail Client&ndash; India\r\nProject Description: The objective of the project was to analyze multi-dimensional retail sales data to uncover hidden trends and anomalies and develop a predictive model that helps business make proactive decisions. \r\nInvolvement Duration: ​2 months\r\nProject Role: ​Business Analyst\r\nResponsibilities:\r\n&bull;Exploratory data analysis\r\n&bull;Data Visualization\r\n&bull;Data Cleaning\r\n&bull;Statistical Modeling\r\nProject Team Size: ​3 members\r\nTools &amp;amp; Technologies:\r\n&bull;Time-series analysis\r\n&bull;Linear Regression\r\n&bull;Logistic Regression, SVM, Random Forest algorithms\r\n&bull;Python (pandas, matplotlib, seaborn)\r\n&bull;Power-BI for Data Visualization\r\nCustomer Segmentation for e-commerce Client &ndash; India\r\nProject Description: The objective of the project was to create customer segments among online consumers in order to reach them as per the interests of the profiles. \r\nInvolvement Duration: ​3 months\r\nProject Role: ​Consultant\r\nResponsibilities:\r\n&bull;Exploratory data analysis\r\n&bull;Data Visualization\r\n&bull;Data Cleaning\r\n&bull;Statistical Modeling\r\n&bull;Model Evaluation\r\nProject Team Size:​4 members\r\nTools &amp;amp; Technologies:\r\n&bull;K-means clustering algorithm\r\n&bull;Python (pandas, matplotlib, seaborn)\r\n&bull;Power-BI for Data Visualization\r\nDriving factors for food sample for FMCG Client &ndash; India\r\nProject Description: The objective of the project was to find out principal factors for driving likeability of the product among sample respondents. \r\nInvolvement Duration: ​2 months\r\nProject Role:​Consultant\r\nResponsibilities:\r\n&bull;Exploratory data analysis\r\n&bull;Data Visualization\r\n&bull;Data Cleaning\r\n&bull;Statistical Modeling\r\n&bull;Model Evaluation\r\nProject Team Size:​4 members\r\nTools &amp;amp; Technologies:\r\n&bull;Logistic Regression, Support Vector Machine, Random forest\r\n&bull;Python (pandas, sklearn )\r\n&bull;Power-BI for Data Visualization\r\nIndian Oil Tanking Engineering Project Pvt. Ltd. (July 2009- November 2014)                           [5 years 4 months]\r\nDesignation: Junior Manager\r\nRoles and Responsibilities:\r\n&bull;Managed Scheduling and monitoring of construction activities in Project Site.\r\n&bull;Worked on Supplier development, processing quotations, and also proper coordination with management for material procurement.\r\n&bull;Coordinated with vendors for cost negotiation and evaluation of Techno-commercial offers before finalization of Purchase Orders.\r\n&bull;Managed different stakeholders of the Projects.\r\n&bull;Managed resources i.e.  Manpower and Equipment, required to carry out Construction activities.\r\n&bull;Worked closely with Project Design team for any design specifications related issues, and B.O.Q estimation.\r\nEnercon India Limited (June 2007 &ndash; August 2008)                                                                          [1 year 2 months]\r\nDesignation: Graduate Engineer Trainee (Incoming Quality assurance)\r\nRoles and Responsibilities:\r\n&bull;Worked as a part of QA team doing Inspection &amp;amp; testing of power cables, electric motors, enameled copper wire as per IS, IEC and DIN standards.\r\n&bull;Handled the supplier quality improvement and commercial activities concerned with Electronics and electrical components for the Production Assembly Department.\r\n&bull;Worked on Identification and development of   dedicated and alternate vendor sources for achieving cost effective purchases of raw materials and reduction in delivery time.\r\nAcademics\r\nCourse\r\nInstitute &amp;amp; University\r\nYear of Passing\r\nCGPA/%\r\nPGDM EBIZ in Operations\r\nWelingkar Institute of Management Development and Research, Bangalore\r\n2017\r\n5.33/7\r\nB.Tech (Electrical Engg.)\r\nNational Institute of Technology, Silchar(Assam)\r\n2007\r\n6.42/10\r\nCertifications\r\n&bull;Certifications in Introduction to Deep Learning from Coursera (National Research University Higher school of Economics).\r\n&bull;Certifications in R programming ,Getting &amp;amp; Cleaning Data, Exploratory Data Analysis , Statistical Inference, Reproducible Research, Regression Models, Practical Machine learning, and Developing Data Products from Coursera (John Hopkins University).\r\n&bull;Certifications in SQL for Data Science and Data Wrangling, Analysis &amp;amp; AB Testing with SQL&nbsp;from Coursera (University of California, Davis).\r\nSoftware/Tools\r\n&bull;Python , SQL, OpenAI, Power-BI,  Azure AI,  Azure Machine Learning,  Azure Databricks\r\nI hereby state and acknowledge that the information provided is true and complete to the best of my knowledge and agree that any inaccurate and misleading information is solely my responsibility.\r\n(Signature)\r\n\r\n\r\n\r\n', 0, 0, NULL, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-04-23 08:54:54', 0),
(331, 75, 63, NULL, NULL, '63_75_14169041866627775e0b673_RAMENCHETIA.docx', 'RAMENCHETIA.docx', '\r\nSenior data scientist\r\nRamen Chetia \r\nProfile Summary\r\n11 years of experience as IT professional with experience in ETL, Machine Learning, Deep Learning, Natural Language processing, Computer Vision and Campaign management\r\nTotal 6 years of relevant experience in Machine learning and deep learning.\r\nHaving good knowledge in Azure data factory, used it to extract the data from different sources and created one final dataset.\r\nInvolved in projects from data extraction, data manipulation, EDA, Model building and deployment.\r\nHelped stakeholders in decision making by providing insights from the data. Pre-processing, EDA and Feature engineering\r\nmethods are used to develop models.\r\nStrong hands-on experience with Python and Pyspark in applying Machine learning algorithms to prepare a model.\r\nHard working, highly motivated, and reliable individual with a constructive approach to the business, client and to other team members.\r\nGood experience in developing data pipelines in Azure Data Factory to extract the data from source and apply transformations in the extracted data and store it in Blob storage.\r\nExperience in predictive analytics, campaign management analytics and Fraud detection.\r\nExperience on the implementation and maintenance of ML model, regular Hyper-parameter tuning is applied.\r\nWell verse with Code version control systems like Git.\r\nWorked with MLFlow architecture and it components, building a training pipeline with MLFlow.\r\nExpertise on creating ML model with advanced algorithms like Random forest, XGBoost, LightGBM, OpenCV.\r\nExperience in end to end ML model solution design, from extraction till model deployment.\r\nTechnical Skills\r\nApplication ADF, Databricks, Snowflake, Databricks AutoML\r\nProgramming Languages Python, Pyspark, R\r\nIDE Databricks notebook, Jupyter Notebook, PyCharm\r\nDatabase My SQL, Oracle DB\r\nCVC, Container Git, Docker\r\nAlgorithms &amp;amp; Concepts Logistics regression, CART, Bagging, Boosting, NLP, CV\r\nTech in ML Regression, Classification analysis, NLP, CV, Recommender engine, Campaign management, CNN, 2D-LSTM, Tensorflow\r\nPROFESSIONAL EXPERIENCE\r\nMonth-Year Designation or Role/Company name Role Responsibilities\r\nMar 2022\r\n(Currently Working) Technical analyst (Data science)\r\n(Coforge Pvt Ltd) Worked for Voya Financial to implement ML solutions\r\nDay started with analysing the data and devising a solution to retrieve the hidden insights from data.\r\nBuild ML model, handling end to end process. Created pipeline to extract the data, work on the data, build a model and deploy the model in production\r\nenvironment.\r\nMigrating SPSS pipelines to python and Pyspark codes in Azure cloud and test it.\r\nHandled Fraud detection and Customer engagement capabilities, implemented ML solutions in different use-case\r\nNov 2019 -Mar 2022 Data Scientist (Capgemini Malaysia Bhd.) Worked for RHB bank and implemented ML solutions to replace the rule based legacy systems.\r\nDeveloping solutions for various departments where we have\r\nimplemented advance analytics and tried to find optimal solutions to boost the revenue growth.\r\nFrom machine learning to deep learning, developed predictive ML solutions for different use-cases.\r\nDiscussion with stakeholders to understand the rule based systems that are being used and finding solutions to replace it with smart ML model.\r\nWorked in advanced AI algorithms like Pytessaract to develop a model for OCR using OpenCV.\r\nWorked in end to end solution development, data extraction to model deployment.\r\nETL Developer Creating data pipelines to extract, transform and load data into data warehousing environment\r\nDesigned and maintained data pipelines and debugged if any issue arises\r\nWorked with different teams to deploy enhancement works.\r\nWorked on POC&rsquo;s to apply machine learning algorithms to different data\r\nGained knowledge on Data pre-processing, exploratory data analysis, extracting valuable insights from data.\r\nApplying Hyper-parameter tuning to re-train old models and update it.\r\nSep 2012&ndash; Oct 2017 (IBM India Pvt. ltd) Junior Data Scientist Dec 2017 &ndash; Nov 2019 (IBM India pvt. ltd) PROJECT EXPERIENCE\r\nProject name: Managed account adoption for Voya Financial\r\nDuration Feb , 2023, to Nov, 2023 Role Data Scientist\r\nProject Type ML solution to replace legacy system Technology ML, Python, Pyspark, Azure, Databricks, SQL\r\nMy\r\nResponsibilities Work with stakeholders to understand the work, devise some plan with client to apply ML solutions to it to make it smart and effective\r\nExtract data from different sources, massage the data and create a final dataset, save it in blob storage or create a table to store the data.\r\nImport the data to Databricks notebook and write python codes to pre-process, EDA and model development.\r\nUse MLFlow to create pipeline and by using Docker to deploy the model.\r\nAutomate and integrate the process by using ADF pipeline.\r\nWhile extracting the data, quality of the data are checked and verified. Source target mismatch, Invalid values, Null values, non-standard date formats are some of the examples of checks done.\r\nAfter completing the pre-process, analysis of data is done, if any hidden patterns are found then they are visualized with different graphs to share it with client.\r\nFeature selection is done with the help of business knowledge, ML algorithms. These features are extensively studied, new features are created with feature engineering if required.\r\nTableau is used to generate different graphs to analyse the pattern and distribution of data.\r\nDifferent ML algorithms are used to develop the model and compare the performance, cross validation and hyper-parameter tuning is used to improve the performance of the model.\r\nAfter multiple runs in production, the performance of the model is monitored and if any depletion of performance happen then re-training of the model is done.\r\nProject name: Cross sell of health benefit products\r\nDuration Mar 2022 to Dec 2023 Role Data Scientist\r\nProject Type ML solution to replace legacy system Technology ML, Python, Pyspark, Azure, Databricks, SPSS\r\nMy\r\nResponsibilities This is a migration project from SPSS to cloud.\r\nWhile extracting the data, the quality of the data are checked and verified. Source target mismatch, Invalid values, Null values, non-standard date formats are some of the examples of checks done.\r\nComparing the source of the SPSS pipeline and dataset made in ADF to extract the data.\r\nCreated ML model after completing the pre-processing and exploratory data analysis, this model mimics the SPSS model, but performance is enhanced in cloud.\r\nTableau is used to generate different graphs to analyse the pattern and distribution of data.\r\nAn Auto ML model is created in data bricks to compare the performances of the ML model, along with that parameter, features are also compared.\r\nName of the Project: - Money mule detection (Fraud detection)\r\nDuration Sep 2021&ndash; Feb 2022 Role Data Scientist\r\nProject Type Fraud detection Analytics Technology ML, Python, Pyspark, Azure, SAS, SQL\r\nMy\r\nResponsibilities This is a use-case for Anti money laundering department, money mules are the account holders of the bank which are being used to launder money. From the customer base, this use-case is to find the accounts which can be used as money mules.\r\nBy using ML solutions I have created a model to identify those money mule accounts which can be used to launder money.\r\nLegacy system is used to study the features being used in it, the different source systems are identified.\r\nWhile extracting the data, quality of the data are checked and verified. Source target mismatch, Invalid values, Null values, non-standard date formats are some of the examples of checks done.\r\nUsing SAS the required data is extracted and saved as blob storage files.\r\nAfter completing the pre-process, analysis of data is done, if any hidden pattern are found then they are visualized with different graphs to share it with client.\r\nFeature selection is done with the help of business knowledge, ML algorithms. These features are extensively studied, new features are created with feature engineering if required.\r\nPython Matplotlib and Seaborn libraries is used to generate different graphs to analyse the pattern and distribution of data.\r\nDifferent ML algorithms are used to develop the model and compare the performance, cross validation and hyper-parameter tuning is used to improve the performance of the model.\r\nAfter modelling the model is deployed using Docker, MLFlow\r\nName of the Project: -Credit card forms scan\r\nDuration Mar 2021&ndash; Aug 2021 Role Data Scientist\r\nProject Type Handwritten character recognition Technology ML, Python, OpenCV, Tensorflow, CNN, 2D-LSTM\r\nMy\r\nResponsibilities Project is for the department of GIA (Group Internal audit), task is to read and extract required information from scanned documents of credit card.\r\nSome of the fields such as DoB, application number which is present in the credit card application form need to be extracted and saved in a table.\r\nFor this task Numpy, OpenCV, Tensorflow is used to pre-process the images, making it ready for Pytesseract to read the image file.\r\nThe data that is being extracted by Pytesseract is then processed from regex to extract the required information.\r\nThis task is also tried using CNN and 2D-LSTM, the result of this task is compared with the Pytesseract results.\r\nAll the image pre-processing like image threshold, changing image angle to remove the noise that are.\r\npresent in the images, also Augmentation process is followed during training.\r\nNational Institute of Engineering, Mysore\r\nIIT - Kharagpur\r\nMCA\r\nBusiness Analytics and AI certification\r\nEDUCATION\r\nNational Institute of Engineering, Mysore\r\nIIT - Kharagpur\r\nMCA\r\nBusiness Analytics and AI certification\r\nEDUCATION\r\n\r\nDetailed IT Skills\r\nSkill Name Exp. in Years Skill Name Exp. in Years Skills Exp. in Years\r\nLanguages Languages Operating Systems\r\nService Now ITSM Python 5 windows 10\r\nService Now ITOM Pyspark 3 Unix 1\r\nService now ITIL R 1 Big Data Platform Cloud Development Digital\r\nPyspark 2 Azure 2 DataBricks 2 Tools/ Platforms S/w Configuration tools Hardware\r\nGit Hub 2 Azure Data Factory 2 --\r\nJenkins DataBricks AutoML 2 MLFlow 1 Testing Practice Domain\r\nBanking &amp;amp; Finance 7\r\nInsurance 2\r\nDatabases Retail 1\r\nOracle 6 SQL 6 ', 0, 0, NULL, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-04-23 08:54:54', 0),
(332, 75, 63, NULL, NULL, '63_75_9787755686627775e0bf78_Sonu_Kumar.pdf', 'Sonu Kumar.pdf', 'Sonu Kumar	 	\n 	\nPython Expert, Machine \nLearning, AI, NLP, SQL 	\nServer	 	 9319263940	 	\nenggsonugupta01@gmail.com \nNew Delhi	 	 https://www.linkedin.com/in/s onu	-	\nkumar	-a587ab16b/	 	 \nSUMMARY	 	  \n4.7	 years  experienced  data  analytics 	\nprofessional  possessing  proven  track \nrecord  of  successfully  applying \neconometric  modelling,  algorithm \ndevelopment  &amp;  machine  learning \ntechniques  to  solve  key  business \nproblems.  Highly  skilled  in  applying \nadvanced  machine  le	arning/statistical 	\nalgorithms  such  as  Gradient  Boosted \nTrees,  Random  Forests,  Ensemble \nModels,  Clustering  etc.  to  real  world \nproblems  using  Python.  Looking \nforward  to  applying the acquired  gamut \nof skills to a challenging role in the data \nanalytics and mac	hine learning space.	 	\n \n           	KEY SKILLS	 	\n   Data &amp; Quantitative Analysis	 	\n \n  Data Science &bull; Big Data Analytics	 	 &bull; Predictive/Statistical Modelling	 	 &bull; Data Mining &bull; Data Visualization	 	 &bull; Machine Learning Algorithms	 	 	&bull; Business Intelligence &bull; Data \nWrangling &bull; 	Optimization	 	\n 	Techniques	 	\n 	\n&bull; Project Monitoring &amp; 	\nManagement	 	\n&bull; Coordination &amp; Liaison	 	 &bull; Client Relationship Management	 	 	&bull; Strategic Planning	 	\n \nTECHNICAL SKILLS	 	 	Tools	: Python, 	JIRA, 	PostgreSQL, 	\nAWS EC2, Azure, MongoDB, Spark, \nML, AI, Python,SQL, Numpy,	 	\nPandas, 	Seaborne,	 Matplotlib, Azure 	\nData Factory, Azure Datalake, Azure \nCodmosdb, Data bricks ,NLP, \nARIMA,TIme series Analysis,	 	 	\nPROFESSIONAL EXPERIENCE	 	  \nLead Consultant                                                       	Aug 2022 to Current	 	\nLearning Links 	Foundation	 	\n(Women in Data) Project	. 	\n 	Project Management: As a lead consultant, you&#039;ll be responsible for managing data \nanalysis projects from initiation to completion. This involves defining	 the project 	\nscope, setting timelines, allocating resources, and ensuring that the project meets \nits objectives.	 	\n 	Data Collection and Preparation: You&#039;ll lead the process of gathering relevant data \nfrom various sources, ensuring data quality, cleaning it, a	nd transforming it into a 	\nusable format for analysis.	 	\n 	Data Analysis: Utilizing your expertise in statistical methods, machine learning, and \ndata visualization, you&#039;ll conduct in	-depth data analysis to extract valuable insights, 	\nidentify patterns, and make 	data	-driven recommendations.	 	\n 	Problem Solving: As a lead consultant, you&#039;ll be expected to tackle complex data	-	\nrelated challenges and provide innovative solutions to business problems using data \nanalysis techniques.	 	\nData Scientist	 	Aug &#039;20	- Aug &#039;22	 	\nOffice Solution Inc.	 	Gurugram, IN	 	 Office Solution Inc is the top consulting, advisory &amp; implementation organization, microsoft partner \nlead by Mckinsey and EX BCG in India	 	\n 	\nExpertise in cu	tting edge technologies in applied deep learning, Machine learning 	\nand AI in one or more of the following fields	 	 	Manufacturing analytics : Root cause analysis, scrap reduction, cycle time \nreduction, warranty analytics	 	 	Supply chain analytics: Inventory 	control, demand forecasting	 	  	Sales Domain : Recommendation systems, Customer Segmentation, Price Elasticity \nComputer Vision	 	 	Strong expertise in coding languages;	 Python	 	  	Work experience in preparing data which includes preprocessing, feature 	selection, 	\nimputation, cleansing, transformation using Python	 	 	Work experience in data exploration techniques, such as, mean	-variance, k	-means, 	\nnearest	-neighbor, outlier techniques, and correlate anomalous sequences of events.	 	  	Proven track record and e	xperience with machine learning algorithms such as 	\nMultivariate Regression, classification models, clustering algorithms, support vector \nmachine, decision tree, random forest, neural network etc. DOE, Forecasting, \nSegmentation, Uncertainty Analysis etc.	 	 	Working with stake holders from different business units in Bosch to identify the \nbusiness opportunities for leveraging the data to drive business solutions. good \nknowledge of advanced statistical methods (automotive or manufacturing domain). \nMine and an	alyze data, applying statistical methods discover the hidden patterns and 	\nviewing experiences to identify critical data insights.	 	 	Experience in creating statistical models and/or optimization frameworks for \nimproving processes/products/profits	 	 	Proacti	vely develop new metrics and studies to quantify the value of different 	\naspects of product.	 	 	Translate analytic insights into concrete, actionable recommendations for business or \nproduct improvement.	 	 	Develop customized Data models and algorithms for the	 customer data so that 	\nthey are suited 100% to the specific requirements	 	 	Partner closely with product and engineering leaders throughout the lifecycle of \nproject. Ensure that necessary data is captured; analytic needs are well	-defined up 	\nfront and coordi	nate the analytic needs.	 	   Data Collection &amp; Web Scraping	 	 	Conducted extensive research on revenue management and pricing analytics in \nthe hospitality sector	 	 	Gathered pricing data from diff	erent aggregators by performing 	web scraping in 	\nPython	 for competitive analysis\n\nTableau/MS 	power BI, Alteryx	 	Applied various 	machine learning techniques using Python	 to build 	dynamic	 	\n 	pricing models	 and maximize profits	 	 	\nPackages:	 Scikit	-Learn, Numpy,	 	Developed segmentation models using 	K-means Clustering	 for exploring new	 	\nScipy, Pandas, 	NLTK,	 	user segments	 	 	\nBeautifulSoup, Matplotlib,	 	Predicted a cus	tomer&rsquo;s likelihood to book hotel	s at a given point in time based	 	\nStatsmodels, Jupyter Notebook	 	on the booking points	 	 	\n 	Designed a 	recommendation engine	 to suggest an ideal cluster price for various	 	\nStatistics/Machine Learning:	 	identified hotel segments	 	 	\nStatistical Analysis, Linear/Logistic	 	Conceptualized and implemented a 	sentiment analysis	 tool to rate hotels based	 	\nRegression, SVM, PCA, Ensemble	 	on 	subjective customer reviews	 	 	\nTrees, Random Forests, Clustering,	 	Created 	multivariate regression	-based attribution models using ad stock analysis	 	\nGraph Theory, Recommenders,	 	from digital marketing data	 	 	\nRegularisations	 	 	 	\n 	Algorithm Development &amp; 	Optimization	 	 	\nCERTIFICATIONS	 	Developed an algorithm for yield management using the concept of price elasticity	 	\nof demand	 	 	\nData Science Certification Training	 	\n 	\nDeployed multiple 	loss minimization &amp; optimization techniques	 	\n| Jspyder | May &#039;18	 	Led the	 development of a hotel performance assessment and pricing analysis	 	\n 	platform created via 	k-NN Algorithm	 	 	\n 	Key Achievements	 	 	\n 	Achieved a MoM 	14% increase	 in revenue through the application of dynamic	 	\n 	pricing	 	 	\n 	Successful in an overall 	loss reduction 	of 10%	 on monthly revenue by	 	\n 	implementing the loss minimisation techniques	 	 	\n 	Data Analyst	 	Sep &#039;18	- Aug &#039;20	 	\n 	ETPL Inc (Nokia Associate Partner)	 	Gurugram, IN	 	  	ETPL is one of the largest software development and Network companies in the world	 	 	Regression Modelling	 	 	Directed 	model development, validation, testing	 and implementation of 	\nanalytical products and applications	 	 	Developed an 	additive scoring model	 for QSM &amp; a logistic regression model to 	\nyield a 	K-S statistic of 51.5	 	 	Tested and imple	mented 	decision trees	, random forests	 and 	ensemble	 models via 	\nbagging and boosting	 	  	Data Management &amp; Data Mining	 	 	Deployed advanced 	text mining	 algorithms to identify search intent latent in 	\nindividual keywords	 	 	Employed 	Principle Component Analysis	 to analyse collinearity and reduce the 	\ndimensionality of datasets	 	 	Applied 	Bayesian Model Averaging (BMA)	 to combine individual keyword	-level 	\nmodels	 	 	\nEDUCATION	 	  	\nMachine Learning Certification	 	Sep &#039;19	- Dec &#039;20	 	 	\nTraining using Python	 	 	\nJspyder	 	Bengaluru,	 IN	 	 	Course Modules:	 	  	Introduction to Data Science | Data Extraction, Wrangling &amp; Visualization \nIntroduction to ML with Python | Supervised Learning I &amp; II Dimensionality \nReduction | Reinforcement Learning | Time Series Analysis	 	 	\nBachelor of 	Technology in Data Science	 	Jul &#039;14	- Jul &#039;18	 	 	\nPunjab Teachnical University	 	New Delhi, IN	 	 	Secured 	87%', 0, 0, NULL, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-04-23 08:54:54', 0),
(333, 75, 63, NULL, NULL, '63_75_4208198196627775e0ce52_Suryapratap_Sunahra.docx', 'Suryapratap Sunahra.docx', '﻿SURYAPRATAP SUNAHRA\r\nDetail-oriented professional, pursuing a dynamic role in Data Science in an organization of high repute for mutual growth and success.\r\ns.sunahra@gmail.com | +91-898-316-8114 | LinkedIn | GitHub | Pune, MH &ndash; 411014\r\n226695869950\r\nPROFESSIONAL SUMMARY: \r\nWorked as a Data Science Intern at Intellipaat Software Solutions Pvt. Ltd., representing practical skills in utilizing the MS SQL Server Database through SQL Server Management Studio (SSMS).\r\nComprehensive understanding of the concept of Data Science - Advanced Analytics, Predictive Modeler, Machine Learning algorithm in technical and functional domains.  \r\nSkilled in providing data-driven, action-oriented solutions to challenging business problems.          \r\nExcel in Python, NumPy, Pandas, Azure Cloud Services and Power BI, with a robust understanding of Deep Learning, NLP and Neural Networks, ANN, RNN, CNN. \r\nProficient in leveraging advanced statistical analysis techniques and machine learning algorithms to extract actionable insights and drive data-driven decision-making processes effectively.\r\nCapable of applying deep learning techniques to analyze and interpret complex datasets.\r\nStay well-informed of the latest advancements in data science and technology, incorporating innovative approaches into existing work-flows.\r\nPossess strong soft skills including communication, analytical thinking, adaptability, time-management and more.\r\nGood understanding of current market trend - Generative AI (GenAI), Large Language Models (LLMs), Transformers, Encoder/Decoder.\r\nCORE COMPETENCIES: Data Science, Data Analysis, Predictive Modelling, Machine Learning , Data Modelling, Python Programming, MLOps, Natural Language Processing (NLP), Deep Learning, Artificial Intelligence\r\nSKILLS: Jupyter Notebook, Google Colab, VS Code, MS SQL Server, Python, NumPy, Pandas, Azure Cloud Services, Power BI, DAX, Git/GitHub, Keras, TensorFlow, Statistics, NLP, Kaggle, Neural Networks, Flask, Data Visualization &amp;amp; Reporting. \r\nEXPERIENCE: \r\nIntellipaat &ndash; Edtech firm                                                          02/23 &ndash; 02/24\r\nData Science Intern\r\nKey Result Areas: \r\nSpearheaded projects in Jupyter &amp;amp; Google Colab environment, utilizing MS SQL Server Database for efficient decision-making.\r\nLeveraged Python &amp;amp; Machine Learning &ndash; AI Algorithms to derive meaningful insights for numerous projects.\r\nManaged cloud operations on Azure environment, including AutoML, Virtual machines &amp;amp; Azure SQL.\r\nEstablished expertise in NLP projects and Deep Learning frameworks for enhanced forecasts &amp;amp; AI executions utilizing TensorFlow, Keras and Neural networks.\r\nEngaged in Kaggle competitions to enhance predictive models and global reach.\r\nUtilized NLP for projects with a focus on NLU &amp;amp; NLG and derived insights through visualizations using PowerBI &amp;amp; DAX.\r\nPerformed Exploratory Data Analysis (EDA) on large small &amp;amp; medium data sets.\r\nCollaborated with cross-functional teams to enhance project outcomes and drive innovation. \r\nAnalyzing and processing complex data sets using advanced querying, visualization and analytics tools.\r\nPractical experience with ETL, data processing, database programming and data analytics.\r\nAnalyzed the pre trained model like VGG16, VGG19, Resnet50, Imagenet, etc. &amp;amp; predicted the images at output. Strong experience with Neural networks, ANN, RNN, CNN.\r\nGood experience with MLOps - Statistical modeling, NLP - Named Entity Recognition (NER), Sentiment Analysis, etc.\r\nPerformed data analysis and extracted meaningful insight for an enhanced Decision making. \r\nTools and packages: Pandas, Matplotlib, Seaborn, Plotly, Numpy, OpenCV, Flask, Sci-Kit Learn, Tensorflow, Keras, Facebook Prophet, NLP &ndash; Beautiful Soup, Spacy. \r\nHighlights: \r\nImplemented a data visualization dashboard using PowerBI, resulting in a 25% increase in data accessibility and insights for stakeholders, improving decision-making processes.\r\nSpearheaded a project resulting in a 20% increase in predictive model accuracy, optimizing decision-making processes and enhancing operational efficiency.\r\nPREVIOUS FULL TIME EXPERIENCE:\r\nInfojini Consulting Pvt. Ltd. | Senior Recruiter - US Staffing | Thane, MH | May, 22 &ndash; Jan, 24\r\nCompunnel Software Group | Account Manager | Goa, IN (Remote) | Feb, 21 &ndash; April, 22\r\nElevax Technologies | Senior Bench Sales Recruiter | Hyderabad (Remote) | June, 20 &ndash; Feb, 21\r\nVeracity Softwares Pvt. Ltd. | Bench Sales Recruiter | Pune, MH | June, 19 &ndash; March, 20\r\nPROJECTS: \r\nWalmart Inventory Management: Resolved inventory management challenges for a national retail chain at Walmart, optimizing supply chain dynamics.\r\nNetflix Recommendation Engine: Enhanced user experience on Netflix by developing a recommendation engine centered on customer viewing and rating data.\r\nAI Customer Churn Classification using Keras: Implemented a Keras-based AI model for binary classification to predict customer churn, leveraging company data for proactive retention.\r\nFace Recognition: Employed Python with OpenCV and haarcascade classifier to identify faces in multiple images for face recognition.\r\nAI Chatbot Implementation: Applied an AI chatbot utilizing IBM Watson Chatbot technology. \r\nNLP &ndash; Implementing LSTM: Utilized NLP and LSTM modeling to analyze Twitter data, determining conversation context and topics.\r\nBio-Signal Analysis for Smoking: Conducted bio-signal analysis to identify smoking behavior based on multiple biological parameters, employing bagging algorithms for high precision.\r\nWeb &ndash; Scrapping: Executed web scraping and crawling utilizing Python, NLP, BeautifulSoup-Requests to extract content and context from Wikipedia pages.\r\nEDUCATION:\r\nMBA&ndash; Human Resource | Savitribai Phule Pune University | Pune | 2019 \r\nB.E. Electronics &amp;amp; Telecommunication | Dr. Babasaheb Ambedkar Marathwada University | Aurangabad | 2017\r\nCERTIFICATIONS: \r\nCertified Data Scientist | Intellipaat\r\nAdvance Data Science &amp;amp; AI | IITM Pravartak\r\nPython for Data Science | IBM\r\nDeep Learning with TensorFlow | IBM\r\n\r\n\r\n\r\n', 0, 0, NULL, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-04-23 08:54:54', 0),
(334, 75, 63, NULL, NULL, '63_75_485690516627775e0d4b9_Sushant_Kumar_Tyagi.pdf', 'Sushant Kumar Tyagi.pdf', 'SUSHANT KUMAR TYAGI       \nDATA SCIENTIST     \nData  Scientist  with  5+  year  of  Industry  Experience,  Where  I  translated  various  Business  problems  into  Analytical \nsolutions  using  Machine  learning  and  Deep  learning.  I  dealt  with  clients  And   catered  optimized  real  data  science \nsolutions  \n   thesushantkumartyagi@gmail.com                                                                            +91 - 7417788010           \n          Delhi , India   \nTOOLS/TECHNIQUES     \n \nPYTHON ,NUMPY,PANDAS,MATPLOTLIB  \n \n   Machine learning     Feature Engineering,Selection   ,EDA    \n        \nNLP         SQL    \n        \nImage Processing , OpenCV  \n \n Statistical ,Predictive Analytics\nSKILLS\nData Mining,  Exploratory Data Analysis,  Clustering, \nClassification,  Linear Regression,  Logistics Regression, \nPredictive Modeling,  Artificial Neural Network, \nMachine Learning,  Optimization Techniques,  GAP \nAnalysis,  Sentiment Analysis,  Reporting &amp; Dashboard \ncreation\n-Rsystems Pvt. Ltd (June 2017 -Present)\n\n\n \n Experience in Developing Statistical/ML/Deep\nlearning model using varies techniques was also \ninvolved in requirement gathering and Client \ninteraction&amp; created model pipelined\n\n \n Pacific Global Pvt. Ltd (Aug 2016  &ndash;May 2017)\n\n\n \n Worked on healthcare Domain project ,Provided EDA\nto uncover meaningful pattern out data by \nvisualization tool like Tableau,Excel\n\nNthrive Global Solutions (Nov 201 5 &ndash; June 2016)\n*  Analyzing Insurance data and creating the Reports\n\nA.S Institute( DS-Trainer) (Aug 2021 -Present)\n-\n Developing and Delievering Training \nprograms,Providing guidance,Evaluation of Training \neffectiveness\n\n    EDUCATION\n  B.Tech in  Computer Science  from UPTU(2008-\n2012)\n    M.B.A in  Finance &amp; Marketing  from Subharti\nUniversity(Pursuing)\n  \n   \n  \n\n  \n  \n\nPROJECTS\n  \n  \n\n   \n \n \n FRAUDULENT \n MEDICAL \n PROVIDER DETECTION\n  \n  \n\nProvider  Fraud  is  one  of  the  biggest  problems  facing \n\nmedicare.  The  total \n medicare  spending  increased \n\nexponentially  due  to  medicare  frauds  and  the  goal  of \n\nthis  project  is  to  predict  the  potentially  fraudulent \n\nproviders based on the claims filed by them\n  \n so built a \n\nbinary classification model\n .\n  \n\n \n\nTABULAR DATA EXTRACTION \n  \n  \n\n\n \n I\n n  this \n project  we  built\n  \n an  end\n -\n to\n -\n end  Deep  l\n earning \n\narchitecture which has \n not only localize\n d\n  \n the Table in \n\nan  image,  but \n  \n also  generate\n d\n  \n structure  of  Table  by \n\nsegmenting  columns  in  that  Table.\n  \n After  detecting \n\nTable  structure  from  the  image,  we  use\n d\n  \n Pytesseract\n  \n\nOCR package to read the contents of the Table\n  \n\n \n\n    \n CUSTOMER CHURN PREDICTION\n  \n\n \n Predicted \n  \n the \n cu\n s\n to\n m\n er \n chu\n r\n n for a \n Tele\n c\n om \n Company\n  \n\nfor\n  \n a\n  \n period\n  \n of\n  \n 5\n  \n years\n  \n with\n  \n the\n  \n primary \n objectiv\n e\n  \n of \n\ninve\n s\n t\n i\n gating \n the \n parameters  contributing\n  \n for \n\ncu\n s\n tomer  churn. \n A \n L\n ogistic  Regression\n  \n Model  was \n\ndeveloped  and  val\n i\n dat\n e\n d \n with  test\n  \n d\n a\n ta  to  predict \n\ncu\n s\n tomer churn\n  \n\n \n  \n\n\n  \n Master SQL for Data Science Certification Course \n\nb\n y\n  \n Udemy\n  \n\n\n  \n AWS foundation (ML Basics)course certificate\n  \n\nHobbies\n   \n  \n\nMeditation, Cricket, Running         \n  \n\n \n  \nDeep Learning\n  \n\n,Tensorflow,Keras\n  \n\n   \n  \n', 0, 0, NULL, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-04-23 08:54:54', 0);
INSERT INTO `resume` (`id`, `screeningId`, `adminId`, `candidateId`, `candidateDetailsId`, `resumeName`, `resumeOriginalName`, `resumeContent`, `isSkillScreened`, `isResumeScreened`, `isCron`, `isCandidate`, `isStatus`, `candidateShortlist`, `isInterviewAssign`, `enableInterviewReport`, `gptLanguageId`, `interviewAssignDate`, `psychoAssignDate`, `interviewValidity`, `isPsychoAssign`, `psychoValidity`, `created`, `createdBy`) VALUES
(335, 76, 63, NULL, NULL, '63_76_1944350916628bb943fa45_ANILKUMARMISHRA.docx', 'ANILKUMARMISHRA.docx', '﻿\r\n\r\nE-mail:anil.mishra3@gmail.com; Phone:+91-9986660401/WhatsApp(+91-9986660401)\r\nSr. Data Modeler, SAP BOBJ/HANA, Tableau/Power BI Technology Lead Consultant\r\n\r\nANIL KUMAR MISHRA\r\nSenior Technology Savvy IT Professional with nearly 17+ years of experience (Including 5 Years in USA) in Data Modeling, SAP BOBJ/HANA, Tableau, Power BI, Spark, Erwin, Hive, Scrum Master also taking initiatives for business excellence through Agile Development Models.\r\nTargeting senior level assignments in Data Modeling/Data Analytics/Data Scientist &amp;amp; as Scrum Master/Business Analyst\r\n     Profile Summary \r\n\r\nComprehensive experience in leading teams to design &amp;amp; implement successful projects that align business &amp;amp; its objectives and deliver rapid results using Agile &amp;amp; Scrum Methodologies\r\nCertified as Scrum Master (SMC Certificate ID &ndash; 97252)\r\nExpert in establishing &amp;amp; building next-generation Data Modeling, Data Analytics &amp;amp; Visualization platform for IDS (Integrated Data Solutions) business unit via insightful data mining &amp;amp; analysis, the creation of actionable data for all the financial activities\r\nHaving strong experience in Tableau, Power BI/SSRS, 5 E2E SAP BOBJ Implementation, SAP HANA Data Modeling using Attribute Views, Analytic Views and Calculation Views\r\nAlmost 3+ years of work experience in Big Data with good knowledge of Data Modeling using ERWIN, HIVE in Hadoop and Spark framework, HDFS and parallel processing implementation.\r\nProven track record of winning number of appreciations from both offshore &amp;amp; onsite managers for the commitment and successful delivery of each project; worked with client as Report Lead for 5 years in USA (Onshore)\r\nScrum Master: Facilitated meetings (daily scrum, sprint planning, sprint demo and retrospective), shielding the team, providing conflict resolutions and creating communication channel (Team, Product Owner &amp;amp; Stakeholder)\r\nActing as an Escalation Gate to resolve critical issues of the team members; expert in mapping client&rsquo;s requirements, custom designing solutions &amp;amp; troubleshooting for complex Information Systems Management  \r\nSkilled at gathering business requirements, analyzing business process, Identifying Gaps, Design and Build, Unit/Integration testing and Go-live\r\nUnique blend of leadership skills wherein leading end-to-end service delivery management and ensuring effective management of various resources to client requirements\r\n     Notable Accomplishments Across the Career\r\n\r\nReceived Best Employee Excellence Award for Working as Role Model in Team\r\nAttained as Best Tools Method &amp;amp; Best Practices Award (Thrice) for creating and using tools\r\nSuccessfully won APEX Award for 2017 &amp;amp; STAR Award 2020 for Technical Capabilities \r\n     Work ExperienceSince Dec&rsquo;22: Nexperia, Malaysia as Data Modeler.\r\nSince Mar&rsquo;22: Mphasis, Bangalore as Project Manager/Senior Data Modeler.\r\nSince Feb&rsquo;19: NTT Data, Bangalore as Software Development Senior Specialist.\r\nSince Mar&rsquo;06: Accenture, Bangalore as System Analyst/Team Lead.\r\nKey Result Areas:\r\nWorking on Spotfire/Tableau/SSRS/PowerBI and MySQL/Oracle/HANA, designing, developing, testing &amp;amp; maintaining Tableau Dashboard, functional reports based on user requirements, deploying rich graphic visualizations with drill down &amp;amp;drop-down menu option based on parameters using Tableau.\r\nPerforming advance analysis actions, calculations, parameters, background images, maps, trend lines, statistics and table calculations also managing multiple POC for clients for various applications and projects\r\nImplementing Data modeling (Dimensional &amp;amp; Relational) concepts like Star-Schema Modeling, Snowflake Schema Modeling, Fact and Dimension table normalization/de-normalization, data extraction, data cleansing &amp;amp; data manipulation.\r\nAdministering functions related to SAP BOBJ 3.1/4.0/4.1 &amp;amp; SAP HANA-gathering the business requirement also building Universes in the Designer &amp;amp; IDT from various sources of retrieving data\r\nSKILL SET\r\nData Modeling, Data Analytics and Reporting\r\nData Visualization\r\nTableau, Power BI, SSRS, SAP BOBJ\r\nSPOTFIRE, TDV, TDS\r\nSPARK, ERWIN, HIVE QL SQOOP(basics)\r\nSAP HANA Data Modeling \r\nCertified Scrum Master\r\nBusiness Intelligence\r\nProject &amp;amp; Product Management\r\nRequirements Gathering &amp;amp; Analysis\r\nService Delivery &amp;amp; Capacity Planning\r\nDisaster Recovery Mgmt.\r\nTeam Building &amp;amp; Leadership\r\nRisk, Incident &amp;amp; Change Mgmt.\r\nPower BI Tools-IDT,UDT &amp;amp; Design Studio of SAP BOBJ Suites\r\nData Base\r\nOracle 9i/10g, SQL Server, Sybase, DB Visualizer\r\nACADEMIC DETAILS\r\nMCA (Computer Application) \r\nBCA (Computer) \r\nPERSONAL DETAILS\r\nDate of Birth: 3rd December 1979\r\nLanguages Known: English &amp;amp; Hindi\r\nAddress: A207, Midtown Opulent Sorahunase Road, Varthur, Bangalore- 560087\r\nFacilitating functions such as scheduling &amp;amp; publication the reports also dealing with various databases like Oracle 9i/10g, SQL Server\r\nSteering activities as Single POC for Agile certification for projects and mentoring the team for agile practices at DU level\r\nSuggesting appropriate technology-based solutions for enhancing functional efficiency and achieving business excellence\r\nEstablishing &amp;amp; enforcing standard test processes / deliverables within the gated process for streamlining testing, support automation and manual testing efforts\r\nProviding technical leadership while estimating &amp;amp; evaluating the effort/ schedules \r\nBuilding &amp;amp; maintaining healthy business relations with clients/customers and ensuring high customer satisfaction matrices by achieving delivery &amp;amp; service quality norms\r\n     Projects Completed\r\nProject: Data &amp;amp; Analytics\r\nDuration: 1 year 2 months;      Client: Nexperia  \r\nTool: ERWIN, BigData, Spark, Spotfire, TDV, TDS, SAP S4/HANA, JIRA\r\nPosition: Data Modeler/Data Architect\r\nKey Result Areas:\r\nWorked as a key member of the Data &amp;amp; Analytics team in ideating, framing &amp;amp; implementing the Data Strategy of the organization.\r\nPioneered the development of the semantic data model that integrates organizational data into a singular Big Data Platform. It enables scalability by driving re-use and presenting a singular truth of data. \r\nHave been involved in data quality stability that involved all spheres of governance, data quality enhancements and data profiling.\r\nInvolved in Implementing the data platform using a hybrid Data Vault enabled progressive growth of the platform and helped achieve stability.\r\nSuccessfully implemented the data model for manufacturing unit like yield, PQE, LOH, MCT and etc along with R&amp;amp;D unit data model. Monitored E2E implementation. \r\nProject: HR &amp;amp; Learning Management System (HR Analytics)\r\nDuration: 2 year 2 months;       Client: Morgan Stanley\r\nTool: Tableau 10.5/SAP BO4.2, DB2,Sybase, JIRA\r\nPosition: Software Development Senior Specialist\r\nLead the Reporting Visualization Team (Involving Tableau/PowerBI/SSRS/SAP BOBJ) \r\nGathering reports requirement and collaborating with the business users\r\nDesigning Data Modeling &amp;amp; deploying rich graphic data visualizations with drill down and drop-down menu option based on parameters using Tableau.\r\nDeveloping Tableau Data Visualization using Cross Tabs, Heat Maps, Box, Whisker Charts, Scatter Plots, Geographic Map, Pie Charts, Bar Charts and Density Chart\r\nPerforming advance analysis actions, calculations, parameters, background images, maps, trend lines, statistics and table calculations.\r\nWorking as a SME for Tableau and IDT Universe Development.\r\nProjects: Proactive Stock Management (PSM), Real Estates Inventory System, NASA, STP, GOLDMINE and LOS\r\nDuration: 2 years 1 month        Client: Mondelez/AT&amp;amp;T\r\nTool: Erwin r7.1/Hive, Hadoop, Oracle11g\r\nPosition: Sr Data Modeler.\r\nGather all the Sales analysis report prototypes from the business analysts belonging to different Business units.\r\nReverse engineered the reports and identified the Data Elements (in the source systems), Dimensions, Facts and Measures required for new enhancements of reports\r\nConduct Design discussions and meetings to come out with the appropriate Data Mart at the lowest level of grain for each of the Dimensions involved\r\nDesigned a STAR schema for the detailed data marts and Plan data marts involving confirmed dimensions\r\nEnsured the feasibility of the logical and physical design models\r\nDeveloped Data mapping, Data Profiling and Data modeling including logical and physical model with ERWIN and Hive respectively.\r\nSuccessfully created Subject area, Notation, naming convention as per Business rules.\r\nOther Projects:\r\nProject: BPC Implementation \r\nDuration: 12 months;                 Client: Energy Queensland\r\nTool: BW4 HANA, SAP Lumira2.0, WEBI\r\nPosition: SAP Lumira Developer/BO Consultant\r\nProjects: NMIC, PMR, Billing Payment System, SHARP, Business Direct, AIMOS, Real Estates, Payroll, JOBS, Learning and Management System- CWAC &amp;amp; SORTS, MyWizard, PLE, Billing Payment System, NMIC Phase 3, Datahub &amp;amp; APLAUSE\r\nDuration: 9 years 10 months; Client: AT&amp;amp;T\r\nTool: SAP BOBJ4.1(WEBI, IDT, UDT),Crystal report 2008/2013, Mercury Quality Center, Oracle 11g, SAP BW 7.3, Bex Query &amp;amp; Rally\r\nPosition: SAP BO Developer/BO Consultant~ Maintained more than 700 BO reports for the SAP HR System\r\n\r\n\r\n\r\n', 2, 2, 1, 'Recruiter', 'Un-assigned', 'SL', 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-04-24 07:58:12', 0),
(336, 76, 63, NULL, NULL, '63_76_1147866586628bb944051b_Anuj_Jain_Data_Modeler.pdf', 'Anuj Jain_Data Modeler.pdf', 'Page 	1 of 	5 	\n 	\n 	 	\n        	 	\nAnuj Jain	                                                     	              	                	Mob:	    +9	1- 9987198538	 	\n                                                                      	                             	Emai	l:  eng.anujjain@gmail.com	 	 	\nProfessional Summary	 	\n  \n* 	Total 1	4 years 	of 	experience 	in Data Warehouse Projects with 	Telecom, 	Insurance	, Supply 	\nchain	 domain 	working 	with 	Organizations 	Infosys, MindT	ree	, Cognizant	, Mobily	. 	\n* 	Experience in	 Design, 	Data Modelling, Data Architecture	, Data Engineering.	 	\n* 	Involved in Requirement Gathering, Requirement Analysis, Customer Interaction, 	and Impact	 	\nAnalysis for new proposals and requirements from client	. 	\n* 	Experience in 	Data Modeling	 with 	Erwin	 Tool.	 	\n* 	Experience 	in working in 	Telecom domain 	in data warehouse environment	 	\n* 	Experience in managing 	business requirement till deployment as 	Scrum master. 	 	\n* 	Experience in working at client site, face client 	interaction	. 	\n* 	Ability to prioritize and perform broad range of respons	ibilities.	 	\n* 	Having Experience	 in ETL Testing, 	Database Testing	, automation	. 	\n* 	Good knowledge in the entire 	Software Development Life Cycle (SDLC)	 and Software 	\nTesting Life Cycle (STLC).	 	\n* 	Experie	nce in 	Azure Data Factory (ADF)	 development	.  	\n 	\nWORK EXPERIENCE	    	\n* 	Worked as Data 	Modeler 	Manager in 	Mobily Infotech	 from 	Nov,	 2020 to Apr	, 202	3. 	\n* 	Work	ed	 as 	an	 Associate Consultant in 	Cognizant (CTS)	 from 	April, 2014 to 	Oct	, 2020	.  	\n* 	Worked 	with 	Mindt	ree	 from 	June, 	2013 to March. 2014.	  	\n* 	Worked with 	Infosys	 from 	Jan, 2010 to May, 2013	.  	\nEducational Summary	    	\n* 	B. Tech. Computer Science	, Greater Noida Institute of Technology, Gr. Noida, U.P (June 200	9).  	\n* 	12	th, from 	(UP State Board), K. K. Inter College, M	eerut, U.P (June 2003	)  	\n* 	10	th, from 	(UP State Board), K. K. Inter College, Meerut, U.P (June 200	1).  	\nSkill Set Summary  	 	\nTechnology	 	Skills	 	\nDatabases	 	Teradata	 ,Oracle 10g	 , SQL Developer, Greenplum	, Snowflake	 	\nOperating Systems	 	WIN XP/2000/2003, UNIX	 	\nModel	ing Tool	 	Erwin Data Modeling	 	\nETL Tools	 	Abnitio	, Datastage, Informatica, 	ADF	, SSIS	 	\nLanguages	 	SQL, C, VB Script, Excel Macro(VBA)	 	\nFramework	 	Automation Framework(QTP) Data Warehouse	 Sys	tem	 	\n \n \nPROJECTS SUMMARY	    	\nPROJECT	 	CLIENT	 	DURATION	 	\nInfosys Training	 	- 	Jan 2010 	&ndash; June 2010	 	\nRetail Distribution of Investment	 	\nProducts, Infosys	 	\nCitigroup	 	June 2010 	&ndash; May 2013	 	\nAIG 	-Operational Data Source	 	AIG	 	June 2013 	&ndash; March 2014\n\nPage 	2 of 	5 	\n 	\n 	 	\n        	 	\n(ODS),  MindTree	 	 	\nReliance Jio Analytics, Cognizant	 	Reliance	 	April 2014 	&ndash; Oct 2015	 	\nSanofi Sa	les Analytics, Cognizant	 	Sanofi	 	Nov 2015 	&ndash; Feb 2016	 	\nSTC EDW Dev and Testing, Cognizant	 	STC	 	Feb 2016	- Oct	, 2020	 	\nTWC POM OEb	 &amp;Mobily Saudi	 	Mobily &amp; TWC	 	Dec	, 2020	- Apr	-202	3 	\n 	 	 	\n   DETAILS OF THE PROJECTS WORKED ON	 	\n01 	Project Name	  	:     	JNJ Sales Forecast	 	\n 	Client	 	\nDuration	 	\n:     	JNJ	 	\n:     	 	\n 	Role    	                    	:     	  Data Engineer and Data Modeler	 	\nResponsibilities:	 	\n \nDesign and Data Modelling	 	\n 	Creating the mapping and design for the data w	arehouse environment and maintain	ing the data 	\narchitecture of warehouse.	 	\n 	Managing the source communications for the data profiling, source structure understanding.	 	\n 	Generating data definition language (DDL) used to create the database schema.	 	\n 	Creating a mod	el to correspond to each environment.	 	\n 	Develop the logic in 	ADF	 and support Reporting Team for 	Developing Dashboard as per 	\nrequirement.	 	\n 	Lead and Guide team end to end from development 	for the 	ETL	 package.	 	\n 	Discussion with 	stake holder	 understand the requirem	ent and suggest the solution to achieve the 	\ngoal.	 	\n 	Understand the logic from 	business	 and document it with proper formula for technical 	\ndocumentation.	 	\n 	Managing the work to ensure the quality and timely delivery of product in agile environment.	 	\n 	Test Enginee	r 	\n 	Software/Tools	 	: 	ADF, ADBK, SQL Server	 	\n    02 	Project Name	  	:     	TWC POM OEE	 	\n 	Client	 	\nDuration	 	\n:     	TWC	 	\n:     	Dec	 2020	 to 	Apr	 202	3 	\n                           	Role    	                    	:     	 Data Modeler and	 ADF Data Engineer	. 	\nResponsibilities:	 	\n \nData Modelling	 &amp; Data Engineer	 	\n 	Creating the mapping and design for the 	TWC POM	 data warehouse environment and maintain	ing the data architecture of warehouse.	 	\n 	Managing the source communications for the data profiling, source structure understanding.	 	\n 	Underst	and the requirement from end user/ client and prepare the data model accordingly.	 	\n 	Generating data definition language (DDL) used to create the database schema.	 	\n 	Creating a model to correspond to each environment.\n\nPage 	3 of 	5 	\n 	\n 	 	\n        	 	\n 	Developing ADF Pipeline for	 POM Machine and 	for forecast	. 	\n 	\nSoftware/Tools	 	: 	ADF , Snowflake	, SQL Server	 	\n 03 	Project Name	  	:     	STC EDW Dev and	 DQ	 	\n 	Client	 	\nDuration	 	\n:     	Saudi Telecom Company	 	\n:     	Feb	 2016	 to 	Sep	, 2020	 	\n 	Role    	              	      	:     	  Designer/Data Modeler, Scrum Master	 	\nRes	ponsibilities:	 	\n \nDesign and Data Modelling	 	\n 	Creating the mapping and design for the Teradata CLDM data 	warehouse	 environment and 	\nmaintain	ing the data architecture of warehouse.	 	\n 	Managing the source communications for the data profiling, source structure under	standing.	 	\n 	Design mapping to fulfill the requirement and feasible technically.	 	\n 	Maintaining a model repository in Erwin environment	 	\n 	Generating data definition language (DDL) used to create the database 	schema.	 	\n 	Creating a model to correspond to each 	environme	nt.	 	\n 	Synchronizing models to ensure that database structures match models and Testing all DDL before \ndeployment	 	\n \nScrum Master	 	\n 	Lead and Guide team end to end from development to production deployment.	 	\n 	Managing the work to ensure the quality and timely delive	ry of product in agile environment.	 	\n 	Good understanding of Abinitio Graph.	 	\n 	Interact with client for the progress of the activity in Team bucket.	 	\n 	\n 	Test Engineer	 	\n 	Software/Tools	 	: 	Erwin, JIRA, 	Abinitio	, Data Stage	, Teradata	, JIRA, UNIX	, ADF	 	\n 	\n 03 	Project Na	me 	 	:     	Sanofi Sales Analytics	 	\n 	Client	 	\nDuration	 	\n:     	Sanofi	 India	 	\n:     	Nov2015 	to 	Feb 2016	 	\n 	Role    	              	      	:      	Developer	- Tester	 	\nResponsibilities:	 	\n 	Experience to work at client location	. 	\n 	Prepare the Test Strategy, Test Plan and RTM for	 DW/ETL testing and QlikView Report Testing	. 	\n 	Involved and helping out for ETL Architecture with Architect	. 	\n 	Develop the test script for ETL Testing and Report testing	. 	\n 	Update the client with testing Status and handle defect call	. 	\n 	Coordinate with the client,	 business analyst and development team during analysis and execution 	\nphase	. 	\n 	Update the client with the current status and suitable approach for future changing conditions	. 	\n 	Logging and tracking of the defects till closure and discuss with development team a	nd client in 	\ndefect call	. 	\n 	Test Engineer\n\nPage 	4 of 	5 	\n 	\n 	 	\n        	 	\n 	Software/Tools	 	: 	Quality Centre, Oracle SQL Developer, Informatica, 	QlikView	, Unix	 	\n 	\n 04 	Project Name 	 	:     	Reliance Jio Analytics	 	\n 	Client	 	\nDuration	 	\n:     	Reliance	 	\n:     	April	 2014	 to 	Nov 2015	 	\n 	Role 	            	     	      :      Associate 	&ndash; Project	 (Developer &amp; 	Sr Test Engineer)	 	\nResponsibilities:	 	\n 	Experience to work at client location	. 	\n 	Prepare the Test Plan and RTM for DW testing and BO Report Testing	. 	\n 	Prepare the test data for SIT phase	. 	\n 	Review and develop the te	st cases for testing	. 	\n 	Develop the test script for ETL Testing	 and BO Testing.	 	\n 	Update the client with testing Status and handle defect call	 	\n 	Coordinate with the client, business analyst and development team during analysis and execution \nphase	 	\n 	Update the clie	nt with the current status and suitable approach for future changing conditions	. 	\n 	Logging and tracking of the defects till closure and discuss with development team and client in \ndefect call	. 	\n Involved in following environments of testing:	 	\no 	SIT 	- (Engineered 	Data)	 	\no 	UAT 	&ndash; (Business Data)	 	\n 	Validate SAP	-BO Report, Spotfire Report	.  	\n 	Test Engineer	 	\n 	Software/Tools	 	: 	Quality Centre, Oracle SQL Developer, GreenPlum, Informatica, BO Report, \nUnix, Spotfire	, Hive	 	\n 05 	Project Name	 	:    	AIG	-TCOE	 	\n 	Client	 	\nDuration	 	\n:    AIG	 	\n:    June 2013 to March 2014	 	\n 	Description of the project 	 	\n 	           	This project has details of insurance clients of AIG. There are different data 	\nWarehouse according to region specific. The current system is to merge them into a \nsingle warehouse syst	em to facilitate the system as a centralize system and to 	\nfacilitate the regulatory body.	 	\nRole 	                       	:      	Senior Test Engineer	 	\nResponsibilities:	 	\n 	Involved in streamlining the Automation testing process. 	 	\n 	Involved in Test Planning and Test	 Case preparation activity.	 	\n 	Involved in finding out the appropriate approach for the testing keeping the future requirements in \nmind.	 	\n 	Identifying the approach for Automation Testing. 	 	\n 	Developed the automation QTP script for testing.	 	\n 	Developed Macro	-tool fo	r the status dashboard.	 	\n 	Developed Macro	-Test Data Generation Tool to generate data for the ETL testing. 	 	\n 	Involved in training activities related to Automation and ETL.	 	\n 	Involved in managing project artifacts.\n\nPage 	5 of 	5 	\n 	\n 	 	\n        	 	\n 	Software/Tools	 	: 	HP Quality C	entre, Oracle SQL	 Developer	, QTP 	, Data Stage	 	\n \n06 	Project Name	  	:     	Retail Distribution of Investment Products	 	\n 	Client	 	\nDuration	 	\n:     	Citigroup Inc	 	\n:     June 2010 to 	June	 201	3 	\n 	Description of the project	 	\n 	         	RDIP is a board	-mandated, global initiative to revie	w and address the risks in the distribution of 	\ninvestment products to retail investors across Citi. 	 	\nProduct Rating System	. One of the high	-impact changes associated with RDIP is consistent product 	\nrating. The same product will carry the same rating across	 regions. All Standard and Non Standard products 	\nwill be assigned a rating on a scale of 1	-6. 	\nData Acquisition	. To mitigate the risk associated with the distribution of retail investment products, IPR 	\ndefined need for DA to provide consistent global survei	llance of suitability mismatches and inconsistent 	\nproduct ratings. Acquired data across the globe and pearl system will be loaded into IPR DW with the data \npopulated by &ldquo;Rules Engine&rdquo; will provide consistent global surveillance of suitability and inconsist	ent 	\nproduct ratings. 	 	\nRole 	                       	:  Test Engineer	 	\nResponsibilities:	 	\n 	Expert in automation in the project and was responsible to manage the responsibilities under \nautomation for RDIP	 	\n 	Involved in scope of automation and identifying the test c	ases for automation	 	\n 	Prepare the framework of Automation for 2 modules in the project	 	\n 	Involved in developing and debugging the script for automation	  	\n 	Worked on Data Warehouse testing and Automation module	. 	\n 	Involved in following types of testing:	 	\no 	Data Wareho	use (ETL) Testing	 	\no 	Regression Testing	 	\no 	Automation Testing (QTP)	 	\no 	Functional Testing.	 	\n Expertise in Data Warehouse testing 	&ndash;verifying all the tables in the stage and target environments.	 	\n Experience in verifying and loading the data.	 	\n Input files (text, excel and	 *.dat files) preparation for DWH.	 	\n 	Performed test case preparation and execution	. 	\nPersonal Details 	 	\nNAME	 	\nDOB	 	\n: \n: 	\nAnuj Jain	 	\n21	-02	-1987	 	\nEMAIL ID	 	: 	eng.anujjain@gmail.com	 	\nMARITAL STATUS	 	: 	Married	 	\nNATIONALITY	 	\nLANGUAGES KNOWN       	 	\n: \n: 	\nIndian	 	\nEnglish, Hindi	 	\n \nDeclaration	  	\nHereby  I  declare  that  the  information  furnished  above  is  true  to  the  best  of  my  knowledge  and \nbelief.	 	\n 	 	 	 	 	 	 	  	                                	Anuj Jain  	 	\nDate:', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-04-24 07:58:12', 0),
(337, 76, 63, 30, NULL, '63_76_14331089286628bb94416dd_ChintanShah.docx', 'ChintanShah.docx', '\nChintan Shah\r\ntechiechintan@gmail.com / LinkedIn / +91-9930701107\r\n422275172414\r\nSummary\r\nAWS Certified Solutions Architect (Associate) with an experience of 8+ years working on DWH/ETL and BI solutions for multiple internal and external clients across various sub-domains like Cloud Operations, Commercial Pharma and R&amp;amp;D (Clinical Trials). Demonstrated history and experience in leading small-medium teams for technology delivery &amp;amp; operations projects.\r\n431800180559\r\nExperience\r\nSenior Data Engineer\r\nTIBCO Software &bull; PUNE, MAHARASHTRA\r\nPlatform Ops Initiatives (May 2021 &ndash; Present) :\r\nAs a Data Engineer, mainly responsible for designing, building and maintaining cloud-based integration data pipelines &amp;amp; reports\r\nConsolidated disparate data sources (Jira/JSD, AWS costs, Azure costs, OpsGenie alerts) into a unified Redshift DW, by leveraging Lambda (Python), SQS and IaC (Terraform, Serverless)\r\nImplemented Python-based solution (synthetic monitoring) to regularly track availability &amp;amp; latency indicators of REST-based endpoints and product web page performance (Selenium-based)\r\nBuilt &amp;amp; maintained Spotfire dashboards based on the above data - to monitor trends, engage stakeholders &amp;amp; optimise cloud costs\r\nWorked on integration (Jira, Slack &amp;amp; XRay), issue triaging and production migration, for rollout of a new release management tool\r\nBusiness Technology Consultant\r\nZS Associates &bull; PUNE, MAHARASHTRA\r\nR&amp;amp;D Clinical Data Ops (Apr 2019 &ndash; Feb 2021) :\r\nLed the Offshore team for a Fortune-500 pharma company wherein the responsibilities included end-to-end management and communication for data ingestion, data standardisation and data publishing activities across 3 clinical applications\r\nInteracted with different client stakeholders to plan and implement multiple enhancements &amp;amp; optimisations, which led to &amp;gt;50% reduction in manual efforts and delivery turnaround time across couple of applications\r\nAlso accountable for ensuring right access controls and governance processes are in place across the clinical applications, by performing regular usage reporting and auditing\r\nWorked with different vendors/infra support teams for issue resolution/management and UAT support\r\nResponsible for onboarding and mentoring new members in the team Commercial DW &amp;amp; BI solution (Feb 2016 &ndash; Mar 2019) :\r\nResponsible for requirement gathering, data modelling, estimation/planning, development &amp;amp; deployment of multiple DW releases for EU region of a Fortune-500 pharma company, utilising AWS Redshift/RDS for MSTR analytical dashboards\r\nComparing the outcomes/metrics from the new releases with legacy solution, analysing the gaps encountered during the process and working with the clients to gain alignment on the justifications/reconciliations\r\nBuilt a Training DB solution, which comprised of pseudonymised data and corresponding dashboards for onboarding new users CRM Solution Enhancement Release (Sep 2015 &ndash; Jan 2016) :\r\nResponsible for building and testing process flows in Dell Boomi to automate data extraction from Salesforce (Veeva CRM) and placing the extracts on client&rsquo;s SFTP location\r\nUtilised Informatica for creating ETL flows to fetch data from flat files, apply transformations and load them into Oracle tables\r\nFor all the above processes, ensured that relevant quality checks are in place to validate source data sanity\r\nOverall, I am a self-motivated and well-organised IT professional, with strong written &amp;amp; verbal communication skills along with proven ability to work as a team player. Additionally, I am willing to travel/relocate based on job opportunities &ndash; I have previously travelled to Germany for a release demo &amp;amp; subsequent UAT support at client location and also possess an active US B1/B2 Visa.\r\n\r\nSkills\r\nDB/DW and ETL Technologies : AWS Lambda, AWS Redshift, AWS RDS (PostgreSQL, MySQL), AWS SQS, AWS S3, Tibco Scribe, Paxata, SnapLogic, Informatica, Salesforce Veeva (SOQL)\r\nScripting Technologies : Python, Selenium, Jupyter notebooks, Unix/Shell, Java\r\nBI Technologies : Spotfire, Tableau, MicroStrategy\r\nData Modeling/Design : Erwin Data Modeler, Visio\r\nProject Infra/ Management Tools : Jira, Git, Terraform, Serverless, ServiceNow, Aha, SharePoint, SVN, HP ALM\r\n431800163103\r\nCertifications, Awards &amp;amp; Publications\r\nCareer Essentials in Generative AI by Microsoft and LinkedIn &ndash; Jul 2023\r\nAWS Partner: Accreditation (Technical) &ndash; Apr 2023\r\nAWS Partner: Cloud Economics Accreditation &ndash; Apr 2023\r\nTCA-TIBCO Spotfire&reg; &ndash; Dec 2021\r\nAWS Certified Solutions Architect (Associate) &ndash; Mar 2021\r\nData Management for Clinical Research (Coursera) &ndash; Nov 2020\r\nDesign and Interpretation of Clinical Trials (Coursera) &ndash; Aug 2020\r\n&ldquo;Leader in the making&rdquo; Award (ZS-client initiative) &ndash; Jul 2020\r\nA Crash Course in Data Science (Coursera) &ndash; Jun 2020\r\nAnalysis and detection of eventful messages in IMs (published in IEEE) &ndash; Oct 2016\r\n355600192779\r\nEducation\r\nB.E. (Information Technology) &ndash; 75.27%\r\nD. J. Sanghvi College of Engineering &bull; MUMBAI\r\n2011 &ndash; 2015\r\nHSC (12th Science) &ndash; 92.5%\r\nT. P. Bhatia College of Science &bull; MUMBAI\r\n2009 &ndash; 2011\r\nCBSE (10th) &ndash; 93.2%\r\nRam Ratna Vidya Mandir &bull; MUMBAI\r\n2007 &ndash; 2009\r\n422275206245\r\nMiscellaneous\r\nLanguages Known : English, Hindi, Gujarati\r\nCurrent Place of Residence : Pune\r\nDate of Birth : 04 Sep 1993\r\n422275665044Hobbies : Travelling/Exploring new places, Listening music &amp;amp; podcasts, Playing basketball and cricket\r\n', 2, 2, 1, 'Recruiter', 'Assigned', 'SL', 1, 'N', 14, '2024-04-24 08:33:01', NULL, '2024-04-30 08:33:01', 0, NULL, '2024-04-24 07:58:12', 0),
(338, 76, 63, NULL, NULL, '63_76_309338336628bb9441d71_Pushpender_Sharma_Data_Modeler_(1).pdf', 'Pushpender Sharma_Data Modeler (1).pdf', 'Pushpender Sharma	 	\n \nCurrent Company 	&ndash; TCS, Pune	 	\nPhone 	- +91	-74476	-50079	 	\nEmail 	- Pushp_Sharma10@yahoo.com	  	\n \nAn  aspiring 	Data 	Vault  data	 Modeler  and 	Cognos  BI	 developer	 offering 	11 	years  of  rich  and  comprehensive  experience	 with  a 	\ndemonstrated	 track record of delivering results 	in a highly	 competitive environment. 	 	\n \nQUALIFICATIONS/CREDENTIALS 	 	\n \n❖ 	B. TECH	 in Electronics and 	\nCommunication	 from PTU 	 	\n 	\n❖ 	10th from 	Shri Guru 	\nHarkrishan Public School	, 	\nPathankot	 	\n 	\n❖ 	12th from 	MDK Arya Senior 	\nSecondary School, \nPathankot	 	\n \n \n 	\n \n 	\nCAREER HIGHLIGHTS 	 	\n 	\n❖ Well  Versed  with  various  OLAP  Tools  such 	as Cognos 	analytics 	and  Cognos	 	\nAdministration,	 Cognos Report Studio, Framework manager	. 	\n❖ Proficient in creating 	Physical, logical	 and conceptual data model depending on the 	\nbusiness requirements.	 	\n❖ Strong  knowledge  on 	setting  up  Single  server  and  distributed  server  Cognos 	\nenvironments at Legacy and Cloud Environments.	 	\n❖ Defined  and  governed  data  modeling  and  design  standards,  tools,  bes	t  practices, 	\nand related development for enterprise data models	. 	\n❖  Extensive  experience  in  converting  CQM  to DQM  packages,  identifying  and  fixing \nbugs during migration from one data source to another.	 	\n❖ Good  knowledge  about  Database  Designing  Administration,  Advanced  Data \nModeling for Star Schema design	 	\n❖ Implementation  expe	rience  with  web  servers  and  working  knowledge  of 	\nauthentication 	providers like Open ID, AD, 	Okta, Pingone	 	\n❖ Experience in migration on	-Prem Cognos to Google cloud environment.	 	\n❖  Extensive  experience  with  Cognos  administration,  LDAP  configuration  and  Single \nsign on experience	 	\n❖ Good Knowledge in 	Managing Cognos user security groups and roles	 	\n❖ Installation, Upgrade, maintenance and support of all Cognos Analytics components	 	\n❖ Experience  in  Data  vault  2.0  data  modeling  for  loading  all  the  enterprise  data  in \nsingle Ent	erprise data warehouse through ETL loads.	 	\n❖ Involved  in  various  projects  related  to	 Data  Modeling,  System/Data  Analysis, 	\nDesign and Development for both OLTP and Data warehousing environments.	 	\n❖  Good exposure on working with cloud database like Google Big 	query .	 	\n❖ Worked extensively 	end to end on migrating Cognos environments from on premise 	\nenvironments to cloud environments	. 	\n❖  Overall  exposure  on  data  server  connections, maintainence,  fix  packs 	, setting  up 	\nsecurity groups on Cognos environments.	 	\n 	\n \n 	\nData Modeling tools	 	Erwin, Oracle SQL developer	 	\nDatabases	 	Oracle 10g, SQL, SQL developer	, Big Query, Teradata	 	\nAnalytic Tools	 	Erwin, C	ognos Analytics, Cognos 10	 	\nETL Tools	 	Informatica	 12x Power center	 	\n 	\nOperating Systems	 	Windows server 2008,2012, Linux	 	\n 	 	 \n \n \n \n \n \nWork Experience 	 	\n \nTata Consultancy Services	                                         	                	May 2020 	&ndash; Present\n\nDesignation: Consultant	 	\nTeam Size: 9	 	\nRole:  Data Modeler and Cognos Admin	 	\n \n \nCommunity Health Services (HealthCare)	 	\n \nCommunity Health Systems, Inc. is one of 	United States	&rsquo; leading operators of general acute care hospitals. The organization&rsquo;s 	\naffiliates own, operate or lease 89 hospitals in 16 states with approximately 15,000 licensed beds. Affiliated hospitals prov	ide 	\nquality healthcare for 	residents	 and contribute to the e	conomic development of their communities. Based on the unique needs 	\nof each community served, these hospitals offer a wide range of diagnostic, medical and surgical services in inpatient and \noutpatient settings.	 	\n \nResponsibilit	ies 	 	\n 	\n❖ Migration and maintenanc	e of Cognos Analytics from On Prem to Google cloud Planform 	 	\n❖ Installation and configuration with AD authentication 	with GCP for better performance 	 	\n❖ Enabling Single Sign on and creating user security groups and providing necessary privileges to the 	users.	 	\n❖ Data Analysis and creating OLTP and OLAP data models based on the client requirements	 	\n❖ Involved in various projects related 	to Data Modeling, System/Data Analysis, Design and Development for both 	\nOLTP and Data warehousing environments	 	\n❖ Preparing Physical and Logical Models 	and 	enabling team mates to 	understand 	Data modeling	 (Dimensional &amp; 	\nRelational)	 concepts like Star	-Schema Modeling, Snowflake Schema Modeling, Fact and Dimension tables.	 	\n❖ Created, documented and maintained logical and ph	ysical database models in compliance with enterprise 	\nstandards and maintained corporate metadata definitions for enterprise 	data	stores within a metadata repository.	 	\n❖ Analyzed database requirements in detail with the project stakeholders by conducting Joint 	Requirements 	\nDevelopment sessions	 	\n❖ Developed a	 Conceptual model	 using Erwin based on requirements analysis	 	\n❖ Developed normalized	 Logical	 and	 Physical	 database models to design OLTP system for insurance applications	 	\n❖ Created dimensional model for the 	reporting system by identifying required dimensions and facts using	 Erwin 	 	\n❖ Used forward engineering to create a Physical Data Model with	 DDL	 that best suits the requirements from the 	\nLogical Data Model	 	\n❖ Worked with Database Administrators, Business Analysts	 and Content Developers to conduct design reviews and 	\nvalidate the developed models	 	\n❖ Identified, formulated and documented detailed business rules and Use Cases based on requirements analysis	 	\n \n \n \n \n \n \n \n \n \n \n \n \n \n \nInfosys Ltd.	  	    	 	 	                                        	From Jan 2015 	&ndash; Apr 2020	 	\n \nDesignation: Technology Analyst	 	\nTeam Size: 3	 	\nRole: 	 Data Modeler and Designer\n\nHillenbrand Batesville Inc.	 	\n \nHillenbrand is a global diversified industrial company with multiple leading brands that serve a wide variety of industries 	 	\naround the world. Hillenbrand&rsquo;s portfolio consists of two business segments:  Process Equipment Group and Batesville	.      	\nBatesvil	le is a recognized leader in the death care industry in North America through the manufacturing and sale of funeral 	\nservices products, including burial caskets, cremation products, selection room display fixturing and technology solutions fo	r 	\nfuneral homes	 	\n \nResponsibilities 	 	\n 	\n❖ Understanding the business requirement in CAB meeting with clients and Extracting data from ERP systems to \ncreate data definition that modifies the metadata into meaningful data.	 	\n❖ Loading analyzed and Extracted data into the 	Staging area and creating Hash Keys to be used in Hub, link and 	\nSatellite tables	 	\n❖ Installation, Upgrade, maintenance and support of all Cognos Analytics components	 	\n❖ Respond to and resolve tickets on technical issues related to Cognos Analytics within defined	 SLAs	 	\n❖ Co-ordinate with IBM Support for any issues related to Cognos Analytics tools	 	\n❖ Responsible for monitoring, reporting, and controlling server usage	 	\n❖ Creation and maintenance of system documentation related to the Cognos Analytics environment	 	\n❖ Deep level 	troubleshooting including RCA	 	\n❖ Communicate status of production issues to stakeholders in a timely manner	 	\n❖ Identify problems in advance and look for continuous service improvements	 	\n❖ Participate in problem management and come up with trend analysis on recurrin	g incidents	 	\n❖ Partner with the DBA, Systems, Networking, and Product teams to facilitate issue resolution	 	\n❖ Identifying Hub, Links and Satellites from the data definition created from JD Edwards and Other customized \nsystems according to data vault 2.0 methodol	ogy.	 	\n❖ Loading analyzed and Extracted data into the Staging area and creating Hash Keys to be used in Hub, link and \nSatellite tables	 	\n❖ Creating mappings for JDE to Stage, Stage to Data Vault (Hub, Link and Satellite loaders) and Data Vault to EDW \nand set up bu	siness logic.	 	\n❖ Creating and validating test scripts to validate the data of JDE with staging, Data Vault and EDW to make all the \ndata is loaded correctly with no loopholes.	 	\n \n 	\n 	\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 	 	\nAtos 	Syntel Ltd.	 	 	    	 	 	                                            	From Nov 2011 	&ndash; Dec 2014	 	\n \nDesignation: Software Developer	 	\nTeam Size: 5	 	\nRole: Reports Developer\n\nBARCLAYS BANK	 	\n 	\nBarclays	 is a British	 multin	ational	 banking and	 financial services	 company headquartered in London. It is a	 bank with 	\noperations in retail, wholesa	le and investment banking, as well as wealth management, mortgage lending and credit cards. 	\nIt has operations in over 50 countries and territories and has around 48	 million customers. Barclays is organized into four 	\ncore business: Personal &amp; Corporate (Per	sonal Banking, Corporate Banking, and Wealth &amp; Investment Management), 	\nBarclaycard, Investment Banking and Africa.	 	\n \nResponsibilities	 	\n 	\n 	\n❖ Strong skills developing DMR models in Framework Manager and dimensional reports in Report Studio 	 	\n❖ Strong understanding of designing dimensional and relational models, star and snowflake schemas and different \nDW design paradigms.	 	\n❖ Good knowledge in building	 Active reports, static reports using conditional grouping and drill through	 	\n❖ Identifying facts and dimensions from the source system and business requirements to be used for the data \nwarehouse.	 	\n❖ Developing reports in BIRT using dimensional and relational mo	dels.    	 	\n❖  Using SQL server and Oracle database for data analysis and query optimization	 	\n \n 	\n 	\n \n \nPERSONAL PROFILE	 	\n 	\n▪ 	Date of Birth 	 	 	 	: 	13th September	 1988	 	\n▪ 	Nationality                    	 	 	: 	Indian	 	\n▪ 	Marital Status	 	 	 	:         	 	Married	 	\n▪ 	Languages known          	 	 	: 	English, Hindi, Punjabi, Japanese	 	\n▪ 	Passport                                                   	  :                 	J7780550	 	\n \nI hereby declare that all the above 	are	 true and correct to the best of my knowledge and belief.	 	\n 	 	 	 	 	 	 	 	 	(Pushpender Sharma)', 2, 2, 1, 'Recruiter', 'Un-assigned', 'SL', 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-04-24 07:58:12', 0),
(339, 77, 63, 31, NULL, '63_77_10811296116628f5d32fc89_YashasweeSinghTomar.docx', 'YashasweeSinghTomar.docx', '﻿Yashaswee Singh Tomar\r\nArchitect \r\nLocation: Pune Phone: +91 8380072723, Email: yashasweesingh@gmail.com                                                                           Immediate Joiner\r\nOverview\r\nQuantitative Management Leader with over 12 years of broad experience in Data Modelling, Data Engineering, Business Intelligence and Big Data Analysis.\r\nExperience in modelling Operations/Business problems into mathematical models and solving them.\r\nExperience in providing the right infrastructure for customers.\r\nBusiness Intelligence expertise\r\nAdmin Experience     \r\nUser Tracking for Embedded Power BI reports\r\nCreated Log analytics workspace and enabled Microsoft insights provider.\r\nUsing the Log Analytics workspace, generated information related to Tennat Summary, Workspace Summary, Engine Activities, Dataset Refresh, User Activities and Error Summary.\r\nTracked user information who are accessing reports, in terms of UserId, Client IP, Workspace Name, Dataset Name, and Timestamp.\r\nPower BI Audit Logs in admin portal, by Microsoft 365 Admin Center.\r\nUsed Audit logs to search for user activity by Dates, Files and Activities.\r\nManaged on premise Gateways for refreshes and data transfers.\r\nCreated deployment pipelines to push reports from Dev-&amp;gt;Pre-Prod-&amp;gt;Prod environment.\r\nInformed business users about licenses, which they can use like Pro, PPU and the cost involved.\r\nCreated workspaces in Dev and Prod environment and assigned premium capacity.\r\nCreated Azure AD groups for user specific access to different workspace.\r\nDevelopment Experience     \r\nDesigned Strategy, Roadmap, Enablement Strategy for various customers, including various fortune 100 Companies.\r\nAlways aim to assist Business Users to make quick and better decisions.\r\nDeveloped Data Marts schemas for multiple business divisions.\r\nReverse engineered application specific name-value pair database into a query friendly normalised data model to support reporting.\r\nPerformed enterprise strategic BI DW Assessment and identified the gaps.\r\nCreated Paginated report Using SSRS and Report builder.\r\nPrepared Synapse Data warehouse and migrated to Synapse.\r\nCreated User commentary using Power apps.\r\nAD groups added to Power apps for users.\r\nUsed Direct query to refresh the data instantaneously using snowflake having Power-app License.\r\nPower bi reports created for Manage accounts and revenue business.\r\nUsed Rest API for Embedded Power BI reports and manage its content.\r\nLed, designed, and implemented data extract processes to derive measurable metrics.\r\nMentored teams in designing and developing multiple system enhancements.\r\nAnalytics expertise\r\nCreated predictive models using Python.\r\nCompared data for previous demands, current demands and forecasting.\r\nCreated Regression models, conjoint analysis in Python.\r\nWorking experience in Azure &amp;amp; AWS cloud.\r\nWorking experience on Synapse real time analytics .\r\nStatistical concepts: Linear Regression (Simple &amp;amp; Multiple), Logistic Regression, Conjoint Analysis, SVM, Bootstrapping, cross validation, Subset Selection (Beat, forward, backward &amp;amp; hybrid), Shrinkage (Ridge &amp;amp; Lasso), Non-Linear (piecewise function), Decision Tree (Bagging &amp;amp; Boosting).\r\nFamiliar with Static and dynamic graphs in Deep Learning and its relevant application for scenarios.\r\nData Engineering expertise\r\nCreated Snowflake schemas, data models and dynamic data masking in Snowflake.\r\nExperience in SSIS, Talend, Azure Data Factory, Azure Analysis Service.\r\nCreated SSIS packages and supported system and acceptance testing.\r\nTuned ETL stored procedures, triggers, and user defined functions. Designed and developed DTS packages and enhanced OLAP cubes using SSAS.\r\nWorked on Synapse Data science from problem formulation to insights.\r\nCreated data process, integration and scheduling using Azure Databricks and ADF.\r\nDesigned various ETL jobs from ingestion, processing to object structures in Data Warehouse.\r\nWarehouse design and transformation for Enterprise Machine Learning.\r\nHandled big data using Mongo db, and created real time data streaming for reporting.\r\nMigration expertise\r\nBusiness Intelligence\r\nStrategized, planned, and spearheaded Migrations\r\nOBIEE  Power BI, SAP BO/Crystal Reports  Power BI,\r\nTableau  Power BI, OBIEE  Qlik, OAC  Power BI, Qlik  Power BI\r\nData\r\nStrategized, planned Migrations\r\nDB2  Snowflake, SQL DWH  Snowflake, Redshift  Synapse, Teradata  Snowflake, \r\nTeradata  Synapse\r\nETL\r\nStrategized, planned Migrations\r\nSSIS  Informatica, SSIS  ADF, Talend  Informatica\r\nTechnical Skills \r\nReporting/BI Tools:&nbsp;Power BI, Tableau, Report Builder, Familarity in Qlik sense, Spotfire\r\nProgramming languages:&nbsp;Python, Matplotlib, Pandas, Numpy, SQL\r\nData Processing:&nbsp;Databricks, Azure Data Factory, SSIS, Alteryx\r\nBig Data and AI:&nbsp;Q and A,NLQ,NLP, Hadoop\r\nCloud services:&nbsp;Azure, Snowflake\r\nDatabases:&nbsp;  Oracle, DB2,Sqlserver, Azure Synapse, Snowflake, Mongo DB\r\nAnalytical Tools- SPSS, Google Analytics\r\nEducation\r\nUniversity Degrees\r\nMBA: Operations &amp;amp; Business Analytics (IMT Nagpur)\r\nBE: Electronics (Medicap&rsquo;s University, Indore)\r\nGraded Certifications\r\nCertificate: PL-300 (Microsoft)\r\nCertificate: Tableau Desktop (Salesforce)\r\nIndustries worked for\r\nProjects: Banking, Retail, Insurance, Finance, Energy,\r\nCore Analytics &amp;amp; BI Work Experience (2010 &ndash; Present)\r\nArchitect &ndash; Business Analytics\r\nLTIMindtree-Bny Mellon    (Oct 2021 &ndash; present)\r\nProject- Handled the Managed Account of business for BNY Mellon. Managed account of business, assets, revenue, partners, and YOY revenue were some of the important parameters.\r\nCreated semantic layers, which acted as source for Business Unit.\r\nWorked on Microsoft fabric from Analytics, Data Science and Power BI.\r\nCreated deployment pipelines and version control using github for reports.\r\nResponsible for activities for Business Analytics; includes POC, estimates, strategy.\r\nUsed Git hub for version control and documentation on Confluence.\r\nDesigned various schemas including Star and Snowflake.\r\nIntegrated the data and ETL using Azure Data Factory\r\nDesigned Analytical Reports for Customers in various business divisions.\r\nCreated ETL processes, triggers, and user defined functions. \r\nReverse engineered from Business Requirement to User Friendly Reports to Data Model to ETL requirements, which made Business Users benefit the most of it.\r\nPerformed enterprise strategic BI DW Assessment and identified the gaps.\r\nPrepared Enterprise BI DW roadmap based on the findings from the assessment process.\r\nWorked on various projects at an Architect Consultant capacity.\r\nArchitect&ndash; Analytics &amp;amp; BI\r\niLink Systems UAE - Banking Domain (Jan 2021&ndash; Oct 2021)\r\nProject- Main scope of the project was to migrate from SAP to Power BI. Financial reporting, Transaction reports, agreement based- Murabaha agreement were created. Hybrid Architecture was created for the migration. Reports were also created in Arabic\r\nDesigned BI Solutions and identified KPI and KGI for the Client.\r\nWorked on multiple RFPs and Proposals.\r\nCreated hybrid architecture for migration from SAP BO to Power BI, which included Semantics layers, licensing, load balancing, Capacity Management, and security.\r\nCreated Paginated and Power BI reports, implemented What if scenarios and forecasting.\r\nTeam Lead &ndash; BI Solutions\r\nAltice USA- Telecomm (July 2018 &ndash; Dec 2020)\r\n\r\nPredictive Analytics - Planned and projected Skillset requirements and SLA adherence for all new projects.\r\nDesigned workflows in Alteryx.\r\nUsed Google analytics used for measuring customer trends and preferences.\r\nProvided strategy, Roadmap for Data infrastructure.\r\nProvided various Dashboards for Operations, HR, and the Executive Board\r\nProvided various Insights for the clients which included Cash flow prediction, Claims Intelligence etc within the Altice Operations domain.\r\nUsed high assurance session for salesforce, also connected Tableau to Power BI Datasets.\r\nRecovered projects worth $1.1 million in red and transpired them into BAU.\r\nManager &ndash; SPG &amp;amp; BI\r\nWestern Union- Financial Services (July 2017 &ndash; July 2018)\r\nExamine cash flow and financial statements, generate summary reports, monitor rate changes, develop financial models, and complete forecasting reports for financial projects.\r\nDesigned and Managed PMS for the whole Organisation. Instrumental in redefining the JD for all incoming employees for the entire company spanning 3 geographic locations.\r\nApart from the regular reports on AP, AR, and GL, we provided various Dashboards for the Organisational Operations, ROI, and balance Sheet ratios.\r\nGathered Business Requirements by interacting with Contract Owners and SMEs.\r\nDefined best practices for Tableau &amp;amp; Power BI report development.\r\nSenior Consultant &ndash; Analytics &amp;amp; BI solutions\r\nAllState- Insurance (July 2016 &ndash; June 2017)\r\nAnalyst &ndash; Operations &amp;amp; BI\r\nSears Holding- Retail (April 2014 &ndash; July 2016)\r\nSystem Engineer &ndash; MIS\r\nTCS- Credit Susisse (March 2010 &ndash; June 2012)\r\n\r\n\r\n\r\n', 2, 2, 1, 'Recruiter', 'Assigned', 'SL', 1, 'N', 14, '2024-04-24 16:53:40', NULL, '2024-04-27 16:53:40', 0, NULL, '2024-04-24 12:06:43', 0);
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(340, 78, 63, NULL, NULL, '63_78_6494391176628fc1407135_Prafulla-_Spotfire_BI_Architect.pdf', 'Prafulla- Spotfire BI Architect.pdf', 'Prafulla Kharwadey	 &ndash; Spot 	fire BI 	architect	             	          	          	  	\n 	\n 	 	\n \nProfessional Summary	:  	 	 	 	 	 	 	\n \n&bull; 	Lead/Architect/Management experience for handling various customer projects.	 	\n&bull; 	12 yrs 	Working 	knowledge of 	Spotfire	/ PowerBI / Tableau / 	Google cloud / 	AWS 	 	\n&bull; 	Working  knowledge  of  data  science  concept  including  linear/log  regression,  multivariate  linear  regression \nusing r and TERR. 	 	\n&bull; 	ETL tools like SSIS. 	 	\n&bull; 	10	+ years  of 	IT 	experience  in	cluding	 Architecture	, Technical  Leadership	, Software 	programming  and 	\nDevelopment	, Migration	 and 	Support using	 Microsoft 	technologies. 	 	\n&bull; 	Expertise  in  web  applications  using 	ASP.NET	, C#	, VB.NET	, JavaScript	, JQuery, 	Web	-Services	,  WCF	 and 	\nDesign Patterns.	 Expert in MS SQL Database design, architecture, programming	 	\n&bull; 	Full  life	-cycle  development  experience  including  design,  development,  testing,  documentation,  on	-site 	\nimplementation and user training. 	 	\n&bull; 	Significant exposure to 	Agile Methodology	, Scrum,	 Proposal and Estimation 	processes.	 	\n&bull; 	Good 	project	 leadership skills and invariably meets client expectations	. 	\n&bull; 	Excellent written and verbal communication skills.	 	\n&bull; 	Domains experience in 	Manufacturing / Retail / Supply chain management / Finance	 / Service	 /Logistic	  	\n&bull; 	Got UK Excellence Award from FUJITSU, UK	 	\n&bull; 	Technical write up via blog	ging 	 (www.sqlwebmentor.blogspot.com	, www.mydotnetcoding.blogspot.com	, 	\nwww.qlikviewmentor.blogspot.com	). 	Got Editor Choice award by 	www.dotnetspider.com	 	\n&bull; 	Valid work permission H1B, USA	 	\nSkills Summary	: 	\n \nCategory	 	Major Skills 	&ndash; Primary	 	Minor Skills 	&ndash; 	\nSecondary	 	\nDomains	 	Manufacture, Retail, Supply chain Management, \nFinance [Share],	 Localization	 	 	\nBI/Analytics Technology	 	Power BI	, Tableau	, Spotfire	, TIBCO Spotfire Server 	\nAdministration	, TIBCO Spotfire Automation	, 	\nCustomization programming	, Qlikview, SSIS	,SSRS	 	\nJSVIZ, 	D3 Charts	 	\nProgramming Skills	 	\n 	\nAngularJS, ReactJS, 	python, 	SSIS	, Dot Net 1.1, 	\n2.0,3.5, C#, VB.NET, ASP.NET, ASP, JavaScript, 	MS 	\nSQL, UML, 	Generics	, LINQ	,   Web Services, Ajax, VBA	   	\nVB, WCF,  WPF, WWF, \nSSMA	 	\nAWS	 	Redshift, Hive, RDS, Lambda, Glue	 	 	\nVirtualization	 	Denodo	 	 	\nTools &amp; Techniques	 	MS Projects 2000, VISIO 2000 , UML	 	 	\nDatabases	 	SQL 2000, SQL 2005,	 SQL 2008	 	MS Access	 	\nETL	 Tools	 	SSIS	 	 	\nOperating Systems	 	Windows 2000, XP, 2003\n\nEducational 	Qualification	: 	\n \nBE in 	Electronics and 	Telecomm. Engineering	  	\n \nEmployment History:	 	\nEmployer	 	From	 	To	 	Designation	 	Area	 	\nConfidential	 	Mar 2021	 	Till date	 	BI Architect /Tech \nLead	 	\nPower BI, Spotfire, Google cloud, \nSQL	 	\nATOS 	SYNTEL, 	\nUSA	 	FEB 2020	 	Mar 2021	 	BI Architect /Lead	 	Spotfire, 	Power Bi, 	Google cloud, 	\nSQL	 	\nAsurion	 	Feb 2017	 	JAN 2020	 	BI Architect	 	Spotfire, Power BI, Tableau,  AWS, \nAngularJS, Data Science, R, Python	 	\nJohnson and \nJohnson, USA	 	Jan 2015	 	Feb 2017	 	BI Architect	 	Spotfire/Tableau, DotNET Bootstrap, \nSSIS, SQL	 	\nTIBCO Software	 	July 2011	 	Dec 2014	 	Technical Lead / BI \nArchitect	 	\nSpotfire, Analytics, 	Presales, 	\nconsulting, education and training, \ncompetency building and resource \nmanagement, delivery, R&amp;D	 	\n \n \nProjects	:  	\n \nCustomer	 	FEDEX, Pittsburg, USA (ATOS SYNTEL)	 	\nPeriod	 	Feb 2020 to 	till date	 	\nFedEx	 Corporation is an American multinational delivery services company	.   Fedex Ground in pittsburg is one 	\nof the biggest BI 	clients	 consuming Spotfire extensively for reporting and analytics	. It&rsquo;s been used in various 	\ndepartments like Linehaul, purchase etc. 	Fedex	 was moving from SQL server to GCP.  Reporting technology is 	\ngetting migrated to newer version of 	Spotfire	 in cloud.	 In continuation Spotfire is being migrated on Power BI	 	\nBI Admin/	Architect	 (Spotfire/ Power Bi/GCP)	 	\n&bull; 	Spotfire to power BI migration.	 	\n&bull; 	Power bi report 	development, 	support,	 and admin activities.	 	\n&bull; 	Manage team, scrum, pi planning in agile way.	 	\n&bull; 	Spotfire 	infrastructure build 	into	 GCP. 	 	\n&bull; 	Maintain 	Spotfire	 infrastructure and 	environment.	 	\n&bull; 	Business requirements	 documentation	, relational database design, progr	amming, testing, implementation.	 	\n&bull; 	Working  closely  with  Customer  to  identify  the  technical  approach  to  be  used  and  the  deliverables  to  be \nfurnished at the completion of the project.	 	\n&bull; 	System Administration (includes site creation, server maintenance/Upgrades/patches).	 	\n&bull; 	Change  management	 and 	Monitor  server  activity/usage  statistics  to  identify  possible  performance 	\nissues/	enhancements.	 	\n&bull; 	Partner with the business to design tableau KPI scorecards &amp; dashboards.	 	\n&bull; 	Performance  tuning 	and 	Create/Manage  Groups,  Workbooks  and  Projects,  Database  Views,  Data  Sources, 	\nand Data Connections.	 	\n&bull; 	Proactively communicate with the Customer/Stakeholders to resolve issues and get work done.	 	\n&bull; 	Set up a governance process around Tableau dashboard processes.	 	\n&bull; 	Handles new report/ Adhoc report development.	 	\n&bull; 	Handles support activities and data quality issues for preexisting projects.	 	\n&bull; 	Architect BI solution using Spotfire/Tableau and SQL database.	 	\n&bull; 	Perform various RnD related to 	Spotfire,	 JSViz and D3 charts. 	 	\n&bull; 	Propose various 	approaches	 and 	solutions	 based on PoCs.\n\nTechnologies	 	Spotfire ,Power BI,Tableau,Dot Net/AngularJS, 	Redshift, 	Hive, RDS, 	SQ	, Python, 	\nLambda	 	\n \n \nCustomer	 	ASURION, Nashville, USA	 	\nPeriod	 	Feb 2017 	to JAN 2020	 	\nASURION is mobile insurance company and is one of the largest in USA having more subscriber than Netflix in \nUSA and across.	 Asurion is one of the biggest client consuming spotfire 	and power BI 	extensively for reporting 	\nand analytics	. It&rsquo;s been used in various 	departments	 like SCM, mobility, product etc.	 Asurion 	was moving	 from 	\nSQL server to AWS.	 	\nReporting t	echnology is getting migrated to POWER BI. I have good knowledge of 	Tableau/	Spotfire	/POWER BI 	\nmobile APP, Admin activities, deployment process	. I am handling BI stack including Tableau, spotfire and 	\npower bi.	 	\n \nBI 	Admin/	Architect	/UI expert using .Net/ 	AWS 	(Spotfire	/Tableau/Power Bi/AWS	) 	\n&bull; 	Architect BI solution using 	Spotfire	, P	ower BI	 , Tableau 	and SQL database	. 	\n&bull; 	Migration form older version to newer one.	 	\n&bull; 	Manage team, scrum, pi planning in agile way.	 	\n&bull; 	Handled 	tableau/ 	spotfie /POWER BI 	admin activities involving 	. Handles adhoc report requests.	 	\n&bull; 	Created reporting portal using Dot Net and AngularJS.	 	\n&bull; 	Created  various  inhouse  applications  that  needs  user  inter	face  using  DotNet  and  angul	arJS  for  various 	\ndepartments on request basis.	 	\n&bull; 	Propose  various  approach  and  solution  based  on  PoCs.  Directing  the  strategic  plan,  development  of \nbusiness  requirements,  development  of  functional  and  program  specifications,  relational  database  design, \nprogramming, testing, implementation and documentation for applications	 	\n&bull; 	Working  closely  with  Customer  to  identify  the  technical  approach  to  be  used  and  the  deliverables  to  be \nfurnished at the completion of the project.	 Follow development schedule 	to ensure that timely delivery.	 	\n&bull; 	Perform User Management Administration for 	spotfire	 / Power BI	 	\n&bull; 	Handles  support  activities  and  data  quality  issues  for  pre	-existing  projects  and  c	reate	d datamarts  using 	\nredshift, hive	(AWS migration)	, S3, AWS lambda and glue, written python program	 	\n&bull; 	Forecasting model for Salvage value for mobiles using Multivariant Linear Regression using R language	 	\nTechnologies	 	Spotfire	 ,Power BI	,Tableau,Dot Net/AngularJS	, Redshift, Hive	, RDS, 	MS SQL	,Pyth	on, 	\nLambda	 	\n \n \nCustomer	 	VISTAKON, Johnson &amp; Johnson USA	 	\nPeriod	 	Jan 2015	 to 	Feb 2017	 	\nVistakon is a contact lens manufacturing unit of Johnson &amp; Johnson	. Engineering division of Vistakon works on 	\nthe various lines implementing new designs, using new materials and new machines.	 	\n \nThe need was there to build an analytical solution to collect all the line lens/lot relevant and actionable data \nback to users to continuously improve the designs and product yields by evaluation the collected data.	 	\n \nIt&rsquo;s a data collection process that continuously pulls and gathers data, churn it, and transform it and bring \nback meaningful defect lens information that is an actionable insight for continuous improvement in machine, \ndesign, production line and proces	s. 	\nBI 	Architect	 (Spotfire/Tableau	) 	\n&bull; 	Architect BI solution using 	Spotfire/Tableau	 and SQL database and SSIS ETL tool	 	\n&bull; 	Perform various RnD related to 	Spotfire	 , JSViz 	and D3 charts. 	 	\n&bull; 	Propose various approach and solution based on PoCs. 	 	\n&bull; 	Directing  the  strategic  plan,  development  of  business  requirements,  development  of  functional  and \nprogram  specifications,  relational  database  design,  programming,  testing,  implementation  and\n\ndocumentation for applications	 	\n&bull; 	Working  closely  with  Customer  to  identify  the  technical  approach  to  be  used  and  the  deliverables  to  be \nfurnished at the completion of the project.	 	\n&bull; 	Follow development schedule 	to ensure that timely delivery.	 	\n&bull; 	Perform User Management Administration for 	Spotfire and Tableau	. 	\n&bull; 	Handles adhoc report requests.	 	\n&bull; 	Handles support activities and data quality issues for preexisting projects.	 	\nTechnologies	 	Spotfire Tableau	, Dot Net with bootstrap,	 D3 Charts	, SSIS	, MS SQL	 	\n \n \nCustomer	 	P&amp;G USA	 	\nPeriod	 	Dec	 20	12 to 	Dec 2014	 	\nProcter &amp; Gamble Co.,	 also known as	 P&amp;G	, is an American	 multinational	 consumer goods	 company. P&amp;G is 	\none of the biggest client for Spotfire and implemented around more 	than 50	 Spotfire analytical 	projects 	\n/applications of various scale.	 	\nSolution Architecture for Review and Technical assistance for more than 40 Spotfire solutions	 	\nRoles and responsibilities as 	Technical Leader / Solution 	Architect	 	\n&bull; 	Defined standards and process for Solution Review	 	\n&bull; 	Defined standard for best practices in terms of usability and data design.	 	\n&bull; 	Participate in architectural discussions of project design and provided guidance to various project teams.	 	\n&bull; 	Working  closely  with  Customer  to  identify  the  technical  approach  to  be  used  and  the  deliverables  to  be \nfurnished at the completion of the project.	 	\n&bull; 	Architect, Design	 to ensure that timely delivery.	 	\n&bull; 	Consulting  and  mentoring technical  resources  concerning  methods,  procedures,  and  standards  to  be  used \nduring design, development, and unit testing phases of system development projects.	 	\n&bull; 	Schedule/conduct	 series of 	quality reviews for Spotfire project 	to give Go/No	-Go decision 	before it goes to 	\nproduction  making  sure  projects  are  as  per  defined  standards  across  P&amp;G,  best  suited  from  performance \nperspective.	 	\n&bull; 	Assists and guide project team for performance improvement.	 	\nTechnologies	 	Spotfire, MS SQL, SSIS, Custom D3 charts	 	\n \n \n \n \nTIBCO Spotfire	 as a role of Technical Lead	 and Architect	 	\n \nI have h	andled	 (designed, architect) for 	various	 Spotfire BI projects with a team of 8 resources and took part 	\nin almost all areas like Presales, consulting, education and training, competency building, delivery, R&amp;D. 	 	\n \nPeriod	 	July	 20	11	 to 	Dec 2012	 	\nClients	 	Responsibility	 	\nGaruda Airlines (Indonesia)	 	Spotfire Custom Datasource for 	Amadeus 	Webservice in spotfire	 	\nNovartis Support  (UK)	 	Technical Support at Architect level.	 	\nTSMC, Pareto Chart \n(TAIWAN)	 	\nArchitect design for custom Chart, development, design, manages in spotfire \nusing spotfire API SDK.	 	\nAstraZeneca (	UK	) &ndash; Gantt 	\nChart	 	\nCustom Gantt Chart development, design, manages in spotfire using spotfire API \nSDK.\n\nCredit Agricole, DBS \n(Singapore) , SHB(Saudi \nArabia), AIMCO (CANADA), \nReliance, Genpact (INDIA), \nHP (INDIA) etc.	 	\nClient  Interaction	 	\nRequirement Gathering	 	\nLead and Architect	 	\nReview 	 	\nEstimation/scheduling	 	\nTechnologies	 	Spotfire, MS SQL, SSIS,	 Custom 	D3 charts', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-04-24 12:33:24', 0),
(341, 79, 1, 4, 12, '1_79_4_2071541210663af80a46bb7_BA_CV_-_CV.docx', 'BA_CV - CV.docx', '\r\nShweta Sharma Sr. Business Analyst \r\nWipro  PROFESSIONAL SUMMARY\r\nExperienced Business Analyst with overall 11+ years’ experience as 6+ years’ in analyzing business requirements in software development and 5 years’ track record in Operations\r\nProfile Summary Business Analysis – Planning &amp; Scoping, AS IS &amp; TO BE Process Modelling, Requirement Analysis &amp; Documentation, managing backlog, prioritizing feature scope, defining Use stories, Manage Stakeholder\'s Sign offs.\r\nWell versed with SDLC methods – Agile and waterfall, experienced in requirements gathering, Group Discussions and Use Cases. Experienced with creating and modifying process flow diagrams and Use Case Diagrams. Excellent communication, analytical, interpersonal, and presentation skills; highly adept at handling the expectations of Multiple Stakeholders\r\nTools Exposure in Visio for requirement modelling, Azure- VSTS, JIRA, Top Team, Kanban Board\r\nCurrent Organization Wipro\r\nRole Product Owner cum Business Analyst Duration Apr’15 – Till Date\r\nKEY PROJECT DETAILS\r\nClient Name  Japan Client Development Methodology Agile and Waterfall\r\nRole Product Owner cum Business Analyst  Duration Jan’19 – Till Date\r\nProject 1 Commercial App (Agile -Jan’19 till Date) Project 2 Residential App (Waterfall -Aug’19 – Till Date)\r\nResponsibilities  Collaborate with business users, product owners and business partners to gather and identify requirements and further define and document requirements.\r\nLead requirements discussion/review sessions with users, vendors, and the partners to further refine/scope requirements.\r\nAnalyze business requirements by doing a research work on To-Be proposed solutions to business teams by understanding the competitors’ applications, current market expectations from the product. \r\nPrioritize the scope based on product strategy.\r\nManage and prioritize backlog items on each iteration.\r\nCreate Use cases, user stories by capturing requirements from multiple stakeholders and getting signed off on the same in timely manner.\r\nAssist in planning, estimates, testing and rollouts of new software release and establish critical project related milestones, and participate in quality assurance.\r\nSupported in user acceptance of a release or feature, and provide value management reporting\r\nInvolved in solution design discussions to improve system usability/UI experiences.\r\nResponsible for delivering status reports to client as and when required.\r\nClient Name US client Development Methodology Agile\r\nRole Business Analyst  Duration Apr\'18 – Jan’19\r\nResponsibilities  Working in capacity of business analyst for Q2 Solution and managing and developing the LTMS application used for clinical trials laboratories services\r\nPlan execute and manage the integration of new applications into existing network infrastructure, systems &amp; software throughout the enterprise\r\nGathering requirements and creating user stories and managing requirements in top team\r\nManaging the scoping of requirements and discussing the same with different stakeholders\r\nStepped up and played scrum master/project manager role when project was short of resources\r\nManaging daily calls and reporting on status on weekly basis to client\r\nClient Name Swiss Client Development Methodology Agile\r\nRole Business Analyst  Duration Apr\'15 –Mar’18\r\nResponsibilities  Working as a business analyst for UBS and managing applications risk assessment for finance stream\r\nRequirement planning &amp; management – Prepare plan for gathering requirement &amp; delivering within milestones\r\nApplication scoping, Requirement gathering and documentation, Elicitation using multiple techniques- User discussions, System documentation, meetings, etc.\r\nLiaison between business &amp; team, stakeholder management, governance reporting\r\nResponsible for overall application Risk Assessment\r\nInvolvement in application transition Go Live\r\nWeekly project reporting\r\nPrevious Organization  Accenture\r\nRole Analyst - Asset Data Management &amp; Reporting Duration Dec\'09 - Apr\'15\r\nResponsibilities  Possess comprehensive understanding of database management systems\r\nInteracting with management in implementation of business, process, and technology improvements\r\nPlanning, implement quality and process improvement initiatives and UAT testing for production environment for enhance productivity\r\nPreparing data for a Dashboard (ORB) and other related reporting in a timely, accurate and consistent format/manner\r\nAnalyze monthly, Quarterly and Annual reporting requirements &amp; prepare month-on-month “Trend &amp; Gap analysis” &amp; forecasting reports\r\nPublishing the documents or reports on intranet web page\r\nReporting sustainability performance against the KPIs for the business sector \r\nAnalyzed data in case of anomalies and carried out quality checks for the reports\r\n', 2, 2, 1, 'Candidate', 'Assigned', 'SL', 1, 'N', 14, '2024-05-08 04:07:33', NULL, '2024-05-11 04:07:33', 0, NULL, '2024-05-08 03:56:58', 4),
(342, 80, 1, 4, NULL, '1_80_3721169316652bf8ce1b8e_Ajay+Bharti+Cv.pdf', 'Ajay+Bharti+Cv.pdf', 'PR O FIL EI  Am   work in g   As  a  Php\nB ack e n d  D eve lo p er.	 	\nI&#039;m  use d   to   w ork in g   un d er\np re ssu re   an d   I  lo ve   all  of\ncre a tiv e  p ro ce ss.\nw hic h  w ill  h elp  m e t o  e xp lo re\nm yse lf   fu lly   an d   re a liz e   m y\npote n tia l.	 	\nL A RA V EL B A C KEN D	\nDEV ELO PER	A ja y B hart i	\n211,  S ta tio n  R oad  K ota ,\n(R aja sth an )\n8 233 8465 96w ww .l in ke d in .c o m /in /a ja y\n-b harti- 6 a3 899227/\naja yb harti6 9 96@ gm ail .c o m	W ORK  E X PER IE N CE	Sta rt W ork in g  h ere  O n C od eIg nit e r A nd  W ord pre ss\nB uild  B ack e n d  d ash b ord  a n d  W ord pre ss	 	\nA ls o  B uild  A  D ro p  S hip in g  W ord pre ss P lu g in .	\n      	E -c o m merc e  W eb sit e s.	\nP H P,  W ORD PR ES S D EV ELO PERT W S T EC H N O LO GY K O TA	Ju ne  2 0 20  -  J a n  2 0 22	A sh m ar T ech nolo gie s &amp;\nR ese arc h  P vt L td .\nPH P L A RA V EL D EV ELO PERApril  2 0 22 -  P re se nt	 E D U CA TIO N  H IS TO RY	Gra d uate d  in  C om pute r E ng in eerin g .	 	\nG ain ed   exte n siv e   tr a in in g   an d   su cce ssfu lly\na cco m plis h ed   all  co u rs e s  fo r  Com pute r\nE ng in eerin g  W It h  6 4 %  A ggre g ate  p erc e n ta g e.\nS um m er T ra in in g  f r o m  W eb in fo te ch  .	\n       	P H P A nd  M yS ql,	\n        	P hoto sh op ,  f la sh  p la ye r,	\nB .T ech\nC om pute r E n g in eerin g\nR aja sth an  T ech nic a l U niv e rs it y ,  K ota	10  N ove m ber 2 0 19	S O FT W ARE &amp;  T O OLSS K IL LSP hp ,  C od eig nit e r,  L ara ve lja va sc rip t,  jq ueryH tm l,  C ss,  B oots tr a pW ord pre ss	V S C od e,  G it  B ash ,  X am pp,  P ostm an ,  F ile zilaF ig m a,  P hoto sh op ,  P hoto p ia ,  C an vaG it  H ub ,  M yS ql  W ork b en ch ,T in y P N G,\nRem ove  b g ,	 	\nI  am  w ork in g   on   M on et  Netw ork s  dep artm en t  of\nA sh m ar I P	 a s a  la ra ve l  b ack e n d  d eve lo p er.	\nM on et  is   th e  fir s t  A I  p ow ere d  P la tfo rm  to   h um an iz e\nd ata  in  s e rv ic e  o f c re a tiv it y .	 	\nW e a re  w ork in g  o n  L ara ve l  6 .0  L T S  v e rs io n ,  h ere  m y jo b\nro le  to  cre a te  A pi,  g en era te  re p orts ,  d ata  tr a n sfe r  to\nM yS ql  t o  M on g o d b.\np ro je cts  :  e em o,  D IY ,	  e em o d ash b oard .', 2, 2, 1, 'Recruiter', 'Assigned', 'SL', 1, 'N', 14, '2024-05-26 05:00:02', NULL, '2024-05-31 05:00:02', 0, NULL, '2024-05-26 04:50:20', 0),
(343, 80, 1, NULL, NULL, '1_80_18620152516652bf8ce2681_Akhil_Bhardwaj.pdf', 'Akhil Bhardwaj.pdf', 'AKH IL  B H ARD W AJ \nakh il b 2106@ gm ail .c o m  \n+91- 6 376065663 \nVais h ali N ag ar, A jm er, I n d ia  \nlin ke d in .c o m /in /a kh il - b hard w aj- 2 a8 020147 \nWORK  E X PER IE N CE \nIm ple m en ta tio n E ngin eer \nE2o pen  S o ft w are  I n d ia  P riv a te  L im it e d  \n09/2 022 -  P re se n t\n, \n  Bangalo re , I n dia  \nOve rs e e \nBack e nd  d eve lo pm ent\n u sin g \nJav a\n t o\nmain ta in  w eb sit e  i n te grit y , s e cu rit y  a n d  e ﬃ cie ncy . \nBuil t  S o ft w are  u sin g \nSp rin g F ra m ew ork\n a n d  d one\nenhan ce m ents\n a n d  ﬁ nd in g \nbugs/d efe cts\n a n d\nan aly sin g r o ot c a u se s i n  d eliv e rin g t h e p ro duct. \nSo ft w are  S u ppo rt  E ngin eer \nAm docs D eve lo pm en t C en te r I n d ia  L LP  \n10/2 021 -  0 9/2 022\n, \n  Gurg ao n, I n dia  \nExp ert is e  i n  C lie nt-S e rv e r a p plic a tio n d eve lo pm ent\nusin g \nPLSQ L D eve lo per\n a n d  \nEclip se\n. \nBein g p art  o f B il lin g a n d  R atin g t e am , I  a m\nre sp onsib le  t o  ﬁ nd  t h e i s su es/ro ot c a u se  t h at o ccu rs\ndurin g t ra n sa ctio n a m ong 1  m il lio n u se rs . \nGenera te d  r e ve nue w ort h  o f $ 20M  b y s u cce ssfu lly\npro ce ssin g b il lin g o n m onth ly  b asis  a n d  t im ely\ntra n sa ctio ns d one b y t h e e nd  c u sto m er. \nED UCATIO N \nBach elo r o f E ngin eerin g ( B .E .)  \nUniv e rs it y  I n stit u te  o f E ngin eerin g a n d\nTe ch no lo gy ( U IE T), P an ja b  U niv e rs it y  \n07/2 017 -  0 8/2 021\n, \n  Chandig arh , I n dia  \nEle ctro nic s a n d\nCom munic a tio n\nEngin eerin g \nCG PA  \n- 6 .9 2/1 0 \nSen io r S eco ndary  E duca tio n ( C la ss X II-\nRBSE ) \nMah ara ja  P ub lic  S ch o ol, A jm er, R aja sth an  \n04/2 015 -  0 4/2 016\n, \n  Perc e n ta ge :  7 0.4 0/1 00 \nSK IL L S  \nJava  \nOra cle  S Q L \nData  S tru ctu re s \nAlg o rit h m s \nObje ct O rie nte d  P ro gra m min g \nSp rin gb oot \nUnix  \nPR O JE C TS \nEm ail  A PI u sin g S p rin gboot\n ( 0 6/2 022 -  0 6/2 022)\n \nPro je ct D esc rip tio n :  \nThis  i s  a  s im ple  a p plic a tio n u sin g  \nSM TP\npro to co l\n f o r s e nd in g  E m ail  .  H ere  I  h ave  u se d  \nPostm an\n t o\nte st A PIs . \nTo ols  a n d  T e ch no lo gie s U se d  :  \nCore  J av a, C olle ctio ns\nFra m ew ork , P ostm an  A PI. \nPro je ct L in k :  \nhttp s:/ /g it h ub.c o m /a k hil b hard w aj2 0/E m ail -\nApi- u sin g-S p rin gb oot\n \nCRU D -O pera tio ns u sin g S e rv le t a n d M VC\nArc h it e ctu re\n ( 0 3/2 022 -  0 3/2 022)\n \nPro je ct D esc rip tio n :  T his  i s  a  l ig ht-w eig ht w eb  a p plic a tio n\nfo r u se r r e g is tra tio n, l o gin , d ata  u p datio n a n d  i d  d ele tio n\nfa cil it ie s b ase d  o n s e ssio n m an ag em ent a n d  \nMVC\n p ara d ig m\nof \nJ2 E E\n. I t  a ls o  i m ple m ents  s e p ara te  a d m in is tra to r a cco unt\nto  v ie w  u se r d ata . \nTo ols  a n d  T e ch no lo gie s U se d  :  E clip se , A pach e T o m ca t\nSe rv e r, S p rin g  M VC, J S P, M yS Q L. \nACH IE V EM EN TS \nSo lv e d  5 00+ p ro ble m s o n l e etc o de b ase d  o n D ata\nStru ctu re s a n d A lg orit h m s. \nLin k :  \nhttp s:/ /le etc o d e.c o m /a khil b 2106/ \nLA N GUAG ES \nEnglis h  \nFu ll P ro fe ssio nal P ro ﬁ cie n cy \nHin d i \nFu ll P ro fe ssio nal P ro ﬁ cie n cy \nAch ie ve m en ts/T a sk s \nAch ie ve m en ts/T a sk s \nCours e s', 2, 2, 1, 'Recruiter', 'Un-assigned', 'SL', 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-05-26 04:50:20', 0),
(344, 80, 1, 4, NULL, '1_80_13675055946652bf8ce2d02_ashutoshkaushikresume.pdf', 'ashutoshkaushikresume.pdf', 'RESUME	 	\nPERSONAL DETAILS	 	\nName:	 	Ashutosh Kaushik	 	 	\nAddress:	 	65, Radhey Shyam Park, \nParwana Road, Delhi	-51	 	\n 	\nEmail id:	 	ashutoshkaushik98@gmail.com	 	 	\nMobile no.:	 	9540541281	 	 	\n \nEDUCATIONAL QUALIFICATIONS	 	\nS.no	 	Degree	 	School/ \nCollege	 	\nBoard/Univ	 	Year	 	Percentage	 	\n1 	10TH	 	Universal \nPublic School	 	\nC.B.S.E	 	2014	 	92	 	\n2 	12th	 	Guru \nHarkrishan \nPublic School	 	\nC.B.S.E	 	2017	 	79.5	 	\n3 	B.Tech.(	CS	E)	 	Delhi \nTechnical \nCampus	 	\nG.G.S.I.P	.U 	2021	 	 	\n \nOBJECTIVE	 	\n \nTo work in globally competitive environment on challenging 	assignments that shall 	\nyield the twin benefits of the job satisfaction and a steady	-pace professional growth.	 	\n \n \nTECHNICAL SKILLS	 	\n \nPHP Codeigniter Framew	ork\n\nHandled projects in	 MVC,HMVC	 patterns	resume	,jquery,javascript,mysql	 ,AJAX 	\ntechnologies	 	\n \nJavascript,google charts	, 	\nCodeigniter minify libraries	 	\nAjax datatable	 	\nImplemented 	various	 Helpers	 and libraries.	 	\nForms,Modular forms,F	orm re	peater	 	\n \n \n. \n \n \n \nEXTRA CURRICULAR ACTIVITIES	 	\n \n-Participation in Social Welfare Activities 	in college	 	\n-Participation in Seminars	 	\n \nCERTIFICATIONS	 	\n \n \nCourse Name	 	Course Type	 	Certified By	 	\nWeb 	Development 	\nBootcamp	(react baasics, 	\njavascript, node, git, \nexpress, mongodb, 	\ngraphql)	 	\nOnline	 	The London App Brewery	 	\nReact	 upto Intermediate 	 	Online	 	Coursera	 (Free) Audit 	\nCourse (1 month)	 	\nMachine Learning	 	Online	 	SuperData Science, \nUdemy	(1 month)	 	\nBlockchain	 	Online	 	George Levy, Blockchain	 	\n 	 	 	\n \nWORK EXPERIENCE:	 August 15	-Present(	Appsquadz Software	)PHP	 developer 	\nCodeigniter(	 1 years	)\n\nPHP Codeigniter Framew	ork	 	\nHandled projects in	 MVC,HMVC	,jquery,javascript,mysql	 ,AJAX technologies	 	\n \nACADEMIC PROJECTS	 	\nI have made these fully functioning projects which apply concepts I have \nlearnt and got practical exposure in code	 	\nFriend request application in PHP	 	\nAdmin 	panel in PHP	 with role management	 	\nJavascript,google charts	, 	\nCodeigniter minify libraries	 	\nAjax datatable	 	\nSed 	various	 Helpers	 	\nForms,Modular forms,F	orm re	peater,	 	\n \nSocial media Web App(React Js)	 	\nDeep Learning Tensorflow(Image Classification)	 	\nYOLO Real Time Detection	 	\nMachine Learning Chatbot	 	\nCoronavirus Real Time Tracker	 	\nTodoist Clone in React JS	 	\nHackerNews API with infinite scroll and 500 stories	 	\nWeb Scraper	 on Craig	slist	 	\nReact Chat Application without user authentication	 	\nReact Chat Application with user authentication and image and video upload	 	\nInstagram like application	 	\nOpen CV	 	\nSE	O 	\nNote Create Web Application	 	\n \nACHIEVEMENTS AND AWARDS	: 	\n \nWeb Development 	Bootcamp	 	\nReact Development	 	\nMachine Learning	 	\nBlockchain	 	\n \nSTRENGTHS:\n\nPositive Attitude	 	\nPatience to learn and solve problems	 	\nLearn the logic behind the problem	 	\nProblems should be solved with different methods	 	\nError troubleshooting is a big part of 	programming	 	\nGood communication skills	 	\n \nWEAKNESSES	: 	\nI trust others easily	 	\n \nPERSONAL PROFILE	 	\n \nFathers Name	- Mr. Sheel Kaushik	 	\nDate of birth 	-03/08/1998	 	\nLanguages Known	- English, Hindi	 	\nNationality	- Indian', 2, 2, 1, 'Recruiter', 'Assigned', 'SL', 1, 'N', 22, '2024-05-26 05:00:29', NULL, '2024-05-28 05:00:29', 0, NULL, '2024-05-26 04:50:20', 0),
(345, 80, 1, NULL, NULL, '1_80_18455614116652bf8ce3445_Avnishs+Resume+(1).pdf', 'Avnish\'s+Resume+(1).pdf', 'A vn is h  K arw a\nT o  p urs e  a  j o b o ppo rt u nit y  i n  a  c o m petit iv e  e nvir o nm en t t h at w il l c h alle n g e m e t o  p ush  m y b o un d arie s\na n d  e xp an d  m y k n o w le d ge i n  t h e ﬁ eld  o f c o m pute r t e ch n o lo gy w hil e  a llo w in g  m e t o  a d d v a lu e t o  t h e\nd yn am ic s o f t h e c o m pan y.	\n\na vik arw a0 001@ gm ail .c o m	\n9 303611001	\n\nH ouse  n o  1 1/1 132 B esid e o f A rih an t T ra d ers  G ud iy a ri\n\nP ad av, R aip ur, C hattis g arh , 4 92011, c h attis g arh , I n d ia	\n\nE D UCATIO N\n\nP U RSU IN G M AST ER  O F T EC H N O LO GY\nP R IY A D ARSH IN I C O LLE G E O F E N GIN EER IN G,\nN AG PU R\n1 1/2 022 -  P re se n t	\n,\n1  y e a r C ours e	\nD efe n se  T e ch n o lo gy	\n\nB A CH ELO R O F E N GIN EER IN G\n\nP R IY A D ARSH IN I C O LLE G E O F E N GIN EER IN G,\nN AG PU R\n0 7/2 021	\n,\n8 .5 3 C G PA  C ours e	\nC om pute r T e ch n o lo gy	\n\nH IG H ER  S E C O NDA RY  C ER TIF IC ATE	\nH O LY	\n\nC RO SS S E N IO R S E C O NDARY S C H O O L, K APA ,\nR A IP U R, C H ATTIS G ARH .\n0 2/2 016	\n,\n6 2.0 0%	\n\nS E C O NDA RY  S C H O OL C ER TIF IC ATE\n\nD ESH BA N DHU H IG H ER  S E C O NDARY E N GLIS H\nM ED IU M  S C H O OL, R A IP U R, C H ATTIS G ARH .\n0 3/2 014	\n,\n7 8.0 0%	\n\nW ORK  E X PER IE N CE A N D I N TER N SH IP	\n\n3 0 D ay s i n te rn sh ip  o n &quot; F ro nt-e n d  w eb\nd eve lo pm en t&quot;\nf ro m  W esig n T e ch n o lo gie s P vt. L td .\n0 1/2 021 -  0 2/2 021	\n,	\n\n3  M onth s i n te rn sh ip  o n &quot;  R  a n d  D  o n l a te st\n\nh ack in g  t e st&quot;\nf ro m  V ig il a n te  C yb er F o rc e s.\n0 2/2 021 -  0 5/2 021	\n,	\nl in ke d in .c o m /in /a vn is h -k arw a-9 630651b 5	\n\nS K IL L S\n\nM ic ro so ft  o ﬃ ce  B asic  o f C  B asic  o f C  + + B asic  o f\n\nJ A VA  F ro nt-e n d  w eb  d eve lo pm en t\nR  a n d  D  o n l a te st h ack in g  t e st\n\nP ER SO NAL P R O JE C TS\n\nM AJO R P R O JE C T: &quot;  D ece n tra liz e d  s to ra g e a n d  s h arin g\ns y ste m  u sin g  b lo ck ch ain &quot;. I n  t h is  w ork , i t  a im s t o  d eve lo p a\nw eb  a p plic a tio n w hic h  e n su re s t h e s e cu rit y , i n te g rit y  a n d\np riv a cy  o f t h e d ata .\n\nA CH IE V EM EN TS\n\n1 . A ctiv e  m em ber o f M ah esh w ari Y u va  S an g ath an  ( A\nC om munit y  G ro up  i n vo lv e d  i n  S o cia l a n d  C ult u ra l\nA ctiv it y ).\n\nC ER TIF IC ATES\n\n1 . P ub lis h ed  a  p ap er e n tit le d  &quot;  A  r e vie w  o f\nd ece n tra liz e d  s to ra g e a n d  s h arin g  u sin g  b lo ck ch ain &quot;.	\nI n ,	\nI n te rn atio nal J o urn al o f A dva n ce  R ese a rc h , I d ea s a n d I n nova tio ns i n\nT e ch no lo gy.\n\n2 . P ub lis h ed  m an usc rip t e n tit le d  &quot; D ece n tra liz e d  s to ra g e\n\na n d  s h arin g  s y ste m  u sin g  b lo ck ch ain &quot;.\nI n  t h e I n te rn atio nal J o urn al o f S cie n tiﬁ c R ese a rc h  i n  E ngin eerin g a n d\nM an ag em en t.\n\nL A N GUA G ES\n\nE n g lis h\nF u ll  P ro fe ssio nal P ro ﬁ cie n cy\n\nI N TER EST S\n\nF o otb all B ad m in to n C hess S w im min g  O n s ta g e d eb ate\n\np ain tin g', 2, 2, 1, 'Recruiter', 'Un-assigned', 'SL', 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-05-26 04:50:20', 0),
(346, 80, 1, NULL, NULL, '1_80_1839201636652bf8ce3b61_Bikash-Jena-SDE.pdf', 'Bikash-Jena-SDE.pdf', 'BIKASH	 JENA	 	\nSoftware	 Engineer	 	 	\nb2j1999jan27@gmail.com	 	 +91	 8327750692	 	  Hyderabad	 	\nLinkedIn	 	  GitHub	 	 Website	 	\n \n \nW	ORK	 EXPERIENCE	 	 	 	\nSoftware	 Engineer	 	\nCGI	 Information	 Syste ms	 and	 Ma nage ment	 	\nCons ultants	 Private	 Limited	 	\n  July	 2021	 - current	 	  Hyderabad,	 Telangana	 	\nDesigned,	 built,	 and	 modiﬁed	 a web	 application	 utilizing	 	\nAngular, Spring boot, RabbitMQ, MongoDB, MySQL and	 	\nAWS.	 	\nDeveloped and tested new restful services utilizing the	 	\nspring	 boot	 framework	 as	 a member	 of	 the	 development	 	\nteam.	 	\nTracked	 and	 ﬁxed	 defects	 in	 SIT,	 UAT,	 and	 production	 	\nstages.	 	\nImplemented	 DevOps	 to	 deploy	 new	 microservices	 to	 the	 	\nOpenShift	 platform.	 	\nDockerized  all  the microservices  to  make  the  deployment	 	\nprocess	 more	 cost	-effective	 and	 documented	 100%	 of	 the	 	\ntechnical	 speciﬁcations	 and	 dependencies	 of	 applications	 	\n \n \nPROJECT	 	 	 	\nKawach: A patient, doctor, and voluntee	r networking	 and	 	\nmanagement	 platform	 for	 pandemic	 support.	 	\nhttps://github.com/b2jena/kawach	-pandemic	-support	 	\n  12th	 July	 2021	 - 20th	 October	 2021	 	\n \n \nCOMPETITIVE	 PROGRAMMING	 	 	 	\nCodechef: 4 star (Highest Rating: 1899	); Usernam	e: b2jena 	\nEDUCATION	 	 	 	\nB.Tech	 	\nMining	 Engineering	 	\nIIEST,	 Shibpur	 	\n  2017	 - 2021	 	\n  Howrah,	 West	 Bengal	 	\nCGPA: 7.87 	\nRelevant	 courses	 	\nData	 Structures	 (Coding	 Ninjas)	 	\nAlgorithm	 Design (Coding	 	\nNinjas)	 	\nDatabase	 Management	 Systems	 	\n \nSenior	 Secondary	 	\nPCM	 with	 Informatics	 Practices	 	\nSri	 Chaitanya	 Techno	 School	  	\n 2015	 - 2017	 	\nVisakhapatnam	, Andhra	 Pradesh	 	\n12th Percentage: 87.6% 	\n \n \nSKILLS	 	 	 	\nData	 Structures	 and	 Algorithms	 	\nJava (Spring boot	) 	\nAngular/HTML/CSS/Typescript	 	\nSQL 	(MongoDB, MySQL, Oracle)	 	\nC/C++	 	\nBasics	 of	 Python	 and	 ReactJS	 	\nGit', 2, 2, 1, 'Recruiter', 'Un-assigned', 'SL', 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-05-26 04:50:20', 0),
(347, 80, 1, NULL, NULL, '1_80_17217918826652bf8ce4327_CV+Pardeep.pdf', 'CV+Pardeep.pdf', 'P A RD EEP	 	\n \nM obi le  N o .	  \n: +91 -9306835883	 	\n \nE-mail :	  \npardeepbaghel0311@gmail.com	 	\n \nCURRICULUM VIT AE	 	\n \nO bje ctiv e :	 	\n \nC are er O bje ct	 	 \n: 	\n \nI  \nw ou ld	  \nl ik e	  \na  \nc a re er	  \nt h at	  \ng iv e s	  \nme	  \nr ic h	  \ne xp osu re	  \nt h ro u gh	  \nd iv e rs e	  \na ssig n men t	  \na n d	 	 \nw ork in g	  \nw it h	  \np eop le	  \no f	  \nh ig h	  \nc a lib re .	  \nI  \nw ou ld	  \nc o n sta n tly	  \nl o ok	  \no u t	  \nf o r	  \nc h alle n ge s,	  \nw hic h	 	\n \nw ou ld  h elp  me t o a ch ie ve  my  p ers o n al  a n d  p ro fe ssio n al  g o al.	 	\n \nP e rs on al  In fo rm atio n :	 	\n \nN am e	 	 \n: 	 \nP A RD EEP	 	\n \nC o rre sp o ndin g A ddre ss	 	 \n: 	 \nS h iv  v ih ar,  P a lw al,  H ary a n a(1 21102)	 	\n \nP h on e N um ber	 	 \n: 	 \n+ 91-9 306835883	 	\n \nD ate  o f B irt h	 	 \n: 	 \n0 3-N ove mb er-2 000	 	\n \nS k ills	 	 \n: 	 \nW eb  D eve lo p men t,	  \nS o \0 w are  D eve lo per,	  \nP ro gra mmi ng	 	\n \nL an gu age  K now n	 	 \n: 	 \nE n glis h  a n d  H in d i	 	\n \nE d u ca tio n al  Q uali f ic a tio n :	 	\n \nD egre e	 	 \nI n stit u te /C olle ge	 	 \nB oard /U niv e rs it y	 	 \nY e ar of  P assin g	 	 \nD iv is io n	 	\n \nM atric u la tio n  ( 1 0th )	 	 \nB .K  S r.  S e c. S c h ool	 	 \nH BSE	 	 \n2 016	 	 \n1  \ns t 	\n \nI n te rmed ia te (N O N M ED ICA L)	 	 \nB .K  S r.  S e c. S c h ool	 	 \nH BSE	 	 \n2 018	 	 \n1  \ns t 	\n \nB .T e ch .(C. S.E )	 	\n \n( P urs u in g)	 	\n \nS a ty a  G ro u p  O f	 	\n \nI n stit u tio n	 	 \nJ C BO SE  Y M CA	 	 \n2 022	 	 \n- 	\n \nJ o b  E xp eri en ce :	 	\n \nS IX  M ONTH  E X PER IE N CE	 	\n \nC om pu te r P rofic ie n cy :	 	\n \nO pera tin g s y ste m s	 	 \n: 	 \nW in d ow s 9 8/2000/X P /7/8/8.1 /10	 	\n \n: 	 \nM S O ffic e  ( M s-W ord ,M s-P o w erP o in t)	 	\n \nP ro gra m min g L an gu age s	 	 \n: 	 \nC , C#.N ET, . N ET  M VC ,	  \nC SS	  \n,  H TM L,J Q UERY, S Q L	 	\n \nD ecla ra tio n :-	 	\n \n&ldquo; I	  \nh ere b y	  \nd ecla re	  \nt h at	  \nt h e	  \na b ove -men tio n ed	  \ni n fo rma tio n	  \ni s  \nc o rre ct	  \nu p	  \nt o	  \nmy	  \nk n ow le d ge	  \na n d	  \nI  \nb ear	  \nt h e	  \nr e sp on sib il it y	  \nf o r	 	\n \nt h e c o rre ctn ess o f t h e a b ove -men tio n ed  p art ic u la rs &rdquo;	 	\n \nP la ce : P a lw al,  H ary a n a	 	\n \nD ate :  0 3/03/2022	 	\n \n( P a rd eep )', 2, 2, 1, 'Recruiter', 'Un-assigned', 'SL', 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-05-26 04:50:20', 0),
(348, 80, 1, NULL, NULL, '1_80_16230787076652bf8ce4f20_Dileep_Mopuri_Resume.pdf', 'Dileep Mopuri Resume.pdf', 'Dileep \nMopuri	 	\nHyderabad	 	 	\n+91 8712140642	 	 	\ndileepchkrpn@gmail.com	 	 	\nhttps://www.linkedin.com/in/dmopuri	 	 	 	\nExperienced and dedicated Data Analyst with 	6 years of working experience. my work consists of 	\nidentifying	 efficiencies and problem areas within data streams. I&rsquo;m adept at receiving and monitoring 	\ndata from multiple data streams. Can interact effectively with colleagues and clients both in country an	d 	\noverseas. worked on software	 applications such as SQL, Informatica	 and in	-house applications known as 	\nUnify (Master Database) and MARS (Data Stewardship). I&rsquo;m a presenter and confident communicator \nwith the ability to circulate information in a way that 	is clear, efficient, and beneficial for end users.	 	\nExperience	 	\n12/2021 	TO 	07/2022	 	\nSenior Data Analyst 	- Teamware Solutions (Client	-TCS)	. 	\nHyderabad.	 	\n&bull; 	Scheduling Batch process as per the required time window which can consists of executing \nhundreds or thousands of jobs in pre	-established sequence. 	 	\n&bull; 	Monitoring the job activity and look for successful completion or job failures and then log the \njob. 	 	\n&bull; 	Raise	d requests that deal with incidents, changes, problems, and other services using ticketing 	\ntools like ServiceNow. 	 	\n&bull; 	Perform general supervision, implementing, maintaining and scheduling workloads and event	-	\nbased processes. 	 	\n&bull; 	Performed analysis, design and im	plementation of batch processing workflows 	with	 Cisco Tidal 	\nEnterprise Scheduler. 	 	\n&bull; 	Using salesforce, I&rsquo;ve analyzed project objectives, created customer workflows, and \ntroubleshoot errors. 	 	\n&bull; 	Good knowledge on administration, creation and maintenance of calen	dars, review and 	\nimplementation of all IT job processing, optimization of job schedules, monitoring and reporting, \nas well as analysis of job failures. 	 	\n&bull; 	Responsible for overseeing the restart and rerun of all production jobs, creating and maintaining \naccur	ate documentation, including all job dependencies, and the development and maintenance 	\nof standard operation procedures. 	 	\n&bull; 	Escalates problems as necessary and provides timely status until transferred or resolved. 	 	\n&bull; 	Assist in developing or improving batch ope	rations best practices. Responsible for the 	\norganization of workloads in the operational environment. 	 	\n&bull; 	Understand impact of changes to job processing and adjust schedules modifying as necessary \nfor scheduled maintenance, etc. 	 	\n&bull; 	Monitor and respond to alarms	, assess impact, troubleshoot and resolve problems	, escalate to 	\nsubject matter experts when required	. 	\n&bull; 	Responsible for changes to IT production environments, managing change control \ndocumentation as changes are made, manage the change control meetings and c	ommunicate 	\nchanges to IT services and business users who are impacted. Document all changes.\n\n01/2019 TO 11/2021	 	\nSenior Data Analyst 	- Phoenix American Sales Focus Solutions India Pvt. Ltd	. 	\nHyderabad.	 	\n&bull; 	Worked as a team leader with my duties including Assigni	ng the work to the fellow team 	\nmembers, discuss the work load with my manager and follow up with the team. 	 	\n&bull; 	Oversaw day to day operations and Monitor team performance. Always provided necessary \nsupport to the team whenever it required my attention, complet	ed the tasks in a given time 	\nframe and provided daily updates to manager at the end of day. 	 	\n&bull; 	Coordinated with Overseas Clients regarding the work requirement and also provided my inputs \nto them in simplifying the work process. 	 	\n&bull; 	Performed data analysis and data profiling using SQL queries. Performed DML Operations for \nInserting, Updating, Merging and Deleting records and also worked on DDL Operations for \nCreating, Altering and Dropping records. 	 	\n&bull; 	Worked on various SQL Functions &amp; S	tatements such as Select, Insert, Update, Delete, Joins, 	\nUnions, Group by etc. 	 	\n&bull; 	Worked on Database statements like Create Database, Drop Database, Alter Database etc.	 	\n&bull; 	Worked on an ETL application called 	Informatica.	 Using the ETL tool, i have extracted dat	a from 	\nsource system, transformation of this source data into the required format for target system \nand finally writing the data or loading into the target system. 	 	\n&bull; 	Well versed in Data Monitoring, Data warehousing and Data Management Concepts.	 	\n06	/20	16	 TO 0	1/20	19	 	\nData Analyst 	- Phoenix American Sales Focus Solutions India Pvt. Ltd.	 	\nHyderabad.	 	\n&bull; 	Worked on an in	-house application called Unify In which we maintain the data of individuals 	\nwho work as Financial Brokers and Investment Advisers  	 	\n&bull; 	I Import the Data fr	om our BAs, upload it in unify, and then we analyze it for any discrepancies. 	\nTheir data consists of their names, office addresses, telephone numbers and the firms in which \nthey were employed. I have used this application for deduping the data, merging of 	data, 	\nremoving the duplicate data. this data could be user name, addresses or firm names. 	 	\n&bull; 	Unify is a master database of Representative information which serves as a proactive approach \nfor maintaining up	-to-date registered Rep data. this application is int	ernally developed to keep 	\ndata current in all clients. 	 	\n&bull; 	I have provided many inputs in developing the unify database to ease the data representation \nand extraction process. made recommendations towards the development of new patches for \nUnify release. 	 	\n&bull; 	I h	ave served as the initial contact person for all Unify support queries. 	 	\n&bull; 	I have used Jira to keep track of the assignments and issues that seldom occur in Unify or MARS. \ncreated dashboards for multiple projects in Jira. 	 	\n&bull; 	Monitored the status of the work as	signments along with identifying the need for automation 	\nprocess that can result in quick resolution. 	 	\n&bull; 	Worked on MARS, which is a Sales and Marketing tool for the Asset Management Industry. it \nincludes data visualization and analytics. 	 	\n&bull; 	Performed data reco	nciliation, scrubbing, and deduping activities to ensure that our clients have 	\naccurate sales and asset data. 	 	\n&bull; 	My work also includes Removing corrupted data, performing final analysis to provide additional \ndata screening. Post analyzing the data, sent back	 reports to clients at the end of the day.\n\nSkills	 	\n&bull; 	SQL Database	  	\n&bull; 	Informatica	 	\n&bull; 	Team player	 	\n&bull; 	Excellent time management skills	 	\n&bull; 	Conflict Management	 	\n&bull; 	System administration	 &amp; Troubleshooting	 	\n&bull; 	Communication and public speaking	 	\n&bull; 	Data analytics	 	\n&bull; 	Data 	warehousing	 	\n&bull; 	Microsoft Excel	 	\nEducation	 	\n2008	 	\nHigh school	 - SSC	 (Sri Rama Krishna Public School)	 	\nKakinada	 	\n2008	-2010	 	\nIntermediate 	&ndash; MPC 	(Narayana Junior College)	 	\nKakinada	 	\n2010	-2014	 	\nBachelor&rsquo;s 	&ndash; Electronics &amp; Communication 	(Pydah College of Engineering	) 	\nKakin	ada	 	\n \nActivities	 	\n&bull; Books	 &amp; Novels 	&bull; Yoga	 &bull; Travel	 &bull; Cricket	 &bull; Chess', 2, 2, 1, 'Recruiter', 'Un-assigned', 'SL', 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-05-26 04:50:20', 0),
(349, 80, 1, NULL, NULL, '1_80_21233880786652bf8ce58cb_honeyfatima.pdf', 'honeyfatima.pdf', 'SO FT W ARE D EV ELO PER\nH O N EY  F A TIM A	\nWeb  D esig n  ( H TM L,  C SS,  J S )\nD esig n  T hin kin g\nW ir e fr a m e C re atio n\nD ata b ase  ( M yS Q L,  M S A cce ss)\nP ro ble m -S o lv in g\nT eam  w ork e r\nS tr o ng C om mun ic a tio n	\nS K IL L S\n+919910553362A -1 3/2 86,  B rijp uri,D elh i,  1 10094	 	ho neyfa tim a0 786@ gm ail.c o mI&#039;m  a  s o ft w are  d eve lo per w it h  o n-h an d  e xp erie n ce  in  L ara v e l,  M yS Q L\nan d  J a v a w it h  s p rin g b o ot.\nI h av e  a b o ut 6  m onth s o f e xp erie n ce  a n d  w ork e d  o n 3  p ro je cts  u n d er\ngu id an ce  o f m y s u p erio r a n d  t e am  m ate s.\nP R O FIL EE X PER IE N CE\nEA SY  L IF E  S T O RE	Data b ase  a d m in is tr a tio n\nA dm in  P an el	 	\nP ET  S ER V IC E	 	Data b ase  a d m in is tr a tio n	 	\nA dm in  P an el	 	\nV YA PA R K H ATA	D ata b ase  a d m in is tr a tio n	 	\n      		\nE D UCA TIO N\nIG N OUPurs u in gP O ST  G RA D U ATIO N  -  M CAIG N OUU N DER  G RA D U ATE -  B C ADeep  M em oria l P ub lic  S ch o ol12 T H  -  C BSE	\nDyamic website\nGD SHOPPING\nDynamic Website', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-05-26 04:50:20', 0),
(350, 80, 1, NULL, NULL, '1_80_1629145846652bf8ce5f16_mohdshahad.pdf', 'mohdshahad.pdf', 'MOH D S H AH AD	\nVija y N ag ar G hazia b ad  U tta r P ra d esh  \n8 077172001	 | 	s h ah ad 1932@ gm ail. c o m	\n 	\nP ER SO N AL D ETA IL S	\nD ate  o f B ir th  :  1 2/0 8/1 997\nLa n g uag e&nbsp; H in d i,E ng lis h &nbsp;\nN atio nalit y &nbsp; I n d ia n\nM arrie d  S ta tu s&nbsp; :  U nm arrie d	\nE X P ER IE N CE	\nUrg en tit s o lu tio n\n15 D ec 	-	\nP hp  D eve lo per\n&nbsp;P hp  b acke n d  d eve lo per	\nED UC AT IO N	\nSun d er D eep  E ng in eerin g  C olle g e D asn a G hazib ad\n2 020\nB .T ech  ( C om pute r S cie n ce  &amp;  E ng in eer)  \n6 .4  C G PA\nS  . H  I n te r C olle g e B ag hp at\n2 016\n12th  C la ss \n6 8  %\nG ove rn m en t H ig h S ch o ol\n2014\n10th  C la ss \n7 2%	\nT EC H NIC A L S K IL LS	\nH TM L ,C SS ,  J ava S crip t ,B oots tra p s\nP hp ,&nbsp;  M ys q l  ,&nbsp;  P do  p hp\nA ja x jq uery &nbsp;&nbsp;\nT o ols  -  L iv e  s e rv e r,  V s c o de	\nN ON  T EC H NIC A L S K IL LS	\nG ood C om mun ic a tio n a n d  C ord in atio n S kills &nbsp;\nS tr o ng  M ult it a skin g  A bilit y\nA bilit y  t o  m ake  d ecis io ns a n d  s o lv e  p ro ble m s&nbsp;\nG ood t e a m  p la ye r a n d  le a d ers h ip  q ualit y\n\nPRO JE C TS	\nA pexO ne\nS kills  u se d  P hp &nbsp;\nW here  u se r c a n  r e g is tra tio n a n d  s h are  r e fe rra l  a n d  g et r e w ard &nbsp;\nTera  M ath em atic s\nS kills  U se d  H tm l&nbsp;  ,C ss,  P hp\nM s w ord  E xc e l  C lo ne\nS kills  U se d  H TM L,  C SS,  J ava sc rip t&nbsp;\nC ru d  o pera tio n\nS kill  u se d  p hp ,  a ja x,j q uery &nbsp; ,m ys q l&nbsp;\nC re a te  p d f f o r m ed ic a l 	a p po in tm en t	\nS kill  u se d  p hp ,a ja x,j q uery  ,m ys q l&nbsp;	\nH OBBIE S	\nLea rn  N ew  t h in g s&nbsp;\nIn te rn et S urﬁ ng\nP la yin g  a n d  w atc h in g  C ric ke t&nbsp;	\nO BJE C TIV 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 o rg an iz a tio n\nD EC LA RAT IO N	\nI h ave  d ecla re d  t h at in fo rm atio n is  c o rre ct a n d  a ccu ra te &nbsp;', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-05-26 04:50:20', 0);
INSERT INTO `resume` (`id`, `screeningId`, `adminId`, `candidateId`, `candidateDetailsId`, `resumeName`, `resumeOriginalName`, `resumeContent`, `isSkillScreened`, `isResumeScreened`, `isCron`, `isCandidate`, `isStatus`, `candidateShortlist`, `isInterviewAssign`, `enableInterviewReport`, `gptLanguageId`, `interviewAssignDate`, `psychoAssignDate`, `interviewValidity`, `isPsychoAssign`, `psychoValidity`, `created`, `createdBy`) VALUES
(351, 80, 1, NULL, NULL, '1_80_163689206652bf8ce69f3_Nikhil_Yalla_Resume.pdf', 'Nikhil Yalla Resume.pdf', 'Nikhil	 Yalla	 | 8464813666	 | nikhilyall	a333	@gmail.com	 	\nProfessional Summary	 	\n● 	3.8 Years of Professional experience 	and 3 years of relevant experien	ce 	on Power BI Desktop, Power BI 	\nService	 and Process Automation.	 	\n● 	Having Good Experience on Power BI Desktop and Service Development and worked on the Power BI \nReports &amp; Dashboards. 	 	\n● 	Develop Power BI reports and effective Dashboards after gathering and translating end user requirements. 	 	\n● 	Imported data from multiple data 	sources into Power BI, like SQL, Excel, CSV etc. 	 	\n● 	Creating relationships between Tables, created calculated columns and measures using DAX Query.	 	\n● 	Having experience in creating different charts like Line chart, bar chart, table, matrix table, area chart, \nscattered chart, tree map. 	 	\n● 	Experience in creating different custom visualizations like Doughnut chart, waterfall chart, gauge chart, bar \nchart etc. 	 	\n● 	Experience in creating maps like filled map, shape map and having experience in using filters like page, \nvis	ual, report and drill through filters. 	 	\n● 	Comfortable in working with filters/calculated columns/measures/relationship and transformations of the \nEdit Query se	ction. 	 	\n● 	Lead Operations and Automation team for 	Worldwide Quota Reconciliations for Microsoft sellers.	 	\n● 	Skilled in 	Agile way of working	 and delivering 	High	-Quality work	 on tight schedules.	 	\n● 	Possess Problem	-Solving Skills, ability to follow industry standards and procedures.	 	\n● 	Strong communication and Interpersonal skills.	 	\n● 	Capable of mastering new technologies quickly.	 	\n● 	Team player	, focused on working towards achieving team/pr	oject success.	 	\nExperience	 	\nEmployer: Tata Consultancy Services (TCS)	 	\nProject 	&ndash; Data	 Insights and Growth	 (DIG)	 	\nDuration	 	             	: December	 202	0 To till date	 	\nClient	  	    	: Microsoft	 	\nRole	 	 	 	: Power Bi Developer	 	\nTools	 	 	 	: Power Bi Desktop, Power Bi 	Services	 	\nKey Responsibilities	 	\n● 	As a Power Bi Developer my responsibilities are to understand and analyze the requirements from client. 	 	\n● 	Independent Communication with client about the progress of task. 	 	\n● 	Worked on fetching data from various sources like SQL,	 SharePoint, Web and Excel.	 	\n● 	Developing various measures, calculated columns and perform data enhancement using Query editor.	 	\n● 	Completely responsible of creating and developing Visualization as per the requirement. 	 	\n● 	Involved in Requirements gathering, data a	nalysis from the upstream system	. 	\n● 	Publishing the reports to service and schedule regular and weekly refresh to maintain data freshness.	 	\n● 	Implemented RLS. 	 	\n● 	Expert in providing the Security to the Power BI Dashboards/Reports.	 	\n● 	Sharing the 	Dashboards/Reports among the members within the organization.	 	\n● 	Monitoring Dashboards and submitting report to client.	 	\nPower Bi Developer\n\n● 	Involved in Testing to ensure and avoid the UAT &amp; Production Issues	. 	\n● 	Participating in Daily Scrum meeting, walkthrough meeting with Team Me	mbers, Lea	ds and PMs.  	\n \nProject &ndash; Worldwide Incentive Compensation (WWIC)	 	\nDuration 	         	    : May	 2019 To 	November	 202	0 	\nClient	  	    	: Microsoft	 	\nRole	 	 	 	: Information Processing Specialist	 	\nTools	 	 	 	: Power Bi Desktop, Power Bi Services, Visual 	Studio, SSMS	, SNOW	 	\nKey Responsibilities	 	\n● 	Acted as the Lead for Quota Reconciliations across all regions. 	 	\n● 	Analyzed and presented the data to stakeholders that helped in making important decisions.	 	\n● 	Participate	d in client discussions and	 created dashboard	s as per the requirements	.  	\n● 	Automated the manual process which saved time and improved accuracy. 	 	\n● 	Designed  and  Developed  the  Power  Bi  Reports  for  analyzing  the  status  of  the  Microsoft  seller&rsquo;s  data  in  a \nweekly ma	nner. 	 	\n● 	Collaborated with engineering and product delivery teams to understand product and project requirements to \ntest according to their requirements.	 	\n● 	Participating in 	developing internal tools for process improvements.	 	\nTechnical Skills	 	\n&bull; 	Power Bi	 Desktop, 	Power Bi Services	 	\n&bull; 	DAX 	 	\n&bull; 	SQL	 Server	 	\n&bull; 	C#	 	\nProfessional Recognition	 	\n● 	Received Star Performer appreciation award thrice from client for best work delivered. 	 	\n● 	Received Emerald Go Getter award	 (Award given to Best Performer for 6 Months).	 	\nC	ertifications	 	\n● 	Microsoft Data Analyst Associate Certification	 (DA	-100	/PL	-300	) 	\n● 	Azure 	Fundamentals Certification (AZ	-900)	 	\nEducation	 	\n&bull; 	B.Tech (ECE) from 	S R K R Engineering College, 	Andhra University	 with 78.60% in 2019	 	\n&bull; 	Intermediate from 	Aditya Junior College	 with 96% in 2015	 	\n&bull; 	SSC from 	Aditya Public School	 with 95 % in 20	13	 	\n \nD	eclaration	 	\nI hereby declare that the above information is true to the best of my knowledge and belief.  	 	\n 	 	 	 	 	 	 	  	\n 	 	 	 	 	 	 	 	                         	Nikhil Y', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-05-26 04:50:20', 0),
(352, 80, 1, NULL, NULL, '1_80_1987434096652bf8ce73ee_Nishchay_sinha.docx', 'Nishchay_sinha.docx', '\r\nNishchay Sinha\r\n-12701022894EXPERIENCE\r\n00EXPERIENCE\r\n-1270259624EDUCATION\r\n00EDUCATION\r\nMale, 23 Years | +91 7050029999| nischey.me008@gmail.com|chandigarh                          \r\nBachelors in Computer Application 2018-2021 Chandigarh University, Mohali 6.66 CGPA\r\nCBSE (Class XII) 2013-2015 Subhash Public School,Giridih Jharkhand 58%\r\nData Analyst, NuvoRetail, New Delhi  (internship 3 Months)                                                                                              Aug 2021- Nov-2021\r\nAnalysed data and drive insights from appropriate managerial facilitation.\r\nGathering Data from different sources and performed ETL on the same.\r\nManaged Data in Azure Database.\r\nUse Python,Vs code,Azure Studio,Selenium web driver,pandas.\r\nAmevatech Research Pvt. Ltd.   (3 mon Internship + 4 mon Full Time)                                                                                                       March 2022- Sep 2022\r\nMade New Forms and Validating Them using php Validation and Javascript Validation.\r\nStoring Employees Data In Database \r\nMade Many modules In CMS\r\nUse Php Session and Cookies.\r\nMade Lead Management Software.\r\n-1270225425PROJECTS\r\n00PROJECTS\r\n\r\nMade a CRUD application in Python Django                                                                                 May 2019- July 2019\r\n0433070SKILLS\r\n00SKILLS\r\n\r\nAdding Student Data,editing Studing ,View student details.\r\nTech Skills - C++ , Pandas, NumPy, Machine Learning, Computer Vision, Python, Azure Database\r\nSoft Skills - Problem solving, Creative thinking, Quick Learning\r\n-1270238125TRAININGS AND CERTIFICATIONS\r\n00TRAININGS AND CERTIFICATIONS\r\nLanguage - English and Hindi.\r\n', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-05-26 04:50:20', 0),
(353, 80, 1, NULL, NULL, '1_80_13418769466652bf8ce7a86_NRakesh_CV.pdf', 'NRakesh CV.pdf', 'www.resumekraft.com\n\nwww.resumekraft.com', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-05-26 04:50:20', 0),
(354, 80, 1, NULL, NULL, '1_80_14704416506652bf8ce81cd_Power_BI_5_Years_Noel_Samuel.pdf', 'Power_BI_5_Years_Noel_Samuel.pdf', 'Name: 	- Noel Samuel	 	\nContact No: 	- +91 9922137457	 	\nEmail ID: 	- noel.samuel30@gmail.com	 	\n 	\nPermanent Address: 	- 64, New Gandhi Layout, Behind Jaffar Nagar, Nagpur	-440013.	 	\n 	\n 	CAREER OBJECTIVE:	 To secure a challenging position in a reputable organization 	\nto expand my learnings, knowledge, 	and skills. Secure a 	\nresponsible	 career	 opportunity to fully utilize my training and skills, while making a 	\nsignificant contribution to the success of the compa	ny.	 	\n \n 	\nWORK EXPERIENCE AND RESPONSIBILITIES:	 	\n \n 	\n    	Company Name: 	- Larsen and Toubro Infotech	 	\n    	Designation:	 - Senior Data Engineer	 	\nDuration:	 - Nov 02, 2021 to	 Present.	 	\n \n	 Cognos	-PBI Migration	| Power BI	 Consultant.	 	\nDomain:	 Manufacturing	 	\nClient	: Scania	 	\nProject 	Description	: Objective  was  to 	do  a  lift	-shift  of  all  Cognos  report  to  Power  BI.  Data 	\nSource used was Tabular model and connection method used was Live connection.	 	\nTools: 	Microsoft Power BI, SQL Server, 	Oracle SQL Developer, SSAS Tabular	 	\nResponsibilities:	 	\n 	\n Created Tabular model in SSAS.	 	\n Analyzed Cognos&rsquo; Reports.	 	\n Understood model of Cognos Reports using Framework Manager.	 	\n Established connection with Data Source in Analysis Services.	 	\n Created calculated column and measures in SSAS.	 	\n Installed 	different drivers of 32	- bit and 64	-bit for Oracle Connection.	 	\n Installed various version of Visual studio with correct version.	 	\n Solved issues related to connection in Visual Studio.	 	\n Created report wireframe for Power BI Reports.	 	\n Helped in creating Power BI	 Report theme.	 	\n Developed more than 20	 reports in Power BI which was migrated from Cognos.	 	\n Created job in Database server to refresh the Analysis server model.	 	\n Connected to Analysis server to PBI for creation of reports.\n\nCompany Name:	 - Nice Software Solutions. 	\nDesignation:	 - Power BI	 Consultant.	 	\nDuration:	 - June 03, 2019 to	 Sep 06, 2021.	 	\n \n	 CWG Dashboard	| Power BI	 Consultant.	 	\nDomain:	 OTC 	Process/Brewery	 	\nProject 	Description	: Objective  was  to  bring  all  the  repo	rting  of  zones  under  one  common 	\ndashboard and bringing in new visibility for the stakeholders.	 	\nTools: 	Microsoft Power BI, SQL Server, SharePoint, Excels	 	\nResponsibilities:	 	\n 	\n Hands	-on exp	erience in creating Power BI	 reports.	 	\n Understanding business requirements for different zones and implementing the same in the \nreports.	 	\n With the help of bookmark and selection panel created toggle	 switch.	 	\n Experience in using Power Query editor, used functi	ons like split, group by, data	 type 	\nchange.	 	\n Experience in using advance	 editor.	 	\n Knowledge of using RLS and giving access to specific	 users.	 	\n Connected to data sources such as excel, sql server, azure sql database, sharepoint,	 power 	\nbi dataset,	 dataflow.	 	\n With the help of python connected to data source in Power	 BI.	 	\n Used R script visual to plot graphs in Power	 BI.	 	\n Handled Azure for uploading data in blob storage, used data factory for importing data and \ncreate database based on excel file.	 	\n Strong planner an	d organizer with demonstrated ability to lead small to large size teams; 	\nresource and effort estimation for projects.	 	\n Implemented Panel Selectors in the project with the help of Bookmark.	 	\n Created DAX to generate computed columns and measures using function	s like FORMAT, 	\nRELATED, CALCULATE, SELECTEDVALUE.	 	\n Created landing page with the help of page navigation and	 buttons.	 	\n Created usage report to check how many users are accessing the report with data flow	 as the 	\ndata	 source.	 	\n Toggle button created to see Month	ly and Weekly view with bookmark &amp; selection	 panel.	 	\n Successfully worked on Azure SQL DW, integrating the same with Power BI.	 	\n Created complex reports using data source as Azure SQL Database server.	 	\n Knowledge on creating Azure DB servers and configuration 	settings.	 	\n Strong planner and organizer with demonstrated ability to lead small to large size teams; \nresource and effort estimation for projects.	 	\n Creation of SOP&rsquo;s, use cases, and Software Requirement Specification (SRS) document.	 	\n Extracting data from datab	ase with the help of SQL.	 	\n Used Table, Matrix, Bar, Card, Gauge, Slicers visualizations.	 	\n Worked on Custom Visualizations like multi slicer and Hierarchy slicer.	 	\n Successfully connected Azure SQL Database to Power BI.\n\n	 Usage Metrics Report	| Power BI	 Consultant.	 	\nDomain:	 OTC	 	\nProject 	Description	: Report  to  understand  adoption  of  the  reports.  Report  created  to  understand  how 	\nmany users are using the report. Analysis to check which users are super users. 	 	\n      	Too	ls: 	Microsoft Power BI, DataFlow	 	\nResponsibilities:	 	\n 	Calculated week on week views and viewers of the report	.  	\n 	Imported data from 	Data Flow	. 	\n 	Week on week percentage change.	 	\n 	Created waterfall chart to show initial number of users and total number of users	. 	\n 	Us	ed Top N filter selection on visual to display 	top users of the report.	. 	\n 	\n 	\n 	\n	 Nice Imports	| Power BI	 Consultant.	 	\nDomain:	 Shipment Industry	 	\nProject 	Description	: Business related to shipment of paper and pulp. Industry focusing on recycle and 	\nreuse any grade of paper. Project that gives deep insight into the importing business performance w.r.t. \ncountry wise order count, order count by port, country wise revenue ge	nerated. 	 	\n      	Tools: 	Microsoft Power BI, Azure	 	\n \n 	\nResponsibilities:	 	\n 	Created and configured Azure SQL server, DW and tables. 	 	\n 	Imported data from MS Excel, MS Access and CSV to Azure SQL DW.	 	\n 	Integrated Azure with power BI and generated reports as per the re	quirement.	 	\n 	Created Different Visualization with dynamic targeting.	 	\n 	Implemented Panel Selectors in the project with the help of Bookmark.	 	\n 	Created DAX to generate computed columns and measures using functions like FORMAT, \nRELATED, CALCULATE, SELECTEDVALUE.	 	\n 	Created DAX expressions to calculate no of Split invoices, percentage of split invoices.	 	\n 	Generated computed tables in Power BI using DAX.	 	\n 	Created multiple dashboards such as Summary, Shipment Details and Customer Details \nwith each navigation with the help 	of Bookmarks.	 	\n 	Imported custom visualization from Power BI marketplace and used it in the report.\n\n	 Pharmacy	| Power BI	 Consultant	 	\nDomain: 	Pharma	 	\nProject  Description	:  The  Power  BI	-based  solution  will  show  data  based  on  Sales,  Field  Activity  and 	\nMarket	 for field	-based users which can be access from mobile device	.  	\nTools: 	Power BI (Mobile + Web) and Azure	 	\nResponsibilities:	 	\n 	Involved in understanding the business requirement	 	\n 	Used Azure SQL DWH and Blob storage to store data. 	 	\n 	Created dashboards from 	reports as well as from the insights	. 	\n 	Created customize tooltip.	 	\n 	Bookmark the pages and link it to button or image etc. from action property.	 	\n 	Used chicklet slicer for metric selector.	 	\n 	Implemented all types of filters visual, page level and report level.	 	\n 	Im	plemented prompts using parameter.	 	\n 	Worked on row level security for customized access.	 	\n 	\n	 Banking	| Power BI	 Consultant	 	\nDomain: 	Banking	 	\nProject  Description	:  Client	 is 	the	 leading  credit  card  provider  that  gets  thousands  of  credit  card 	\napplicants every year. B	ut in the past few years, it has experienced an increase in credit loss.	 With the 	\nhelp of predictive analysis using Python in Power BI the client wants to mitigate risk by acquiring the \nright customers. Used Python script editor to import .csv file into Po	wer BI. 	 	\nTools: 	Microsoft Power BI And Azure	 	\n 	\n \nResponsibilities:	 	\n 	Worked on predictive analysis and linear regression to understand credit score of \ncustomers.	 	\n 	Installed various libraries such as Anaconda, Matplotlib and import os.	 	\n 	Created Azure 	Datafactory to integrate cloud	-based platform for data	 from and to on	-	\npremise, on	-cloud, and hybrid sources and destinations. 	 	\n 	Imported .csv file with the help of script editor into Power BI.	 	\n 	Used grid and graph combination to display customer against thei	r details.	 	\n 	Used various graphs to precisely display which 	the right customers are	 having good credit 	\nscore.	 	\n 	Plotted graphs by using Python language against various metrics.	 	\n 	Used checklist slicer for metric selector.	 	\n 	Implemented all types of filters visual,	 page level and report level.	 	\n 	Published the report on Power BI service and gave access to various users.\n\nCompany Name: 	- Excellon Software. 	\nDesignation: 	- BI 	Consultant. 	 	\nDuration: 	- Aug 03, 2015 to July 25, 2017.	 	\n 	\nPlace: 	- Nagpur	 	\n 	\n 	Creation of Power BI 	reports.	 	\n 	Monthly update of the reports.	 	\n 	Maintaining the reports and dashboards at service level.	 	\n 	Sharing the reports with the end users.	 	\n 	Giving access of the reports to different users.	 	\n 	Creation of SOP&rsquo;s.	 	\n 	Giving training to new joiners.	 	\n 	Used visuals like m	ap, water gauge, table, matrix, bar chart.	 	\n 	Sending monthly and billing reports to client.	 	\n 	Creation of user guides for solving particular issues and sharing it with team.	 	\n 	\n 	\nWorking Exposure: 	- 	\n 	\n 	Good amount of exposure in Power BI, Azure Dev	 Ops.	 	\n 	Experience 	of working in agile	 methodology.	 	\n 	Exposure in handling ad hoc	 requests.	 	\n 	Handled a team of more than 3 people to deliver power bi	 projects.	 	\n 	Played a role in automating the process of DB refresh and Power BI schedule	 refresh.	 	\n 	Created management view for 	mobile for super uses of the	 report.	 	\n \n \n \n \n \n \n \n \n \n \nPower BI, SSAS, Tabular, Live Connection, #power bi, #sql, #analysis #oracle oracle\n\nEDUCATIONAL QUALIFICATIONS: 	- 	\n \n 	\nCourse	 	Year of Passing	 	Name of the \nInstitute	 	University/ Board	 	\nMBA (Operations+ 	\nMarketing)	 	2018	-20	19	 	RCOEM	 	RTMNU	 	\nB.E (Computer Science 	\n&amp; Engineering)	 	2010	-2014	 	G.N.I.E.T	 	RTMNU	 	\n \n 	\nCOMPUTER LITERACY:	 	\n 	\n 	Microsoft Power BI test by	 LinkedIn.	 	\n 	Certification of Power BI by Leanardo	 Karpinski.	 	\n 	SQL. (Certification from	 Unisoft)	 	\n 	MS	-Excel.	 	\n 	Google Digital Unlock Certification.	 	\n 	Google Analytics Beginner Certification.	 	\n 	Google Analytics 	Advanced Certification.	 	\n 	HTML.	 	\n 	\nPERSONAL DETAILS:	 	\nFather&rsquo;s Name: Lucas \nMother&rsquo;s Name: Mercy \nDate of Birth: 30/09/1992 \nGender: Male.	 	\nNationality: Indian.	 	\nLanguages Known: English, Hindi, Marathi, Telugu.	 	\nPermanent Address: 64, New Gandhi Layout, Behind Jaffa	r Nagar, Nagpur	-440013.	 	\n 	\nDECLARATION:	 	 	\nI, the undersigned hereby declare that the above information is true to the best of my knowledge.	 	\n 	\nPlace:	 	Date:	 	\nBusiness intelligence, azure, sql, data analytics, computer science, data modelling, data wareshousing', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-05-26 04:50:20', 0),
(355, 80, 1, NULL, NULL, '1_80_1168844636652bf8ce89d5_Pratik_Test_Engineer.pdf', 'Pratik Test Engineer.pdf', 'Pra tik  T h am ake  \nTe st E ng in eer \nSo ft w are  T e st E ng in eer w it h  4 + y e ars  e xp erie nce  i n  S o ft w are  T e stin g  u nd er w in d ow s e nvir o nm ent w it h\nexce lle nt a n aly tic a l a n d  d iv e rs iﬁ ed  e xp erie nce  i n  m an ual a n d  a u to m atio n t e stin g  \nof w eb  b ase d\nap plic a tio n. S o lid  u nd ers ta n d in g  i n  S o ft w are  D eve lo pm ent L if e  C ycle (S D LC ), S o ft w are  T e stin g  L if e  C ycle\n(S T LC ), B ug  l if e  c y cle  a n d  d iﬀ ere nt t e stin g  p ro ce d ure s \npra tik 9 4q a@ gm ail .c o m  \n+91-7 020998919 \nPune, I n d ia  \nWORK  E X PER IE N CE \nTe st E ngin eer \nZS A sso cia te s \n11/2 021 -  P re se n t\n, \n  Pune \nRevie w ed  b usin ess r e q uir e m ent d ocu m ents  w it h  b usin ess\ndeve lo pm ent t e am  t o  u nd ers ta n d  t h e a rc h it e ctu re  a n d\nfu nctio nalit y  o f t h e a p plic a tio n. \nPla n ned , S ch ed ule d , D eve lo ped  a n d  E xe cu te d  t h e q ualit y\nassu ra n ce  t e stin g  a ctiv it ie s. \nDeve lo ped  t e st d ocu m ents  s u ch  a s \nTe st S tra te g y, T e st\nSce nario s, T e st C ase s, T e st S u m mary  R ep ort  a n d  B ug  R ep ort .\nDeve lo ped  A uto m atio n ( C ucu m ber) f ra m ew ork  f o r U I a n d\nData b ase  A uto m atio n t e stin g  .  \nSe le niu m , C ucu m ber, T e stN G, P ostm an , P ostg re SQ L, J IR A . \nAsso cia te  T e st E ngin eer \nCalc u e I n fo  S e rv ic e s \n12/2 018 -  1 1/2 021\n, \n \nPerfo rm  M an ual a n d  A uto m atio n t e stin g . \nResp onsib le  f o r c re ate  a u to m atio n t e st s c rip t f o r s e le cte d\nTe st c a se s i n  t h e T e stN G f ra m ew ork . \nDefe cts , D eve lo p a n d  M ain ta in  m an ual a n d  a u to m ate d  t e st\npro ce sse s. \nPerfo rm  t h ro ug h R ete stin g  a n d  R eg re ssio n t e stin g  w hen\nbug s a re  r e so lv e d . \nPre p are d  B ug  S ta tu s r e p ort  a n d  s e nd  i t  t o  t h e t e am  o n\ndail y /w eekly  b asis . \nSe le niu m , T e stN G, P ostm an , J IR A . \nED UCATIO N \nBE ( B ach elo r o f E ngin eerin g )  \nGenesis  I n stit u te  o f T e ch no lo gy \n06/2 013 -  0 6/2 016\n, \n  Kolh apur \nDip lo m a \nD.Y .P atil  P oly te ch nic  \n06/2 009 -  0 4/2 013\n, \n  Kolh apur \nSK IL L S  \nAuto m atio n T e stin g  \nSe le niu m  \nMan ual T e stin g  \nMobil e  T e stin g  \nAPI \nSD LC  \nPostg re SQ L \nJIR A \nJav a \nIn te g ra tio n T e stin g  \nTe stN G \nCucu m ber \nTe st C ase  D esig n \nFu nctio nal T e stin g  \nPostm an  \nSan it y  T e stin g  \nPag e O bje ct M odel \nAgil e  \nTe st C ase  D esig n \nReg re ssio n T e stin g  \nDesig n T e st S tra te g y D oc \nSe le niu m  W eb D riv e r \nMave n \nST LC  \nAPI T e stin g  \nPR O FE SSIO NAL P R O JE C TS \nJO TS\n ( 0 9/2 022 -  P re se nt)\n \nPeer T o  P eer P ro gra m  D esig ner\n ( 1 2/2 021 -  0 9/2 022)\n \nCit y  I n d ex W eb  T ra d er S e cu rit ie s\n ( 0 2/2 020 -  1 1/2 021)\n \nRoam in g B il lin g S yste m\n ( 1 2/2 018 -  1 2/2 019)\n \nIN TER EST S \nCric k e t \nMusic  \nTra ve llin g  \nAch ie ve m en ts/T a sk s \nAch ie ve m en ts/T a sk s', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-05-26 04:50:20', 0),
(356, 80, 1, NULL, NULL, '1_80_8913317296652bf8ce904c_Shailja_Tyagi_CV.docx', 'Shailja Tyagi_CV.docx', '\r\nShailja Tyagi Sr. Business Analyst \r\nHCL Technologies  Email:   shailjatyagi28@gmail.comPhone: +91-9540063311\r\nPROFESSIONAL SUMMARY\r\nExperienced Business Analyst with overall 11+ years&rsquo; experience as 6+ years&rsquo; in analyzing business requirements in software development and 5 years&rsquo; track record in Operations\r\nProfile Summary Business Analysis &ndash; Planning &amp;amp; Scoping, AS IS &amp;amp; TO BE Process Modelling, Requirement Analysis &amp;amp; Documentation, managing backlog, prioritizing feature scope, defining Use stories, Manage Stakeholder&#039;s Sign offs.\r\nWell versed with SDLC methods &ndash; Agile and waterfall, experienced in requirements gathering, Group Discussions and Use Cases. Experienced with creating and modifying process flow diagrams and Use Case Diagrams. Excellent communication, analytical, interpersonal, and presentation skills; highly adept at handling the expectations of Multiple Stakeholders\r\nScrums/ Project Management &ndash; Performed scrum master/project manager role and successfully delivered the release on time\r\nTransition Management &ndash; Project planning, Application risk assessment, Transition Go Live\r\nOperations &ndash; Assisting Ops delivery and change management, Improvement projects by using LEAN quality tools, Automations of reports to enhance productivity and efficiency, analyzing processes and recommending modifications to enhance operational efficiency\r\nIndustry/ Domain  Industrial Air Condition Software Product (HVAC)\r\nClinical Trial Management\r\nApplication Transition Management\r\nOperation delivery and change management\r\nEducation  Graduated in BSC-IT from Kuvempu University (Year: 2012)\r\nGNIIT from NIIT Ltd. (Year)\r\nTools Exposure in Visio for requirement modelling, Azure- VSTS, JIRA, Top Team, Kanban Board, HP ALM, SNOW, GCRS, Business Object, Cognos 8\r\nCurrent Organization HCL Technologies\r\nRole Product Owner cum Business Analyst Duration Apr&rsquo;15 &ndash; Till Date\r\nKEY PROJECT DETAILS\r\nClient Name  Johnson Controls Hitachi - Japan Development Methodology Agile and Waterfall\r\nRole Product Owner cum Business Analyst  Duration Jan&rsquo;19 &ndash; Till Date\r\nProject 1 Commercial App (Agile -Jan&rsquo;19 till Date) Project 2 Residential App (Waterfall -Aug&rsquo;19 &ndash; Till Date)\r\nResponsibilities  Collaborate with business users, product owners and business partners to gather and identify requirements and further define and document requirements.\r\nLead requirements discussion/review sessions with users, vendors, and the partners to further refine/scope requirements.\r\nAnalyze business requirements by doing a research work on To-Be proposed solutions to business teams by understanding the competitors&rsquo; applications, current market expectations from the product. \r\nPrioritize the scope based on product strategy.\r\nManage and prioritize backlog items on each iteration.\r\nCreate Use cases, user stories by capturing requirements from multiple stakeholders and getting signed off on the same in timely manner.\r\nAssist in planning, estimates, testing and rollouts of new software release and&nbsp;establish critical project related milestones, and participate in quality assurance.\r\nSupported in user acceptance of a release or feature, and provide value management reporting\r\nInvolved in solution design discussions to improve system usability/UI experiences.\r\nResponsible for delivering status reports to client as and when required.\r\nKey Achievements Received appreciation from client\r\nClient Name Q2 Solutions Development Methodology Agile\r\nRole Business Analyst &ndash; Clinical Trial Management Duration Apr&#039;18 &ndash; Jan&rsquo;19\r\nResponsibilities  Working in capacity of business analyst for Q2 Solution and managing and developing the LTMS application used for clinical trials laboratories services\r\nPlan execute and manage the integration of new applications into existing network infrastructure, systems &amp;amp; software throughout the enterprise\r\nGathering requirements and creating user stories and managing requirements in top team\r\nManaging the scoping of requirements and discussing the same with different stakeholders\r\nStepped up and played scrum master/project manager role when project was short of resources\r\nManaging daily calls and reporting on status on weekly basis to client\r\nKey Achievements Received appreciation from Senior BA(client) and Project Manager/Scrum Master\r\nClient Name UBS Bank Development Methodology Agile\r\nRole Business Analyst - Application Transition Management Duration Apr&#039;15 &ndash;Mar&rsquo;18\r\nResponsibilities  Working as a business analyst for UBS and managing applications risk assessment for finance stream\r\nRequirement planning &amp;amp; management &ndash; Prepare plan for gathering requirement &amp;amp; delivering within milestones\r\nApplication scoping, Requirement gathering and documentation, Elicitation using multiple techniques- User discussions, System documentation, meetings, etc.\r\nLiaison between business &amp;amp; team, stakeholder management, governance reporting\r\nResponsible for overall application Risk Assessment\r\nInvolvement in application transition Go Live\r\nWeekly project reporting\r\nKey Achievements Managed SLA&rsquo;s &amp;gt;95% transactions for all projects within timeframe\r\nValue idea creation of approx. US $ 15K in cost savings per annum &amp;amp; process improvements\r\nReceived &ldquo;Live Wire&rdquo; Certification &ndash; 2Q17, 3Q17\r\nPrevious Organization  Wipro Ltd.\r\nRole Analyst - Asset Data Management &amp;amp; Reporting Duration Dec&#039;09 - Apr&#039;15\r\nResponsibilities  Possess comprehensive understanding of database management systems\r\nInteracting with management in implementation of business, process, and technology improvements\r\nPlanning, implement quality and process improvement initiatives and UAT testing for production environment for enhance productivity\r\nPreparing data for a Dashboard (ORB) and other related reporting in a timely, accurate and consistent format/manner\r\nAnalyze monthly, Quarterly and Annual reporting requirements &amp;amp; prepare month-on-month &ldquo;Trend &amp;amp; Gap analysis&rdquo; &amp;amp; forecasting reports\r\nPublishing the documents or reports on intranet web page\r\nReporting sustainability performance against the KPIs for the business sector \r\nAnalyzed data in case of anomalies and carried out quality checks for the reports\r\nKey Achievements Lean Certified for Value idea creation for process improvements &ndash; Jun&rsquo;14\r\nReceived &ldquo;Star of the Month&rdquo; for performance - Sep&rsquo;14, Jul&rsquo;14, Jun&rsquo;14, May&rsquo;14, Jan&rsquo;14\r\nReceived &ldquo;Star of the Quarter&rdquo; for performance &ndash; 2Q12, 3Q14\r\nReceived &ldquo;Letter of Appreciation&rdquo;- Oct&#039;12, Mar&#039;13\r\nPromoted from &ldquo;Officer&rdquo; to &ldquo;Sr. Officer&rdquo; - Sep&rsquo;12\r\nPERSONAL DETAILS\r\nDate of Birth 28th Jun&rsquo;91\r\nMarital Status Single\r\n', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-05-26 04:50:20', 0),
(357, 81, 1, 4, 13, '1_81_4_8110027236652c0832c7a1_Shailja_Tyagi_CV.docx', 'Shailja Tyagi_CV.docx', '\r\nShailja Tyagi Sr. Business Analyst \r\nHCL Technologies  Email:   shailjatyagi28@gmail.comPhone: +91-9540063311\r\nPROFESSIONAL SUMMARY\r\nExperienced Business Analyst with overall 11+ years’ experience as 6+ years’ in analyzing business requirements in software development and 5 years’ track record in Operations\r\nProfile Summary Business Analysis – Planning &amp; Scoping, AS IS &amp; TO BE Process Modelling, Requirement Analysis &amp; Documentation, managing backlog, prioritizing feature scope, defining Use stories, Manage Stakeholder\'s Sign offs.\r\nWell versed with SDLC methods – Agile and waterfall, experienced in requirements gathering, Group Discussions and Use Cases. Experienced with creating and modifying process flow diagrams and Use Case Diagrams. Excellent communication, analytical, interpersonal, and presentation skills; highly adept at handling the expectations of Multiple Stakeholders\r\nScrums/ Project Management – Performed scrum master/project manager role and successfully delivered the release on time\r\nTransition Management – Project planning, Application risk assessment, Transition Go Live\r\nOperations – Assisting Ops delivery and change management, Improvement projects by using LEAN quality tools, Automations of reports to enhance productivity and efficiency, analyzing processes and recommending modifications to enhance operational efficiency\r\nIndustry/ Domain  Industrial Air Condition Software Product (HVAC)\r\nClinical Trial Management\r\nApplication Transition Management\r\nOperation delivery and change management\r\nEducation  Graduated in BSC-IT from Kuvempu University (Year: 2012)\r\nGNIIT from NIIT Ltd. (Year)\r\nTools Exposure in Visio for requirement modelling, Azure- VSTS, JIRA, Top Team, Kanban Board, HP ALM, SNOW, GCRS, Business Object, Cognos 8\r\nCurrent Organization HCL Technologies\r\nRole Product Owner cum Business Analyst Duration Apr’15 – Till Date\r\nKEY PROJECT DETAILS\r\nClient Name  Johnson Controls Hitachi - Japan Development Methodology Agile and Waterfall\r\nRole Product Owner cum Business Analyst  Duration Jan’19 – Till Date\r\nProject 1 Commercial App (Agile -Jan’19 till Date) Project 2 Residential App (Waterfall -Aug’19 – Till Date)\r\nResponsibilities  Collaborate with business users, product owners and business partners to gather and identify requirements and further define and document requirements.\r\nLead requirements discussion/review sessions with users, vendors, and the partners to further refine/scope requirements.\r\nAnalyze business requirements by doing a research work on To-Be proposed solutions to business teams by understanding the competitors’ applications, current market expectations from the product. \r\nPrioritize the scope based on product strategy.\r\nManage and prioritize backlog items on each iteration.\r\nCreate Use cases, user stories by capturing requirements from multiple stakeholders and getting signed off on the same in timely manner.\r\nAssist in planning, estimates, testing and rollouts of new software release and establish critical project related milestones, and participate in quality assurance.\r\nSupported in user acceptance of a release or feature, and provide value management reporting\r\nInvolved in solution design discussions to improve system usability/UI experiences.\r\nResponsible for delivering status reports to client as and when required.\r\nKey Achievements Received appreciation from client\r\nClient Name Q2 Solutions Development Methodology Agile\r\nRole Business Analyst – Clinical Trial Management Duration Apr\'18 – Jan’19\r\nResponsibilities  Working in capacity of business analyst for Q2 Solution and managing and developing the LTMS application used for clinical trials laboratories services\r\nPlan execute and manage the integration of new applications into existing network infrastructure, systems &amp; software throughout the enterprise\r\nGathering requirements and creating user stories and managing requirements in top team\r\nManaging the scoping of requirements and discussing the same with different stakeholders\r\nStepped up and played scrum master/project manager role when project was short of resources\r\nManaging daily calls and reporting on status on weekly basis to client\r\nKey Achievements Received appreciation from Senior BA(client) and Project Manager/Scrum Master\r\nClient Name UBS Bank Development Methodology Agile\r\nRole Business Analyst - Application Transition Management Duration Apr\'15 –Mar’18\r\nResponsibilities  Working as a business analyst for UBS and managing applications risk assessment for finance stream\r\nRequirement planning &amp; management – Prepare plan for gathering requirement &amp; delivering within milestones\r\nApplication scoping, Requirement gathering and documentation, Elicitation using multiple techniques- User discussions, System documentation, meetings, etc.\r\nLiaison between business &amp; team, stakeholder management, governance reporting\r\nResponsible for overall application Risk Assessment\r\nInvolvement in application transition Go Live\r\nWeekly project reporting\r\nKey Achievements Managed SLA’s &gt;95% transactions for all projects within timeframe\r\nValue idea creation of approx. US $ 15K in cost savings per annum &amp; process improvements\r\nReceived “Live Wire” Certification – 2Q17, 3Q17\r\nPrevious Organization  Wipro Ltd.\r\nRole Analyst - Asset Data Management &amp; Reporting Duration Dec\'09 - Apr\'15\r\nResponsibilities  Possess comprehensive understanding of database management systems\r\nInteracting with management in implementation of business, process, and technology improvements\r\nPlanning, implement quality and process improvement initiatives and UAT testing for production environment for enhance productivity\r\nPreparing data for a Dashboard (ORB) and other related reporting in a timely, accurate and consistent format/manner\r\nAnalyze monthly, Quarterly and Annual reporting requirements &amp; prepare month-on-month “Trend &amp; Gap analysis” &amp; forecasting reports\r\nPublishing the documents or reports on intranet web page\r\nReporting sustainability performance against the KPIs for the business sector \r\nAnalyzed data in case of anomalies and carried out quality checks for the reports\r\nKey Achievements Lean Certified for Value idea creation for process improvements – Jun’14\r\nReceived “Star of the Month” for performance - Sep’14, Jul’14, Jun’14, May’14, Jan’14\r\nReceived “Star of the Quarter” for performance – 2Q12, 3Q14\r\nReceived “Letter of Appreciation”- Oct\'12, Mar\'13\r\nPromoted from “Officer” to “Sr. Officer” - Sep’12\r\nPERSONAL DETAILS\r\nDate of Birth 28th Jun’91\r\nMarital Status Single\r\n', 2, 2, 1, 'Candidate', 'Assigned', 'SL', 1, 'N', 14, '2024-05-26 05:11:35', NULL, '2024-05-29 05:11:35', 0, NULL, '2024-05-26 04:54:27', 4),
(358, 82, 1, 4, 14, '1_82_4_13452865066661dff8456a9_BA_CV_-_CV.docx', 'BA_CV - CV.docx', '\r\nShweta Sharma Sr. Business Analyst \r\nWipro  PROFESSIONAL SUMMARY\r\nExperienced Business Analyst with overall 11+ years’ experience as 6+ years’ in analyzing business requirements in software development and 5 years’ track record in Operations\r\nProfile Summary Business Analysis – Planning &amp; Scoping, AS IS &amp; TO BE Process Modelling, Requirement Analysis &amp; Documentation, managing backlog, prioritizing feature scope, defining Use stories, Manage Stakeholder\'s Sign offs.\r\nWell versed with SDLC methods – Agile and waterfall, experienced in requirements gathering, Group Discussions and Use Cases. Experienced with creating and modifying process flow diagrams and Use Case Diagrams. Excellent communication, analytical, interpersonal, and presentation skills; highly adept at handling the expectations of Multiple Stakeholders\r\nTools Exposure in Visio for requirement modelling, Azure- VSTS, JIRA, Top Team, Kanban Board\r\nCurrent Organization Wipro\r\nRole Product Owner cum Business Analyst Duration Apr’15 – Till Date\r\nKEY PROJECT DETAILS\r\nClient Name  Japan Client Development Methodology Agile and Waterfall\r\nRole Product Owner cum Business Analyst  Duration Jan’19 – Till Date\r\nProject 1 Commercial App (Agile -Jan’19 till Date) Project 2 Residential App (Waterfall -Aug’19 – Till Date)\r\nResponsibilities  Collaborate with business users, product owners and business partners to gather and identify requirements and further define and document requirements.\r\nLead requirements discussion/review sessions with users, vendors, and the partners to further refine/scope requirements.\r\nAnalyze business requirements by doing a research work on To-Be proposed solutions to business teams by understanding the competitors’ applications, current market expectations from the product. \r\nPrioritize the scope based on product strategy.\r\nManage and prioritize backlog items on each iteration.\r\nCreate Use cases, user stories by capturing requirements from multiple stakeholders and getting signed off on the same in timely manner.\r\nAssist in planning, estimates, testing and rollouts of new software release and establish critical project related milestones, and participate in quality assurance.\r\nSupported in user acceptance of a release or feature, and provide value management reporting\r\nInvolved in solution design discussions to improve system usability/UI experiences.\r\nResponsible for delivering status reports to client as and when required.\r\nClient Name US client Development Methodology Agile\r\nRole Business Analyst  Duration Apr\'18 – Jan’19\r\nResponsibilities  Working in capacity of business analyst for Q2 Solution and managing and developing the LTMS application used for clinical trials laboratories services\r\nPlan execute and manage the integration of new applications into existing network infrastructure, systems &amp; software throughout the enterprise\r\nGathering requirements and creating user stories and managing requirements in top team\r\nManaging the scoping of requirements and discussing the same with different stakeholders\r\nStepped up and played scrum master/project manager role when project was short of resources\r\nManaging daily calls and reporting on status on weekly basis to client\r\nClient Name Swiss Client Development Methodology Agile\r\nRole Business Analyst  Duration Apr\'15 –Mar’18\r\nResponsibilities  Working as a business analyst for UBS and managing applications risk assessment for finance stream\r\nRequirement planning &amp; management – Prepare plan for gathering requirement &amp; delivering within milestones\r\nApplication scoping, Requirement gathering and documentation, Elicitation using multiple techniques- User discussions, System documentation, meetings, etc.\r\nLiaison between business &amp; team, stakeholder management, governance reporting\r\nResponsible for overall application Risk Assessment\r\nInvolvement in application transition Go Live\r\nWeekly project reporting\r\nPrevious Organization  Accenture\r\nRole Analyst - Asset Data Management &amp; Reporting Duration Dec\'09 - Apr\'15\r\nResponsibilities  Possess comprehensive understanding of database management systems\r\nInteracting with management in implementation of business, process, and technology improvements\r\nPlanning, implement quality and process improvement initiatives and UAT testing for production environment for enhance productivity\r\nPreparing data for a Dashboard (ORB) and other related reporting in a timely, accurate and consistent format/manner\r\nAnalyze monthly, Quarterly and Annual reporting requirements &amp; prepare month-on-month “Trend &amp; Gap analysis” &amp; forecasting reports\r\nPublishing the documents or reports on intranet web page\r\nReporting sustainability performance against the KPIs for the business sector \r\nAnalyzed data in case of anomalies and carried out quality checks for the reports\r\n', 2, 2, 1, 'Candidate', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-06-06 16:12:40', 4),
(359, 84, 1, NULL, NULL, '1_84_16850685626661e19fe1a63_Shailja_Tyagi_CV.docx', 'Shailja Tyagi_CV.docx', '\r\nShailja Tyagi Sr. Business Analyst \r\nHCL Technologies  Email:   shailjatyagi28@gmail.comPhone: +91-9540063311\r\nPROFESSIONAL SUMMARY\r\nExperienced Business Analyst with overall 11+ years&rsquo; experience as 6+ years&rsquo; in analyzing business requirements in software development and 5 years&rsquo; track record in Operations\r\nProfile Summary Business Analysis &ndash; Planning &amp;amp; Scoping, AS IS &amp;amp; TO BE Process Modelling, Requirement Analysis &amp;amp; Documentation, managing backlog, prioritizing feature scope, defining Use stories, Manage Stakeholder&#039;s Sign offs.\r\nWell versed with SDLC methods &ndash; Agile and waterfall, experienced in requirements gathering, Group Discussions and Use Cases. Experienced with creating and modifying process flow diagrams and Use Case Diagrams. Excellent communication, analytical, interpersonal, and presentation skills; highly adept at handling the expectations of Multiple Stakeholders\r\nScrums/ Project Management &ndash; Performed scrum master/project manager role and successfully delivered the release on time\r\nTransition Management &ndash; Project planning, Application risk assessment, Transition Go Live\r\nOperations &ndash; Assisting Ops delivery and change management, Improvement projects by using LEAN quality tools, Automations of reports to enhance productivity and efficiency, analyzing processes and recommending modifications to enhance operational efficiency\r\nIndustry/ Domain  Industrial Air Condition Software Product (HVAC)\r\nClinical Trial Management\r\nApplication Transition Management\r\nOperation delivery and change management\r\nEducation  Graduated in BSC-IT from Kuvempu University (Year: 2012)\r\nGNIIT from NIIT Ltd. (Year)\r\nTools Exposure in Visio for requirement modelling, Azure- VSTS, JIRA, Top Team, Kanban Board, HP ALM, SNOW, GCRS, Business Object, Cognos 8\r\nCurrent Organization HCL Technologies\r\nRole Product Owner cum Business Analyst Duration Apr&rsquo;15 &ndash; Till Date\r\nKEY PROJECT DETAILS\r\nClient Name  Johnson Controls Hitachi - Japan Development Methodology Agile and Waterfall\r\nRole Product Owner cum Business Analyst  Duration Jan&rsquo;19 &ndash; Till Date\r\nProject 1 Commercial App (Agile -Jan&rsquo;19 till Date) Project 2 Residential App (Waterfall -Aug&rsquo;19 &ndash; Till Date)\r\nResponsibilities  Collaborate with business users, product owners and business partners to gather and identify requirements and further define and document requirements.\r\nLead requirements discussion/review sessions with users, vendors, and the partners to further refine/scope requirements.\r\nAnalyze business requirements by doing a research work on To-Be proposed solutions to business teams by understanding the competitors&rsquo; applications, current market expectations from the product. \r\nPrioritize the scope based on product strategy.\r\nManage and prioritize backlog items on each iteration.\r\nCreate Use cases, user stories by capturing requirements from multiple stakeholders and getting signed off on the same in timely manner.\r\nAssist in planning, estimates, testing and rollouts of new software release and&nbsp;establish critical project related milestones, and participate in quality assurance.\r\nSupported in user acceptance of a release or feature, and provide value management reporting\r\nInvolved in solution design discussions to improve system usability/UI experiences.\r\nResponsible for delivering status reports to client as and when required.\r\nKey Achievements Received appreciation from client\r\nClient Name Q2 Solutions Development Methodology Agile\r\nRole Business Analyst &ndash; Clinical Trial Management Duration Apr&#039;18 &ndash; Jan&rsquo;19\r\nResponsibilities  Working in capacity of business analyst for Q2 Solution and managing and developing the LTMS application used for clinical trials laboratories services\r\nPlan execute and manage the integration of new applications into existing network infrastructure, systems &amp;amp; software throughout the enterprise\r\nGathering requirements and creating user stories and managing requirements in top team\r\nManaging the scoping of requirements and discussing the same with different stakeholders\r\nStepped up and played scrum master/project manager role when project was short of resources\r\nManaging daily calls and reporting on status on weekly basis to client\r\nKey Achievements Received appreciation from Senior BA(client) and Project Manager/Scrum Master\r\nClient Name UBS Bank Development Methodology Agile\r\nRole Business Analyst - Application Transition Management Duration Apr&#039;15 &ndash;Mar&rsquo;18\r\nResponsibilities  Working as a business analyst for UBS and managing applications risk assessment for finance stream\r\nRequirement planning &amp;amp; management &ndash; Prepare plan for gathering requirement &amp;amp; delivering within milestones\r\nApplication scoping, Requirement gathering and documentation, Elicitation using multiple techniques- User discussions, System documentation, meetings, etc.\r\nLiaison between business &amp;amp; team, stakeholder management, governance reporting\r\nResponsible for overall application Risk Assessment\r\nInvolvement in application transition Go Live\r\nWeekly project reporting\r\nKey Achievements Managed SLA&rsquo;s &amp;gt;95% transactions for all projects within timeframe\r\nValue idea creation of approx. US $ 15K in cost savings per annum &amp;amp; process improvements\r\nReceived &ldquo;Live Wire&rdquo; Certification &ndash; 2Q17, 3Q17\r\nPrevious Organization  Wipro Ltd.\r\nRole Analyst - Asset Data Management &amp;amp; Reporting Duration Dec&#039;09 - Apr&#039;15\r\nResponsibilities  Possess comprehensive understanding of database management systems\r\nInteracting with management in implementation of business, process, and technology improvements\r\nPlanning, implement quality and process improvement initiatives and UAT testing for production environment for enhance productivity\r\nPreparing data for a Dashboard (ORB) and other related reporting in a timely, accurate and consistent format/manner\r\nAnalyze monthly, Quarterly and Annual reporting requirements &amp;amp; prepare month-on-month &ldquo;Trend &amp;amp; Gap analysis&rdquo; &amp;amp; forecasting reports\r\nPublishing the documents or reports on intranet web page\r\nReporting sustainability performance against the KPIs for the business sector \r\nAnalyzed data in case of anomalies and carried out quality checks for the reports\r\nKey Achievements Lean Certified for Value idea creation for process improvements &ndash; Jun&rsquo;14\r\nReceived &ldquo;Star of the Month&rdquo; for performance - Sep&rsquo;14, Jul&rsquo;14, Jun&rsquo;14, May&rsquo;14, Jan&rsquo;14\r\nReceived &ldquo;Star of the Quarter&rdquo; for performance &ndash; 2Q12, 3Q14\r\nReceived &ldquo;Letter of Appreciation&rdquo;- Oct&#039;12, Mar&#039;13\r\nPromoted from &ldquo;Officer&rdquo; to &ldquo;Sr. Officer&rdquo; - Sep&rsquo;12\r\nPERSONAL DETAILS\r\nDate of Birth 28th Jun&rsquo;91\r\nMarital Status Single\r\n', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-06-06 16:19:43', 0);
INSERT INTO `resume` (`id`, `screeningId`, `adminId`, `candidateId`, `candidateDetailsId`, `resumeName`, `resumeOriginalName`, `resumeContent`, `isSkillScreened`, `isResumeScreened`, `isCron`, `isCandidate`, `isStatus`, `candidateShortlist`, `isInterviewAssign`, `enableInterviewReport`, `gptLanguageId`, `interviewAssignDate`, `psychoAssignDate`, `interviewValidity`, `isPsychoAssign`, `psychoValidity`, `created`, `createdBy`) VALUES
(360, 85, 1, NULL, NULL, '1_85_430573143666fe7447596b_Kuricheti-Venkataramana-FlowCV-Resume-20240617_(1)_(1).pdf', 'Kuricheti-Venkataramana-FlowCV-Resume-20240617 (1) (1).pdf', 'Ku ric h eti V en ka ta ra m an a  \nP ro g ra m  A naly st	\nVEN KA T78871@ gm ail .c o m\n7 997566756\nH yd era b ad ,  IN D	\nPro ve n  IT  p ro fe ssio n al  w it h  e xp erie n ce  o f  3  y e ars  a n d  h ig hly  m otiv a te d  d ata  s cie n tis t  w it h  a\ns tr o n g  b ack g ro u n d  in  m ath em atic s  a n d  s ta tis tic s .  S kil le d  in  u sin g  p ro g ra m min g  l a n g uag es s u ch  a s\nP yth on  a n d  R .  P ro fic ie n t in  m ach in e le arn in g  a lg orit h m s &amp;  C on ce p ts  o f D eep  le arn in g  a n d  N LP  &amp;\nG en  A I.  H avin g  g re at  k n ow le d g e o n  d ata  v is u aliz a tio n  lik e  P ow er  B I  a n d  d ata b ase  lik e  S Q L.\nS eekin g  a  c h alle n g in g  r o le  a s a  d ata  s cie n tis t w here  I  c a n  u til iz e  m y s k il ls  a n d  k n ow le d g e t o  d riv e\nd ata -d riv e n  s o lu tio n s a n d  c o n tr ib ute  t o  t h e s u cce ss o f t h e o rg an iz a tio n .	\nP R O FE S SIO NAL E X PER IE N CE	\n2021&nbsp;J u n e &ndash;  p re se n t\nH yd era b ad ,	 In d ia	\nC og niz a n t 	te ch nolo g ie s 	a n d  	so lu tio n  	P V T 	Lim it e d , 	J r  	D ata  	S cie n tis t	\n&bull;W ork e d  A t C og niz a n t IP A  A naly tic s  T e am .\n&bull;Pro fe ssio n al q ualif ie d  D ata  S cie n tis t/D ata  A naly st w it h  o ve r 3  y e ars  o f	 	\nexp erie n ce ,  w here  I  h ave  in  D ata  S cie n ce  a n d  A naly tic s ,  in clu d in g	 	\nD eep  l e arn in g ,  M ach in e L earn in g ,  S ta tis tic a l A naly sis ,  N LP  a n d  S Q L.\n&bull;D esig ned  a n d  im ple m en te d  e n d -to -e n d  a u to m atio n  p ip elin es u til iz in g	 	\nC N N/R N N m od els  a n d  a d va n ce d  R A G  ( R etr ie va l- A ug m en te d	 	\nG en era tio n ) t e ch niq ues f o r d ocu m en t in d exin g  a n d  d ata  e xtr a ctio n .	 	\nA ch ie ve d  a  s ig nif ic a n t r e d uctio n  in  p ro ce ssin g  t im e,  s p eed in g  u p	 	\nd ep lo ym en t t o  m ark e t b y 4 0% .\n&bull; O ptim iz e d  c o st- e ff e ctiv e n ess b y in te g ra tin g  L LM s ( L arg e L an g uag e	 	\nM od els ) a n d  f in e-tu n in g  s tr a te g ie s,  r e d ucin g  o p era tio n al c o sts  b y 3 0%	 	\nw hil e  m ain ta in in g  h ig h a cc u ra cy  in  d ocu m en t p ro ce ssin g  t a sk s.\n&bull; C ra ft e d  a n d  o p tim iz e d  t e xt p ro m pts  f o r v a rio u s g en era tiv e  A I  t a sk s	 	\nin clu d in g  t e xt g en era tio n ,  t r a n sla tio n ,  a n d  c o d e c o m ple tio n .	 	\nC olla b ora te d  c lo se ly  w it h  d ata  s cie n tis ts  t o  t a il o r p ro m pts  f o r o p tim al	 	\np erfo rm an ce  a cro ss d if f e re n t d ata se ts ,  f o cu sin g  o n  m etr ic s  s u ch  a s	 	\nflu en cy,  c o h ere n ce ,  a n d  c re ativ it y .\n&bull; C on d ucte d  A /B  t e stin g  a n d  h um an  e va lu atio n s t o  it e ra te  o n  p ro m pt	 	\nd esig ns,  e n su rin g  d esir e d  m od el o u tp uts  a n d  id en tif y in g  b ia se s o r	 	\nerro rs  in  G en A I  o u tp uts .  Im ple m en te d  a d ju stm en ts  t o  p ro m pts  b ase d	 	\no n  f in d in g s t o  e n han ce  o ve ra ll p erfo rm an ce .\n&bull; E xp lo re d  n ew  p ro m ptin g  t e ch niq ues s u ch  a s f e w -s h ot a n d  z e ro -s h ot	 	\nle arn in g  t o  in nova te  p ro m pt d esig n a n d  im pro ve  G en A I  m od el	 	\nb eh avio r in  c re ativ e  t e xt g en era tio n  a p plic a tio n s.\n&bull; D eve lo p ed  e ff ic ie n t d ata  p ip elin es f o r p ro m pt e va lu atio n ,  e n ab lin g	 	\nd eta il e d  a n aly sis  o f G en A I  o u tp uts  t o  r e fin e p ro m pts  a n d  a ch ie ve	 	\no p tim al r e su lt s .  S hare d  p ro m pt e n g in eerin g  b est p ra ctic e s w it h in  t h e	 	\nte am ,  f o ste rin g  a  c u lt u re  o f c o n tin uou s im pro ve m en t.\n&bull;C om mun ic a te d  t h e im pact o f p ro m pt d esig n o n  G en A I  o u tp uts	 	\ne ff e ctiv e ly  t o  b oth  t e ch nic a l a n d  n on -te ch nic a l s ta ke h old ers ,	 	\nd em on str a tin g  t h e v a lu e o f o p tim iz e d  p ro m ptin g  s tr a te g ie s in	 	\na ch ie vin g  b usin ess g oals .\n\n&bull;Con tr ib ute d  t o  t h e d eve lo p m en t o f in te rn al p ro m pt m an ag em en t a n d	 	\neva lu atio n  t o ols ,  e m pow erin g  d ata  s cie n tis ts  a n d  a n aly sts  t o	 	\ns tr e am lin e p ro m pt c re atio n ,  v e rs io n  c o n tr o l,  a n d  d ata  a n aly sis	 	\np ro ce sse s.\n&bull;L eve ra g ed  s tr o n g  p ro b le m -s o lv in g  s k il ls  t o  e va lu ate  m ult ip le	 	\np ro m ptin g  a p pro ach es a n d  s e le ct t h ose  y ie ld in g  t h e b est c re ativ e	 	\no u tp uts  f r o m  G en A I  m od els ,  e n su rin g  a lig nm en t w it h  p ro je ct	 	\no b je ctiv e s.\n&bull;T his  e xp erie n ce  s e ctio n  h ig hlig hts  t h e c a n d id ate &#039;s  p ro fic ie n cy  in	 	\nb uil d in g  a u to m atio n  p ip elin es u sin g  a d va n ce d  A I  m od els ,  o p tim iz in g	 	\nop era tio n al c o sts ,  a n d  e xp ertis e  in  p ro m pt e n g in eerin g  f o r g en era tiv e	 	\nA I  t a sk s.  It  e m phasiz e s t h eir  a b il it y  t o  in nova te ,  c o lla b ora te  e ff e ctiv e ly	 	\nw it h  c ro ss-fu n ctio n al t e am s,  a n d  d riv e  c o n tin uou s im pro ve m en t in  A I-\nd riv e n  s o lu tio n s f o r d ocu m en t p ro ce ssin g  a n d  b eyo n d .	\nE D UCA TIO N	\n2016&nbsp;J u n e &ndash;\n2 020&nbsp;S ep te m ber\nK ham mam	\nB ach elo r 	o f 	T ech nolo g y, 	\nS w arn a 	B hara th i 	I n stit u te  	o f 	S cie n ce &amp;  	Tech nolo g y	\nC G PA :	7.0	\n2 015&nbsp;M arc h  &ndash;\n2 016&nbsp;A pril\nK ham mam	\nIn te rm ed ia te , 	K ris h nave n i 	J u n io r 	c o lle g e	\nP erc e n ta g e: 	9 4.2	\n2 013&nbsp;J u n e &ndash;\n2 014&nbsp;M arc h\nK ham mam	\nS SC , 	S ri 	c h ait a n ya  	V id ya la ya m	\nC G PA : 	9 .8	\nS K IL LS	\nPyth on	M ach in e L earn in g	P an d as	N um py	M atp lo tlib	S eab orn	S Q L	\nGen era tiv e  A I	D eep  L earn in g	N LP	P yT o rc h	T e n so rF lo w	\nP R O JE C TS	\nVA T-E rro r 	A naly sis	\nC lie n t: 	A ke r S olu tio n s	\nTech nolo g ie s:	 P yth on ,  R an d om  f o re st C la ssif ic a tio n ,  M ach in e l e arn in g	\n&bull;A s a  D ata  S cie n tis t,  I  h ave  s u cce ssfu lly  c o m ple te d  a  p ro je ct w here  I  b uil t  a  R an d om  F o re st	 	\ncla ssif ic a tio n  m od el t o  id en tif y  e rro rs  in  V A T t a x c a lc u la tio n s.\n&bull;T he p ro je ct in vo lv e d  d ata  p re  p ro ce ssin g ,  d ata  c le an in g ,  f e atu re  e n g in eerin g ,  a n d  m od el t r a in in g	 	\nusin g  P yth on  a n d  l ib ra rie s l ik e  P an d as ,N um py,  S eab orn  &amp;  S cik it - L earn .\n&bull;I  a n aly ze d  l a rg e d ata se ts  a n d  u se d  s ta tis tic a l t e ch niq ues t o  id en tif y  p att e rn s in  t h e d ata  t h at	 	\nw ere  in d ic a tiv e  o f t a x c a lc u la tio n  e rro rs .\n&bull;T he r e su lt in g  m od el a ch ie ve d  a  h ig h a cc u ra cy  r a te ,  a llo w in g  f o r t h e id en tif ic a tio n  o f t a x e rro rs	 	\nw it h  a  h ig h d eg re e o f p re cis io n .\n&bull;T his  p ro je ct d em on str a te s m y e xp ertis e  in  d ata  a n aly sis ,  m ach in e l e arn in g ,  a n d  p ro b le m -\nso lv in g ,  a n d  m y a b il it y  t o  d eliv e r d ata -d riv e n  s o lu tio n s t h at d riv e  b usin ess v a lu e.	\nS m art 	A ud it	\nC lie n t: 	T e am  H ealt h	\nT ech nolo g ie s:	 P yth on  ,R an d om  f o re st R eg re ssio n ,  M ach in e l e arn in g\n\n&bull;As a  D ata  S cie n tis t,  I  h ave  s u cce ssfu lly  c o m ple te d  a  p ro je ct w here  I  b uil t  a  R an d om  F o re st	 	\nre g re ssio n  m od el t o  m in im iz e  e rro rs  in  t h e a u d it  p ro ce ss.\n&bull;T he p ro je ct in vo lv e d  a n aly zin g  l a rg e d ata se ts  u sin g  P yth on  a n d  P an d as,  N um py,  S eab orn ,	 	\nS cik it - L earn ,  id en tif y in g  f e atu re s t h at w ere  p re d ic tiv e  o f a u d it  e rro rs ,  a n d  t r a in in g  a  r e g re ssio n	 	\nm od el t o  m in im iz e  t h ose  e rro rs .\n&bull;I  a ls o  c o n d ucte d  d ata  v is u aliz a tio n  a n d  f e atu re  e n g in eerin g  t o  e xtr a ct m ean in g fu l in sig hts  f r o m	 	\nth e d ata .\n&bull;T he r e su lt in g  m od el a ch ie ve d  h ig h a cc u ra cy  in  p re d ic tin g  a u d it  e rro rs ,  l e ad in g  t o  a  m ore  e ff ic ie n t	 	\nan d  e ff e ctiv e  a u d it  p ro ce ss.\n&bull;T his  p ro je ct s h ow ca se s m y e xp ertis e  in  d ata  a n aly sis ,  m ach in e l e arn in g ,  a n d  p ro b le m -s o lv in g ,	 	\nas w ell a s m y a b il it y  t o  d eve lo p  a n d  d ep lo y d ata -d riv e n  s o lu tio n s t h at d riv e  b usin ess v a lu e.	\nC ER TIF IC A TES	\nMic ro so ft  p ow er p la tfo rm	 	\nfu n d am en ta ls  ( P L-9 00)\nP ow er A uto m ate  R PA	 	\nD eve lo p er A sso cia te  ( P L-\n5 00)	\nP ow er B I  D ata  A naly st	 	\nA sso cia te  ( P L-3 00)	\nP ow er P la tfo rm  A pp M ake r	 	\nA sso cia te  ( P L-1 00)	\nD EC LA RATIO N	\nI  h ere b y d ecla re  t h at t h e in fo rm atio n  p ro vid ed  in  t h is  r e su m e is  t r u e a n d  a cc u ra te  t o  t h e b est o f\nm y k n ow le d g e a n d  b elie f.	\nK uric h eti&nbsp; V en ka ta ra m an a', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-06-17 07:35:32', 0),
(361, 86, 1, NULL, NULL, '1_86_671044946667904b5a7613__Aamir_Ashraf.pdf', '_Aamir_Ashraf.pdf', 'SU M M AR Y	PR O JE C TSED U CAT IO NTEC H NIC AL S K IL LSC ER T IF IC AT IO NS	Ben galu ru ,  K arn ata k a	\naam ir 8 20 02@ gm ail.c o m	+9 17 0 0636 80 91	\nA AM IR  A SH RAF\nCSE  G ra d uate\nA s a  r e ce n t C om pute r S cie n ce  E ngin eerin g g ra d uate  a n d d yn am ic  e n tr y -le ve l p ro fe ssio n al,  I  a m  w ell- v e rs e d  i n\nm ajo r c o m pute r p ro gra m min g l a n gu ag es,  d em on str a tin g p ro fic ie n cy i n  P yth on .  A ctiv e ly  c u lt iv a tin g e xp ertis e  i n\nD ata  S cie n ce .  I  a m  r e co gn iz e d  f o r a d ap ta b ili t y ,  i n nova tio n ,  a n d a  p ro ac tiv e  a p pro ac h .  E ag er t o  l e ve ra g e m y s k ills\na n d k n ow le d ge i n  D ata  A naly tic s,M ac h in e L earn in g a n d S o ft w are  D eve lo p m en t t o  c o n tr ib u te  m ean in gfu lly  i n  a	\nd yn am ic  w ork  e n vir o n m en t a n d s u pport t h e s u cce ss o f y o u  t e am .	                                                       	\nS u cce ssfu lly  c o m ple te d  a  p ro je ct f o cu se d  o n  d is e ase  d ete ctio n  i n\np la n t l e ave s.\nIm ple m en te d  C on vo lu tio n al N eu ra l N etw ork  ( C N N) f o r d is e ase\nid en tif ic atio n  a n d r e m ed ie s.\nC on tr ib u te d  t o  a g ric u lt u ra l a n d e n vir o n m en ta l s u sta in ab ili t y\nt h ro u gh  i n nova tiv e  t e ch n olo gy.\nA cq u ir e d  k n ow le d ge a n d p ra c tic al e xp erie n ce  i n  m ac h in e\nle arn in g a lg o rit h m s,  i n clu d in g K -N eare st N eig h bo rs  ( K N N) 	a n d	\nLin ear R eg re ssio n .\nE m plo ye d  P yth on  p ro gra m min g f o r a  p ro je ct a im ed  a t a sse ssin g\nth e q u ali t y  o f w in es.\nP ro fic ie n tly  d eve lo p ed  J a va  A pple ts  f o r t h e p ro je ct&#039;s  f r o n t- e n d\nin te rfa c e .\nE ffe ctiv e ly  i n te g ra te d  a n d u tili z e d  M yS Q L f o r d ata b ase\nm an ag em en t a n d s to ra g e.	\nB ac h elo r&#039;s  D eg re e i n  C om pute r S cie n ce  E ngin eerin g\n20 17	 &ndash;  2 0 23	\nH ig h er S eco n dary  ( 1 0 +2 )\n20 16	\nP ro gra m min g l a n gu ag es:  C ,  C ++,\nJa va S crip t,  J a va ,  P yth on .\nW eb  D eve lo p m en t:  H TM L5,  C SS.\nD ata b ase  m an ag em en t:  M YSQ L,\nM on go D b.\nM ac h in e L earn in g\nD ata  S cie n ce\nG oogle  D ata  A naly tic s	 	\nP yth on  E sse n tia ls  I  ( C is c o )\nP yth on  E sse n tia ls  I I ( C is c o )\nJa va S crip t E sse n tia ls  I  ( C is c o )	\nL eaf D is e ase  D ete ctio n  &amp;  R em ed y u sin g C N NW in e Q uali t y  A naly sisH ote l M an ag em en t S yste mV is v esv ara y a T ech n olo gic a l U niv ers it yS ri P ra ta p  H ig h er S eco n dary  S ch oolS O FT  S K IL LS	Tim e m an ag em en t\nA dap ta b ili t y\nP ro ble m  S o lv in g\nC om mun ic atio n\nT eam  P la y e r	\nE X PE R IE N CEKaru n ad u  T ech n olo gie s P riv ate  L im it e d\nIn te rn sh ip  E xp erie n ce  |  0 9/ 20 21 -  1 0 / 20 21	\nD eve lo p ed  a  w in e q u ali t y  a n aly sis  m od el u sin g t h e K N N	\n        	a lg o rit h m  t o  p re d ic t t h e q u ali t y  o f w in es b ase d  o n  v a rio u s	\n        	f e atu re s.\nIm ple m en te d  t h e K N N a lg o rit h m  f o r c la ssif ic atio n ,  l e ve ra g in g t h e	    	\ns c ik it - le arn  l i b ra ry  i n  P yth on .\nE xtr a c te d  m ean in gfu l i n sig h ts  f r o m  t h e m od el&rsquo;s  p re d ic tio n s,	\n        	p ro vid in g a  d eep er u n ders ta n din g o f t h e f a c to rs  i n flu en cin g w in e	                  	\n        	q u ali t y .	\nL A N GUAG ES	Engli s h\nH in di\nU rd u', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-06-24 05:31:33', 0),
(362, 86, 1, NULL, NULL, '1_86_1908525779667904b5a7e12_48_VikasM.pdf', '48_VikasM.pdf', 'V i k a s M a g a r eA I E n g i n e e r+ 9 1 9 8 6 0 7 6 6 4 7 0 | v i k a s m a g a r e 0 3 0 9 @ g m a i l . c o m | M a h a r a s h t r a , I n d i aL i n k e d I n : h t t p s : / / w w w . l i n k e d i n . c o m / i n / v i k a s - m a g a r e - 6 6 8 7 5 4 1 a 3\nS U M M A R Y :\nA s p i r i n g A I E n g i n e e r c a n d i d a t e w i t h s t r o n g m a c h i n e l e a r n i n g f o u n d a t i o n a n d p r o g r a m m i n g\np r o f i c i e n c y ( P y t h o n ) . E a g e r t o l e v e r a g e r e s e a r c h a n d p r o b l e m - s o l v i n g s k i l l s t o c o n t r i b u t e t o\ni n n o v a t i v e G e n e r a t i v e A I m o d e l s .\nE x p e r i e n c e :\nA I T r a i n e r A p r 2 0 2 4 - P r e s e n t\nO u t l i e r / I n d i a , R e m o t e\n C o l l a b o r a t e o n o p t i m i z i n g a n d t r a i n i n g l a r g e l a n g u a g e m o d e l s ( L L M s ) , d r i v i n gi m p r o v e m e n t s i n g e n e r a t i v e A l f o r e n h a n c e d c o d e q u a l i t y .\n D e s i g n , d e v e l o p , a n d r e f i n e A l - g e n e r a t e d t e x t p r o m p t s , o p t i m i z i n g p r o m p t p e r f o r m a n c e ,a n d i m p r o v i n g t h e A l p r o m p t g e n e r a t i o n p r o c e s s f o r v a r i o u s a p p l i c a t i o n s .\nC a m p u s A m b a s s a d o r F e b 2 0 2 4 - M a r c h 2 0 2 4\nW a y s p i r e / G u r u g r a m , I n d i a\n A s a C a m p u s A m b a s s a d o r a t W a y s p i r e , I p r o m o t e a n d r e p r e s e n t t h e c o m p a n y &#039; s o n l i n el e a r n i n g p l a t f o r m t o s t u d e n t s a n d f a c u l t y a t m y u n i v e r s i t y\nE D U C A T I O N :\nB a c h e l o r &#039; s D e g r e e i n C o m p u t e r S c i e n c e a n d E n g i n e e r i n g M a r 2 0 2 4\nB A M U U n i v e r s i t y , A u r a n g a b a d , M a h a r a s h t r a\nT E C H N I C A L S K I L L S : T e c h n i c a l : A r t i f i c i a l I n t e l l i g e n c e , G e n e r a t i v e A I , L a r g e L a n g u a g e M o d e l s , N L P , M a c h i n eL e a r n i n g , A n a l y t i c a l s k i l l s , P r o g r a m m i n g , P y t h o n , A W S , C o m m u n i c a t i o n s k i l l s .\n L a n g u a g e s : E n g l i s h , C h i n e s e , H i n d i , J a p a n e s e , M a r a t h i\n\nP R O J E C T S :\nN a t i v e L a n g u a g e A I T r a i n e r - M a r a t h i : J u n e 2 0 2 4 - P r e s e n t\n D e s i g n , d e v e l o p , a n d r e f i n e A l - g e n e r a t e d t e x t p r o m p t s , o p t i m i z i n g p r o m p t p e r f o r m a n c e ,a n d i m p r o v i n g t h e A l p r o m p t g e n e r a t i o n p r o c e s s f o r v a r i o u s a p p l i c a t i o n s .\n I t &#039; s a 6 m o n t h s u p w o r k p r o j e c t .\nH i n d i A I T r a i n e r : M a y 2 0 2 4 - J u n e 2 0 2 4\n D e s i g n , d e v e l o p , a n d r e f i n e A l - g e n e r a t e d t e x t p r o m p t s , o p t i m i z i n g p r o m p t p e r f o r m a n c e ,a n d i m p r o v i n g t h e A l p r o m p t g e n e r a t i o n p r o c e s s f o r v a r i o u s a p p l i c a t i o n s .\nT r a i n i n g a n d P l a c e m e n t C e l l : J a n 2 0 2 3 - M a y 2 0 2 3\n D e s i g n e d f o r o r g a n i z a t i o n t o t r a i n i n g a n d p l a c e m e n t s e t t i n g s T e c h n o l o g y u s e d : J A V A , T o m c a t s e r v e r , S Q L\nA W A R D S / A C C O M P L I S H M E N T S :\nF r i e n d s U n i o n f o r E n e r g i s i n g L i v e s ( F U E L ) J u n e 2 0 2 3\n A w a r d e d f o r t h e c o m p l e t i o n o f m a x i m u m c e r t i f i c a t i o n o n L i n k e d I n R e c e i v e d t h e B e s t P e r f o r m a n c e A w a r d a n d C e r t i f i c a t e o f A p p r e c i a t i o n\nC E R T I F I C A T I O N S :\nA C a r e e r E s s e n t i a l i n G e n e r a t i v e A I b y L i n k e d I n a n d M i c r o s o f t ( M a r 2 0 2 4 ) - M i c r o s o f t\nA W S C l o u d P r a c t i t i o n e r E s s e n t i a l s ( F e b 2 0 2 3 ) - C o u r s e r a\nG o o g l e D a t a A n a l y t i c s ( J a n 2 0 2 3 ) - C o u r s e r a\nG o o g l e P r o j e c t M a n a g e m e n t ( J a n 2 0 2 3 ) - C o u r s e r a\nA C a r e e r E s s e n t i a l i n P r o j e c t M a n a g e m e n t b y L i n k e d I n a n d M i c r o s o f t ( D e c 2 0 2 2 ) - M i c r o s o f t\nP o s t D i p l o m a I n M e c h a t r o n i c s ( J u n 2 0 2 2 ) - I G T R , A u r a n g a b a d\nD E C L A R A T I O N :\nI h e r e b y d e c l a r e t h a t a l l t h e d e t a i l s m e n t i o n e d a b o v e a r e i n a c c o r d a n c e w i t h t h e t r u t h a n d f a c t a s\np e r m y k n o w l e d g e a n d I h o l d t h e r e s p o n s i b i l i t y f o r t h e c o r r e c t n e s s o f t h e a b o v e - m e n t i o n e d\np a r t i c u l a r s .', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-06-24 05:31:33', 0),
(363, 86, 1, NULL, NULL, '1_86_1388886937667904b5a849a_HasnaResume.pdf', 'HasnaResume.pdf', 'HASNA C\n +916238494289  hasnachelamadathil@gmail.com\nLIN\nKS\n\nGitHub hasnac\n\nLinkedin hasna‑c\nSKI\nLLS\nPROFICIENT WITH:\n&bull; Python\n&bull; SQL\n&bull; R Programming\n&bull; Java\n&bull; Machine Learning\n&bull; AWS\n&bull; NLP\n&bull; Statistics\nFAMILIAR WITH:\n&bull; Pyspark\n&bull; GCP\n&bull; Hadoop\n&bull; Git\n&bull; Excel\n&bull; Tableau\nEDU\nCATION\nMSC IN BIG DATA ANALYTICS\n(COMPUTER SCIENCE)\nCentral University of\nRajasthan\n Nov 2021 ‑ Aug 2023 Rajasthan, India\nBACHELOR IN COMPUTER\nAPPLICATION\nUniversity of Calicut\n 2017 ‑ 2020 Kerala\nINT\nERNSHIP\nWEB DEVELOPMENT INTERN\nBluegen Solutions, Calicut\n Jul 2019 &ndash; Jan 2020 Calicut, Kerala\n&bull;\nTouch‑Based Digital Ordering\nSystem\n&bull;\nFront End: C, .Net, Android\n&bull;\nBack End: Microsoft SQL Server\n2008\nDATA ENGINEER INTERN\nThe Venture Build\n May 2023 &ndash; Oct 2023 Austin\n&bull;\nAutomotive Data Analysis\n&bull;\nTools and Technologies:\nPython, SQL, ETL (Mage), GCP,\nLooker Studio\nPRO JECTS\nDIGIT RECOGNIZER\nAcademic Project\n sep 2022 &ndash; Dec 2022\nA handwritten digit recognition using Machine Learning.\nTechnologies used:CNN,Augmentation,Hyper‑parameter tuning.\nLink to GitHub repo:\nhttps://github.com/hasna‑c/Digit‑Recognition\nSTOCK MARKET REAL-TIME DATA ANALYSIS USING KAFKA\nPersonal Project\n Feb 2023\nI successfully completed a project that utilized Kafka for processing stock\nmarket data. Using Python, I produced data and transmitted it to a Kafka\ncluster for consumption. The data was then stored on Amazon S3 and\nsubsequently crawled to create a catalog. Finally, I analyzed the data using\nAmazon Athena with SQL.\nTechnologies used:\n1) Python\n2) AWS(EC2,S3,Athena,Glue Crawler,Glue Catalog)\n3) Apache Kafka\nLink to GitHub repo:\nhttps://github.com/hasna‑c/kafka‑project\nSMOKING DETECTION SYSTEM\nPersonal Project\n Nov 2023\nThis project focuses on building a smoking detection system using a\nmeta‑learning approach. It utilizes a custom Vision Transformer (ViT)\nmodel for feature extraction, addresses the curse of dimensionality\nproblem through Principal Component Analysis (PCA), and employs a\ntuned XGBoost model for the final classification stage. The project is\norganized into four key notebooks: data preparation, ViT feature\nextraction, XGBoost classification, and model evaluation. Leveraged\nTensorFlow&rsquo;s Mirrored Strategy for parallel processing, tf.data for efficient\ndata handling, and SHAP for feature explanation.\nLink to GitHub repo:\nhttps://github.com/hasna‑c/Smoking‑Detection\nCOM PETITIONS\nWIDS DATATHON 2023\nCentral University of Rajasthan, Jaipur\n February 24, 2023\n&bull; WiDS(Women in Data Science Community) Organized by the\nDepartment of Data Science and Analytics at the Central University of\nRajasthan, Jaipur.\n&bull; The competition focused on &rdquo;Adapting to Climate Change by\nImproving Extreme Weather Forecasts.&rdquo;\n&bull; Challenging competition that tested my skills in data analysis,\nmachine learning, and statistical modeling.\nCOU RSES AND CERTIFICATES\nMACHINE LEARNING\nSimplylearn Skillup\n Nov ‑ 2022\nDATA USED IN FOOTBALL\nAnalayiSport\n Jan ‑ 2023', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-06-24 05:31:33', 0),
(364, 86, 1, NULL, NULL, '1_86_2118574785667904b5a8a93_Monish_TM_Resume.pdf', 'Monish TM_Resume.pdf', 'fsaar	                                                                                                 	 	\n 	\n 	 	\n \n      	Objective 	  	\n   	\nI  am  seeking  a  career  as  a 	Data	 Scientist	 that  will  allow  me  to  utilize  my  knowledge 	and 	\ndeveloping	 skills  in  Python,	 Gen	AI Machine  Learning,	 and  Data  Analysis,  with  a  passion  for 	\nturning  data  into  valuable  insights.	 Eager  to  contribute  my  skills  and  learn  in  a  dynamic 	\ndata	 science	 role.	 	\n 	\n    	Internship	   	\nData Science Internship |	Everest IMS	                                                                            	Feb 2024	 	\n \nOffline Chatbot for Private Document Interaction	: 	\n&bull; Developed  an  offline  chatbot  for  securely  interacting  with  private  documents  using  the \nMistral	-7B	-Instruct model, FAISS vector store, and LangChain	. 	\n&bull; Ingested  documents,  generated  embeddings  with  instructor	-xl,  indexed  in  FAISS  for 	\nefficient vector similarity search.	 	\n&bull; Enabled context	-aware question	-answering by retrieving relevant chunks and generating 	\nconcise responses through 	RAG	 pipeline, ensuring data privacy.	 	\n 	\n    	Education	 	\n     	  Aug	 202	0 &ndash; July	 202	4                	Reva University, Bangalore	 	\n                                             	      	         Bachelors in Computer Science and System Engineerin	g 	\n                                                            	Score:	 8.8                                                                                 	 	\n  \n       	  Aug 20	18	 - June 	2020	       	      	   SBGNS COMP PU COLLEGE, Chikkaballapur	 	\n                                             	       	         	Major: PCMB, Score: 	86.67	% 	\n \n      June 2017 	&ndash; May 2018              	BGS High 	School,	 Chikkaballapur 	 	\n                                                           	 Score: 	90.24	% 	\n        	Knowledge	 &amp; Skills	 	\nProgramming Skills	 	Python, SQL.	 	\nLibraries in Python	 	NumPy	, Pandas	, Matplotlib	, Scikit	-learn	, TensorFlow	, LangChain	,  	\nHugging Face	. 	\nIDE	 	Colab	, Visual Studio code	, Jupyter Notebook.	 	\nData Science	 	LLMs, 	Machine Learning (Regression, Decision Tree, Clustering)	, 	\nDeep Learning (ANN, CNN	, RNN, LSTM), RAG pipelines.	 	\nSoft Skills 	 	Communication, Team Work, Quick Learner.	 	\n                                                   	 	\n                         	 	\n \n \n \n \n                                         	 	\nMonish T	 M	 	\n8th Semester, Computer Science and 	System 	Engineering	 	\nReva University	 	\nmonishreddy173@gmail.com	 | +	91	 8050252601	 	\nYelahanka	, Bangalore	, Karnataka\n\nProject	s 	\nCustomer Churn Analysis in Telecom Company	 	                                                           	\n[January 2023]	 	\n&bull;  The  Telecom  Customer  dataset  consist  of 	7,000  records  with 	21	 attributes  including 	\ndemographic and behavioral attributes.	 	\n&bull; Performed EDA (data visualization, descriptive analysis, heatmap for correlation).	 	\n&bull; Applied Logistic Regression, Decision Tree, Random Forest, SVM and 	AdaBoost 	classifiers 	\nto identify customers at risk of churn.	 	\n&bull;Comparative  study  has  shown  that  both  Random  Forest  and 	AdaB	oost  have  performed 	\nwell.  Random  Forest  Classifier  gave the  accuracy,  precision  and  recall  of 86.45%,  88%  and \n90%, respectively.	 	\n \nEnd	-to	-End 	Chicken Disease	 Classification 	  	 	 	 	 	                             	\n[April 2023]	 	\n&bull; Developed an efficient deep learning model for classifying chicken diseases using modular \nprogramming techniques.	 	\n&bull; To  foster  collaboration  and  transparency,  I  established  a  GitHub  repository  with  a  well	-	\norganized project template and comprehensive logs. 	 	\n&bull; Leveraging modular code, I ensured a smooth and flexible training and prediction process.	 	\n \n \nEnd	-to	-End  Machine  Learning  Project  on  Student  Exam  Performance  Indicator                             	\n[May	 2023]	 	\n&bull;Performed  a  comprehensive  End	-to	-End  machine  learning  initiative  via  GitHub,  focusing 	\non predicting student exam performance.	 	\n&bull;  Coordinated  the  project  using  modular  components,  covering  data  ingestion, \ntransformation, and model training processes.	 	\n&bull; Additionally, the project entailed a well	-structured pipeline featuring extensions, logging 	\nmodule, and utility functions.	 	\n \n \n 	\n   	  Certifications	   	\n&bull; 	Associate Cloud Engineer Certification	: Google	 	\n(Deploying and managing solutions on Google Cloud Platform.	) 	\n&bull; 	2022 Python for Machine Learning &amp;Data Science Masterclass: Udemy	 	\n(Data Preprocessing, Regression, Classification, Clustering, Dimensionality Reduction	) 	\n&bull; 	Python for Data Science, AI &amp; Development: Coursera 	 	\n(Python programming logic using Branching, Loops, Functions, Objects &amp; Classes.	 	\n Python Basics including Data Types, Expressions, Variables, and Data Structures.	) 	\n&bull; 	The Complete SQL Bootcamp: Udemy	 	\n(PostgreSQL  and  PgAdmin  |  GROUP  BY  statements  and  SQL  JOIN  commands  |  Creating \nDatabases and Tables.	) 	\n          	 	\n Extra	-Curricular Activities	  	\n&bull; 	Secured 2	nd Position in 600 metres running in the year 2018.	 	\n \n! self	-declaration by student', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-06-24 05:31:33', 0),
(365, 86, 1, NULL, NULL, '1_86_302111230667904b5a9330_Naila_Nausin_Resume_main.pdf', 'Naila_Nausin_Resume_main.pdf', 'Naila Nausin\nMIG 1/81 Hudco Bhilai, Chhattisgarh\n� +91 9340984243\n#nausinnaila@gmail.com �\nlinkedin.com/in/nausinnaila �\ngithub.com/NAUSINNAILA Summary\nHighly motivated professional with a robust educational foundation in both Data Science and Software Engineering.\nMy unique skill set, seamlessly integrating expertise in Data Science and Software Engineering, positions me as a\nversatile and innovative contributor in the field of computer science.\nEducation Dhirubhai Ambani Institute of Information and Communication Technology\n2022 &ndash; 2024\nM.Tech. in Machine Learning CPI:7.36\nBhilai Institute of Technology, Durg 2017 &ndash; 2021\nB.Tech. in Information Technology CPI:8.54\nExperience Knowledge Gate Eduventure - LLP\nJune 2021 &ndash; July 2022\nContent and Tech Writer Hybrid\nI collaborated with educators and designers to understand feature requirements and designs, contributing to the\ncreation of accurate documentation. I played a vital role in analyzing and preparing performance reports, offering\nvaluable insights into user experiences. This role honed my skills in collaborative communication, documentation,\nand data analysis in a dynamic hybrid work environment.\nSeed IT Solution, Bhilai May 2019 &ndash; August 2019\nVocational Training Bhilai, Chhattisgarh\nDuring my vocational training at Seed IT Solution, Bhilai, I undertook the responsibility of developing and\nimplementing a user-friendly alert system. This involved utilizing embedded C programming with a focus on IoT\nconcepts. Engaging in the end-to-end development process, from conceptualization to execution, I coded in\nembedded C to facilitate seamless communication between devices. Leveraging IoT principles, I ensured efficient\ndata exchange and real-time monitoring. Additionally, I integrated sensors and actuators to enhance the alert\nsystem&rsquo;s responsiveness and reliability.\nTechnical Skills Languages\n: C/C++, Python, HTML/CSS, SQL\nDeveloper Tools &amp; IDEs : Jupyter-Notebook, Google-Colab, Visual Studio Code.\nTechnologies/Frameworks : Git/ GitHub, Plotly, Scikit-Learn, Matplotlib, Pandas, NumPy, TensorFlow, Keras.\nKnowledge of Core Sub jects : Machine Learning, Deep Learning, Natural Language Processing, Information Retrieval,\nOperating Systems.\nLeadership / Extracurricular Teaching Assistant (TA)\nAugust 2022 &ndash; Present\nAs a Teaching Assistant (TA), I played a crucial role in supporting the teaching and learning process,\ncollaborating closely with professors and instructors to enhance the academic journey of students. In my first\nsemester, I served as a TA for &ldquo;Language and Literature&rdquo; under Prof. Amishal Modi for B.Tech first-year\nstudents. This involved conducting labs and tutoring a sizable batch of 360 students, ensuring a clear\nunderstanding of the covered concepts. In subsequent semesters, I took on the role of a TA for &ldquo;Software\nEngineering&rdquo; (IT-314) under Prof. Saurabh Tiwari for B.Tech Pre-final year students. My responsibilities\nincluded conducting quizzes, labs, and tutoring, as well as grading assignments, providing constructive\nfeedback, facilitating discussions, and group work, and offering mentorship and support to students.\n\nTechnical Pro jects\nMulti-class fake news detection using IR Models\n|Python October 2023\nIn October 2023, our pro ject focused on combating the rising tide of fake news in the digital realm. We aimed to\nassess the efficacy of advanced language models&mdash;specifically GPT-2, Recurrent BERT, and RoBERTa&mdash;in\ndetecting fake news within the English language context. Leveraging the transformative capabilities of models like\nBERT and RoBERTa, we scrutinized their performance, ultimately finding that GPT-2 exhibited superior\nclassification abilities for English news. Our evaluation extended to practical application, testing the model on news\nfrom the Politifact website, where it demonstrated moderate effectiveness according to the &rdquo;truth-o-meter.&rdquo; This\nwork contributes to the ongoing endeavors to enhance fake news detection using state-of-the-art language models.\nProbabilistic Forecasting using deep learning models |Python July 2023\nIn this pro ject, we addressed the challenges presented by the chaotic and uncertain nature of real-world time-series\ndata. Recognizing the limitations of single-point forecasts in capturing the inherent complexities, our ob jective was\nto enhance reliability by obtaining a narrow interval for future value estimation. Leveraging deep learning models in\nPython, we focused on quantifying uncertainties within the data. The methodology involved advanced techniques\nto navigate the chaotic and random aspects of the time-series data, ensuring a more accurate and nuanced\nforecasting approach.\nCollaborative-based recommendation system on Movie lens dataset(100k) |Python February 2023\nI undertook the development of a collaborative-based recommendation system using the Movie Lens dataset (100k)\nwith the primary goal of analyzing and evaluating data within the movie domain. The pro ject involved the creation\nof a collaborative system, encompassing the writing of code and utilizing exploratory data analysis (EDA)\ntechniques to extract valuable insights from the MovieLens dataset. Through this initiative, the aim was to enhance\nthe understanding and utilization of collaborative filtering methodologies for effective and personalized movie\nrecommendations.\nClassification on MNIST-fashion dataset |Python October 2022\nIn October 2022, I engaged in a pro ject focused on image classification using the MNIST-Fashion dataset. The\nob jective was to design a robust model incorporating various layers to extract features from images and facilitate\naccurate classification into distinct fashion categories. Employing a convolutional neural network (CNN)\narchitecture, the pro ject aimed to leverage the power of deep learning to enhance the model&rsquo;s ability to discern\nintricate patterns within the dataset, contributing to effective and precise classification outcomes.', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-06-24 05:31:33', 0),
(366, 86, 1, NULL, NULL, '1_86_1158719229667904b5a9acd_pradeep_j_resume.pdf', 'pradeep j resume.pdf', '(+91)	-637906924	7                             	     	                  	  PRADEEP	 J                    	                             	                    	  Linked	In/ pradeep	 	\npradeepvlytr29@gmail.com	       	    	           	    	DATA SCIENTIST	/ML ENGINEER	                         	         	              	  github.com/pradeep	 	\nPROJECTS	 	 	\nNext	-word prediction application,	                         	          	                                                         	           	                                	 APR 	2024	 &mdash; Present	             	     	\nM.Sc Major project, Department of 	 Computer Applications, Bharathiar University	                                              	 	\n&bull; Using 	YouTube	-DL	 to download videos from YouTube and utilizing 	FFmpeg 	to extract audio	. 	\n&bull; Designed	 a whisper	-to-text conversion model, to accurately transcribe audio speech into written text. 	Utilizing  	tokenization	 	\ntechniques to break down text into smaller.	 	\n&bull; Deep learning techniques to train an 	LSTM	 algorithm for predicting subsequent sentences.	 	\nPharmacy Order Chatbot	,    	                                                                                                                	                                 	Dec 2023	 &mdash; Dec 2023	           	     	\nM.Sc Mini project, Department of Computer Applications, Bharathiar Universit	y                                             	 	\n&bull; Development of a cutting	-edge Pharmacy Order Chatbot, 	using	 Dialogflow	, offering two key features	. 	\n&bull; New Order Intent: Seamlessly place orders with a user	-friendly chat interface.	 	\n&bull; Track Intent: Stay updated on order status in real	-time.	 	\n&bull; Leveraging	 FastAPI 	for efficient backend processing and 	sql	 for secure storage of order and tracking data.	 	\nText	-based Personal Assistant	,                 	                                                     	                                  	                                  	 Apr 2024	 &mdash; Apr	 2024	 	\n&bull; Developed a text	-based personal assistant	, Fine	-tune	 the	 Palm2	 transformer architecture to inter	act with an 	sql	 database, leveraging 	\nthe capabilities of 	sql	 database langchain	.  	\n&bull; Utilized the 	Hugging Face	 embedding to create embedding vectors that facilitate the identification of word similarities.	 	\n&bull; ChromaDB to store embedded vectors, reducing	 bias	 through the application of few	-shot learning techniques.	 	\nBook reader (private AI)	, 	                  	           	                                                                             	                             	Apr	 202	4 &mdash; Apr	 202	4 	\n&bull; Created a local Retrieval Augmented Generation (RAG) pipeline for conversational interactions with PDF files.	 	\n&bull; Integrated the retrieval component with the 	Mistral Llama	 model for generating context	-aware responses.	 	\n&bull; Loaded a PDF file using the 	UnstructuredPDFLoader	 and split the loaded PDF data into chunks using the RecursiveSplitter.	 	\n&bull; Created embeddings of the chunks using OllamaEmbeddings, utilizing the from_documents method of Chroma to generate a \nnew vector database, incorporating the updated chunks and 	Ollama	 embeddings.	 	\n&bull; Retrieves relevant context from the updated vector database, generates an answer based on both the context and the question, \nand then returns the parsed output.	 	\nAI	-Powered Resume Enhancement Too	l,                                                                               	                                     	Apr	 202	4 &mdash; Apr	 202	4 	\n&bull; Resume  Adviser, 	 leverages  the  power  of  Google  Gemini	-Pro  and  PyPDF2  to  transform  your  resume  into  a  standout 	\nprofessional documen	t. 	\n&bull; Using 	PyPDF2	, the tool accurately extracts and preprocesses text from your PDF resum	e 	\n&bull; Google 	Gemini	-Pro	 analyzes the content to provide a detailed resume score, highlighting areas for improvemen	t 	\nImage	 to captions,	 	                                                                                                                	                                       	Apr	 202	4 &mdash; Apr	 202	4 	\n&bull; Engineered an AI tool capable of generating captions for 	images by analyzing their content	. 	\n&bull; Designed	 a feature extraction module utilizing 	VGG16	 to extract image features.	 	\n&bull; Developed a sequence	-to-sequence	 module	 with an encoder	-decoder architecture. The encoder comprises embedding layers 	\nfollowed by 	LSTM	 layers, while the decoder consists of additional layers for generating output sequences.	 	\n&bull; Attained a 	Bilingual Evaluation	 Score of 0.15 in the image caption 	framework	. 	\nML	-based	 web	 application	 for	 predicting	 Bank	 customer	 Churn	 using	 Deep	 Learning	, 	             	                     	Feb 	202	4 &mdash; Feb 	202	4 	\n&bull; Leveraged pre	-existing datasets from Kaggle to train a deep neural network model in 	TensorFlow	 due to the lack of original customer data 	\nin India.	 	\n&bull; Scrutinized  the  data  for  analysis,  including  pre	-processing  and  cleaning,  and  provided  insights  on  the  data  through 	  and  created  a  web 	\napplication using Streamlit to predict customer churn based on user input.	 	\n&bull; Created 	ANN	 and 	CNN 	models for predicting customer churn dataset. Achieved an accuracy of 88% in predicting customer churn through 	\nthe developed model, which can be helpful to identify potential customer churn.	 	\nHand Landmark Classification,	                                                                                           	                             	Dec	 202	3 &mdash; Dec	 202	3 	\n&bull; Gathered the dataset using 	OpenCV	 in conjunction with a webcam to capture custom frames and store the data in a repository.	 	\n&bull; Utilized the 	Mediapipe	 Hand Landmarks Detector	 to extract features from hands	. 	\n&bull; Incorporated a 	Random forest	 model with 	100 decision	 trees to achieve a 	95% accuracy	 rate in hand landmark classification.\n\nEDUCATION	 	 	\nMaster	 of Science,	 Data	 Analytics,	 Bharathiar	 University,	 coimbatore	 GPA:	 7.80/10.00	                            	                          	Jun	 202	2 &mdash; May	 202	4 	\nBachelor of science, statistics ,	Government Art&rsquo;s college, coimbatore, GPA: 7.50/10.00                    	                               	Jul	y 2019 	&mdash; May 2022	 	\n \n \nCOMPETITIONS	 	 	\nContributed Ideation for a Problem Statement in Smart India Hackathon 2023	 	\n&ndash; Implementation of Leaf Feature Extraction Model Using VGG16 CNN Architecture.	 	\n&ndash; Leaf Disease Classification Using CNN Model.	 LLM	-Powered Web Application Providing Solutions for	 farmers.	 	\n \nSKILLS	 	 	\nLanguages	 	Python,	 R, SQL	 	\nLibraries	 &amp; Tools	 	Pandas, Numpy, Matplotlib, Seaborn, Plotly, Scipy, Tkinter	, Scikit	-learn, TensorFlow, Keras, NLTK, Flask, 	\nBeautifulSoup, PowerBI, Tableau, GIT, Github, Spacy, FastAPI	. 	\nData	 Wrangling	 	Data generation, Data Extraction, Data Cleaning, Exploratory Data Analysis, Feature Engineering, \nFeature  selection,  Data  visualization,  Web  scraping,  text  summarization,  topic  modeling, \nsentiment analysis.	 	\nML	 Skills	 	Data  Modeling,  Clustering  &amp;  Classification,  Quantitative  Analysis,  Regression,  Predictive \nModeling, Statistical Modeling, Model Validation, Model deployment, NLP, LLM, Hugging face, \nTensorFlow Hub, CNN &amp; RNN, LSTM, ANN, BERT, Transformers.	  	\n \nCERTIFICATIONS	 	 	\n&bull; Hacker	 Rank	 - SQL	 (Basic)	 	\n&bull; NPTEL	 - Machine	 Learning,	 ML	 	\n&bull; UiPath	 - Introduction	 to RPA	 and	 Automation	 	\n&bull; Coursera	 -   Advanced Data Science	 	\n&bull; Cognitiveclass  	-Data 	Analysis with python', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-06-24 05:31:33', 0);
INSERT INTO `resume` (`id`, `screeningId`, `adminId`, `candidateId`, `candidateDetailsId`, `resumeName`, `resumeOriginalName`, `resumeContent`, `isSkillScreened`, `isResumeScreened`, `isCron`, `isCandidate`, `isStatus`, `candidateShortlist`, `isInterviewAssign`, `enableInterviewReport`, `gptLanguageId`, `interviewAssignDate`, `psychoAssignDate`, `interviewValidity`, `isPsychoAssign`, `psychoValidity`, `created`, `createdBy`) VALUES
(367, 86, 1, NULL, NULL, '1_86_1071212822667904b5aa1fc_priyanka-Resume_(1).pdf', 'priyanka-Resume (1).pdf', 'Priyanka	 Kommuri	 	Hyderabad	 	\n6300506894	 	\npriyankakommuri182	@gmail.com	 	\n 	\nProfessional	 Summary:	- 	\n 	\n&bull; 	I  have  1.5  years  of  work  experience  as 	Data  Analyst 	with 	strong  analytical  skills,  statistical	 	\nmodelling,  predictive  modelling	,  and  Segmentation  Analysis 	to  drive	 high	-impact  business	 	\noutcomes through	 data	-driven	 innovations	 and	 decisions.	 	\n&bull; 	Experience	 with	 varied	 data	 sources	 such	 as	 semi	 structured,	 unstructured,	 time	 series.	 	\n&bull; 	Hands	 on Experience	 in Python	 and	 SQL	. 	\n&bull; 	Familiar	 with	 Reporting	 tools	 like	 Power	 Bi. 	\n&bull; 	Hands on experience with all phases of Data Analysis 	and Data Science project life cycle	 	\nincluding Exploratory Data Analysis: 	Data Extraction, Data Cleaning, Data Visualization	 	\nand	 building	 Models.	 	\n&bull; 	Collaborate	 with	 cross	-functional	 teams	 to	 ensure	 data	 accuracy	 and	 completeness	 	\n&bull; 	Experience	 with	 using	 libraries	 such	 as	 Matplotlib,	 Seaborn,	 Pandas	, NumPy,	 Plotly	 and	 	\nStats Models.	 	\n&bull; 	Hand	 on	 Experience	 in Designing	 the	 Documents	 for 	Clients	 as	 well	 for	 Internal	 Purpose.	 	\n&bull; 	Involved	 in Developing	 the	 Machine	 Learning	 Models	 like	 Logistic	 Regression,	 Linear	 	\nregression,	 K- Nearest	 Neighbour,	 Naive	 Bayes,	 Support	 Vector	 Machines,	 Decision Trees.	 	\n&bull; 	Excellent	 communication	 and	 leadership	 skills.	 	\n&bull; 	Played	 a key	 role	 in scaling	 the	 company&#039;s	 operations	 and	 support	 the	 teams	 in making	 	\ndata	-driven	 decisions.	 	\n 	\nEducation	 : 	\n 	\n&bull; 	B.tech (ECE) in Malla Reddy College of Engineering For Women 	passed out in 2018	-2022 with an	 	\naggregate	 of 7.3	 CGPA.	 	\n 	\nSkills	 : 	\n  	\n&bull; 	C, Python	 	\n&bull; 	PostgreSQL,	 Mongo	 DB,	 SQL	 Server	 	\n&bull; 	Django,	 Streamlit	 	\n&bull; 	Power	 Bi 	\n&bull; 	PyCharm,	 Jupyter,VScode	 	\n&bull; 	SQL	 	\n&bull; 	HTML,	 CSS	 	\n&bull; 	NumPy,	 Pandas,	 Matplotlib,	 	\nPlotly,	 Seaborn	 	\n&bull; 	Basics	 in Machine	 Learning	 	\n 	\nProfessional	 Experience:	 	\nClinztech	 Research	 Solutions	 Private	 Limited,Hyderabad	 	\nAssociate	 Software	 Engineer	 - May	 2022	 &ndash; April	 2023	 	\n 	\nAgasthaya 	Edtech	 Private	 Limited,	 Banglore	 	\nPython	 Developer	 &ndash; Oct	ober 	2023	 &ndash; March 2024	 	\n \nData Science Intern 	&ndash; Grocareer 	 	\nMarch 2023	&ndash;Current 	&ndash;Hyderabad,Telangana\n\nProject	 1:	 	\nClient:	 Education	 Ind	ustry,	 India.	 	\nDescription: EduTrack is a comprehensive the School Management 	System with	 	\nMachine  Learning  Integration  aims  to  provide  a  comprehensive  platform  for	 	\nmanaging	 various	 aspects	 of a school&#039;s	 operations	 while	 leveraging	 machine	 learning	 	\nalgorithms	 to	 enhance	 decision	-making	 processes.	 The	 system	 includes	 	\nfunctionalities	 	for	 	student	 	management,	 	teacher	 	management,	 	course	 	\nmanagement,	 attendance	 tracking,	 performance	 analysis,	 and	 predictive	 analytics.	 	\nTools	 &amp; Technologies:	 Python,	 Django,	 HTML,	 CSS,	 JavaScript,	 Postgresql,	 Manual	 	\ntesting, Numpy,	 Pandas	 ,Scikit	-learn,	 TensorFlow.	 	\nResponsibilities:	 	\n&bull; 	Designed and developed user interfaces using HTML, CSS, and	 	\nJavaScript. Designed and optimized the database schema using	 	\nPostgreSQL.	 	\n&bull; 	Implement server	-side logic using Django, including authentication,	 	\ndata	 models,	 and	 business	 logic.	 	\n&bull; 	Integrated	 frontend	 components	 with	 backend	 functionalities.	 	\n&bull; 	Develop machine learning models using appropriate algorithms and	 	\nlibraries to analyze student 	performance, predict outcomes, or	 	\nprovide	 recommendations.	 	\n&bull; 	Communicated progress, challenges, and proposed solutions	 	\neffectively	 within	 the	 team.	 	\n 	\nProject	 2:	 Sentiment	 Analysis	 of	 Restaurant	 Reviews	 	\nIn this 	project, I conducted sentiment analysis on 	restaurant reviews to gain insights	 	\ninto	 customer	 satisfaction	 and	 sentiment	 trends.	 The	 goal	 was	 to	 help	 restaurant	 	\nowners and managers understand customer 	feedback better and make data	-driven	 	\ndecisions	 to improve	 their	 dining	 experience.	 	\nTools &amp; Technolo	gies: 	Python, Pandas, NumPy, Plotly, PyCharm, Matplotlib, Naive	 	\nBayes, TensorFlow/Keras,	 Support Vector	 Machines.	 	\nResponsibilities:	 	\n&bull; 	Collected and pre	-processed a diverse dataset of customer feedback,	 	\nensuring	 data	 quality.	 	\n&bull; 	Developed a sentiment analysis 	model with [73%] accuracy to classify	 	\nreviews	 as positive,	 negative, or	 neutral.	 	\n&bull; 	Train machine learning models such as Support Vector Machines	 	\n(SVM), Naive Bayes, or neural networks using libraries like Scikit	-learn	 	\nor TensorFlow/Keras.	 	\n&bull; 	Developed an 	interactive dashboard for visualizing and exploring	 	\nsentiment	 analysis	 results.\n\n&bull; 	Collaborated with a team to ensure successful project execution and	 	\neffective	 communication of	 findings.	 	\n 	\nProject	 3:	 2019	 Key	 Issues	 Study	 Finance	 - The	 Hackett	 Group	 	\nLed	 the	 &quot;2019	 Key	 Issues	 Study	 Finance&quot;	 at The	 Hackett	 Group,	 managing	 end	-to	- 	\nend  analysis  of  prevalent  challenges  and  priorities  in  Finance  organizations.	 	\nDesigned 	and  executed  surveys,  utilizing  Python  with  Pandas  for  data  analysis.	 	\nEnsured data i	ntegrity and accessibility through robust data management 	practices.	 	\nDeveloped	 visually	 informative	 reports	 and	 dashboards	 in Tableau	 for	 stakeholder	 	\ncommunication.	 Orchestrated	 collaborative	 project	 management	 for	 timely	 	\ncompletion.	 	\nTools	 &amp; Technologies: 	Python,	 Pandas,	 NumPy,	 Seaborn,	 SQL,	 Django,	 Jupyter,	 Matplotlib	 	\nResponsibilities:	 	\n&bull; 	Responsible for data identification, collection, exploration, cleaning	 	\nfor modelling.	 	\n&bull; 	Created	 Dashboards	 Using	 Django.	 	\n&bull; 	Visualize, interpret, report findings, and develop 	strategic uses of data	 	\nby	 python	 libraries	 like	 NumPy, Pandas.	 	\n&bull; 	Strong	 skills	 in data	 visualization	 like	 Matplotlib.	 	\n&bull; 	Participated	 in all	 phases	 of	 data	 mining	 and	 visualization.	 	\n&bull; 	Orchestrated the design and execution of surveys, collecting insightful	 	\ndata	 from	 a diverse	 range	 of	 finance	 professionals.	 	\n&bull; 	Implemented robust data management practices, ensuring the	 	\nintegrity	 and accessibility of survey	 data	 for	 analysis.	 	\n&bull; 	Applied Python with Pandas for data analysis, revealing significant	 	\ninsights	 that	 directly	 informed	 the	 strategic	 objectives	 of	 the	 study.	 	\n&bull; 	Developed visually impactful reports and dashboards in Tableau,	 	\nfacilitating stakeholders&#039; grasp and interpretation of key findings with	 	\nease.	 	\n \nProject	 4:	 	\nProject  is  about  collecting  and  maintaining  data  rela	ted  to  the  doctors  and	 	\nassociated	 with	 the	 list	 of	 Hospitals	 requested	 by	 the	 client	 (only	 when	 	\navailable	 in Doctors	 URL)	 There	 are	 about	 3000	 hospitals	 in the	 current	 scope.	 	\nTools	 &amp; Technologies: 	Python,	 Pandas,	 NumPy,	 Seaborn,	 SQL,	 Jupyter,	 PyCharm	 	\nResponsibilities:	 	\n&bull; 	Participated	 in all	 phases	 of	 data	 cleaning,	 developing	 models	 to	 	\ndeliver	 data	 science	 solutions.	 	\n&bull; 	Retrieving	 data	 from SQL	 Server	 database	 by	 writing	 SQL	 queries.	 	\n&bull; 	Connected Database with Jupyter notebook for modelling and Matplotlib for	 	\nvisualization	 and	 reporting.', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-06-24 05:31:33', 0),
(368, 86, 1, NULL, NULL, '1_86_959739676667904b5ab131_Shikhar_Aditya_CV_v9.pdf', 'Shikhar_Aditya_CV_v9.pdf', 'Shikhar Aditya\nEmail: satyamshikhar@gmail.com Mobile: +91 9082355413\nEducation &bull;\nCentral University of Ra jasthan\nAjmer, India\nMaster of Science - Computer Science(Data Science and Analytics); GPA: 8.06 2021 - 2023\nCourses: Probability Distribution, Linear Algebra, Statistical Methods,Computing for Data Science, Machine Learning, Cloud\nComputing, Databases,Data Mining,Operations Management,Hadoop for Big Data\n&bull; University of Mumbai\nMumbai, India\nBachelor of Science - Computer Science; GPA: 9.93 2018 - 2021\nCourses: Operating Systems,Databases,Networking,Programming with C,Linux,Data Structures and Algorithms\nSkills Summary &bull;\nLanguages : Python, R, Java, SQL, HTML/JS/CSS\n&bull; Frameworks : Scikit-learn, Flask, Django, Apache Airflow, Android Studio, React\n&bull; Tools : GIT, Prompt Engineering, Power BI, Excel, Pyspark, Databricks, Selenium\nWork Experience ◦\nData Analyst - Advisai Consulting, Lucknow : [Nov 2023 - Present]\n&lowast; Designed and deployed an AI-driven news app on AWS, boosting daily news published by 400%. Integrated AI news\nsummarization for smoother publishing workflows\n&lowast; Analyzed client data to pinpoint inefficiencies in marketing strategies, revealing underperformance in user acquisition\nby current agency. Proposed strategic recommendations resulting in substantial cost reductions and improved ROI\nmetrics.\n&lowast; Produced and delivered weekly and bi-weekly analytics reports using Power BI, enabling clients to track and\nvisualize their performance metrics effectively.\n◦ Backend Engineer and Analyst - LocalWell Healthtech Pvt. Ltd, Bangalore : [Jan 2023 - Oct 2023]\n&lowast; Accomplished creation of Data Pipeline integrating multiple APIs,reducing manual data ingestion and verification\n&lowast; Revamped multiple third party APIs into the system, made their interaction efficient and scalable.\n&lowast; Analysed features and components of application, enhancing user experience\nProjects &bull;\nAI News Aggregator App :\nProblem Statement - Client experienced a substantial deficit in the number of news articles published, hindering their\ncompetitive edge in the market.\nRecognizing the need for a solution, developed an AI-powered news collector app to address this issue. The app&rsquo;s purpose was\nto aggregate news content efficiently from various sources, enabling Client to significantly increase their daily publication\noutput and maintain relevance in their industry.\nTech Stack - Python/Flask, React, ChatGPT API, CSS/JS\n&bull; Web Scraping Data Verification and Decision Support Pipeline :\nProblem Statement - To validate the medications existing in LocalWell&rsquo;s database and incorporate new drugs and products\nsourced from external websites through web scraping.\nDesigned and implemented data pipelines that automated the process of scraping data from various websites, cleaning and\ntransforming the acquired data, and ingesting it into our databases.Resulting in verification of about 300,000 products.\nTech Stack - Python, Flask, Jupyter Notebooks, PostgreSQL, Beautifulsoup, Requests\n&bull; Unified CSV File Integration and Performance Enhancement :\nProblem Statement - Enhance CSV purchase bill handling and optimisation of backend API.\nCreated an efficient API that could identify and categorize both organized and unorganized CSV files, intelligently mapping\ndata to specific software formats for seamless extraction.fine-tuned the code to automatically map CSV files to various\nformats.Cutting processing time from 15 seconds to just 7 seconds.\nTech stack - Python, Requests, Flask, Postman, PostgreSQL\nCertifications &bull;\n*Google Data Analytics Professional Certificate : Coursera - Certification in Foundation of data, Data Processing, Data\nAnalysis, Visualization, Analysis using R Language\n&bull; Machine Learning Specialisation : Coursera - University of Washington - Specialisation in machine learning paradigms -\nClassification, Regression, Clustering ; Tech used - TuriCreate, Python, Jupyter Notebook\nExtracurriculars &bull;\nYoga and fitness\n2023\nSecured second runner up position in yoga competition for breathing exercises and advance poses.\n&bull; Marathons and runs\n2023\nFinished runner up in 8 km run in societies running community. * - ongoing', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-06-24 05:31:33', 0),
(369, 86, 1, NULL, NULL, '1_86_1415029936667904b5abb24_Shobith_Gowda__CV.pdf', 'Shobith Gowda__CV.pdf', 'Email	 : shobithmgowda31@gmail.com	 	\nMobile:	 9964122616	 	\nAddress	 : #2874,	 6th Cross,	 Gandhinagara,	 Mandya	-501401.	 	\nLinkedIn Id: 	https://www.linkedin.com/in/shobith	-gowda	-25b196267	 	\nHackerRank	 : https://www.hackerrank.com/shobithmgowda31	 	\n  EDUCATION	 QUALI	FICATION	 	 	\n 	\nQualification	 	Degree/	 	\nStream	 	\nBoard	 	College	 	 Year	 of	 	\nCompleti	on 	\nCGPA/	 	\nPercentag	 e 	\n10th	 	Science	 	CBSE	 	Sharad	a 	\nVidhyaniketha	na     	         	\nPublic	 School	 	\n March	-2017	 	9.2	 	\n12th	 	PCMB	 	Karnata	 	\nka	 	\nSTG Pre	- 	\nUniversity	 	\nCollege	 	\n March	-2019	 	83.9%	 	\nBachelor 	Of	 	\nEngineering	 	\nInformation	 	\nScience	 and	 	\nEngineering	 	\n- 	PES College of	 	\nEngineering,	 	\nMandya	 (VTU)	 	\n 	\n \nAugust	-2019	 	\nto 	\nJuly	-2023	 	\n8.0	7 	\n 	\n  COMPUTER	 SKILLS	 	 	\n 	\n 	Programming	 Languages	 	: Java, C	 Programming	 , Python, Machine Learning	,  	\n                                                       	Transfer learning	, JavaScript,	 React.js	, Analytics, Data Mining	 	\n 	Web	 Development	 	: HTML,	 CSS	 	\n 	Databases	 	: MySQL,	 SQL	 	\n  INTERNSHIP	 &amp;	 WORKSHOP	 	 	\n 	Completed a Virtual Internship focused on Robotic Process 	Automation (RPA), gaining 	\npractical experience and proficiency in automation technologies.	 	\n 	Completed a workshop focused on Mobile Application Development, gaining skills and \ninsights into the latest industry trends.	 	\n 	Interne	d at WebNet Solutions from June	-2023 to Feb	-2024 as a Software Trainer in Machine 	\nLearning (ML).	 	\n 	\n     PROJECT	S                         	                                    	                                                                                    	 	\n 	\n1. Title    	 : Yoga	 Pose	 Classification	 Using	 Deep	 Learning	 Techniques	 	\n 	Successfully  trained  a  deep  learning  model  utilizing 	Convolutional  Neural  Networks	 	\n(CNNs) to classify 107 distinct yoga poses.	 	\n 	Optimized  model accuracy to an  impressive 92% on test data by  implementing 	transfer	 	\nlearning	 	methodologies  with  pre	-trained 	VGG16	,  strategically  integrating  data 	\naugmentation tech	niques for enhanced performance	. 	\nSHOBITH	 M	 GOWDA\n\n2. Title  	 : Heart	 Rate	 Monitoring	 (IOT)	 	\n 	Engineered  an  innovative  IoT  solution  integrating  the 	MAX30102	 sensor  for  heart  rate 	\nmonitoring and GPS modul	e for precise location tracking	. 	\n 	Utilized  Python  to  streamline 	data  processin	g  and 	visualization	,  enabling  real	-time 	\nmonitoring  of  heart  rate  and  location  data  with  potential  applications  in  healthcare  and \nfit	ness tracking.	.  	\n 	\n3. Title     	 : Hostel	 Management	 Syst	em	 (DBMS)	 	\n 	Engineered  and  executed  a  revolutionary  Hostel  Management  System  using 	HTML, 	\nCSS,  Python,	 and 	MySQL	;  enhanced  guest  check	-in  and  check	-out  operations, 	\nstreamlining processes and increasing 	operational efficiency by 40%.	 	\n 	Achieved  a  30%  reduction  in  wait  time  and  a  remarkable  40%  boost  in  customer \nsatisfaction through the implementation of the system. 	 	\n \n4. Title     	 : Sports	 Result	 Prediction	 (ML)	 	\n 	Developed  a 	machine  learning	 model  using 	Python,	 NumPy,  Pandas	,  and 	logistic 	\nregression	 to predict sports outcomes with an 	accuracy rate of 82% 	on test data.	 	\n 	Implemented advanced statistical analysis te	chniques, resulting in a 90	% 	improvement in 	\npredictive accuracy, leading to successful forecasts of 	sports events	. 	\n 	\n  ACHIEVEMENTS	 &amp; AWARDS	 	 	\n 	\n 	District level KhoKho player, showcasing dedication and skill in competitive sports.	 	\n 	Engaged in diverse cultural activities throughout schooling and college, f	ostering teamwork 	\nand creative 	activities.	 	\n 	\n \n \n \n 	\n 	\n \n \n \n \n \n \n \n \n \nDeclaration	 	\nI hereby	 declare	 that	 the	 information	 furnished	 above	 is true	 to the	 best	 of my	 knowledge	 and	 belief.', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-06-24 05:31:33', 0),
(370, 86, 1, NULL, NULL, '1_86_1140625242667904b5ac360_Vivekkumar-Mohan-Ghodmare-DSUP_(2).pdf', 'Vivekkumar-Mohan-Ghodmare-DSUP (2).pdf', 'Viv e k ku m ar M oh an  G hod m are	\nD ata  S cie n tis t |   D ata  A naly st	\nviv e k g h od m are 56 77@ gm ail. c o m	 	0 956 19 46 72 5	 	P un e ,  M ah ara sh tr a	 	0 5/0 6/1 9 97	 	In dia n	 	\nS in gle	 	w ww.li n ked in .c o m /in /v iv e k ku m ar- g h od m are -5 15 4 6 32 19	 	g it h u b.c o m /V gh od m are	 	\nE D UCATIO N\nB.E  	C iv il 	E ngin eerin g 	, P ro f. 	R am  	Meg h e 	C olle g e 	O f 	\nE ngin eerin g 	A nd 	M an ag em en t 	B ad n era  	A m ra va ti 	, 	\nM ah ara sh tr a\n2 0 15  &ndash;  2 0 21	 |  	A m ara vti,	 I n dia	\nP erc e n ta g e : -  6 6.4 2 %\nH SC  	, N .K  	Ghok h ale  	H ig h er 	S eco n dary  	C olle g e 	O f 	\nS cie n ce\n2 0 14  &ndash;  2 0 15	 |  	A ko la ,	 I n dia	\nP erc e n ta g e : -  6 2 .6 2 %\nS SC  	, J a g ru ti 	V id ya la ya	\n2 0 13	 |  	A ko la ,	 I n dia	\nP erc e n ta g e : -  7 7.4 5%\nS K IL L S	\nPro g ra m min g L an gu ag es: P yth on , S Q L\nD ata  M an ip u la tio n  a n d A naly sis : P an das, N um Py,\nM ach in e L ea rn in g: S cik it - L ea rn , X G Boost,	 	\nL ig h tG BM , T en so rF lo w , K era s, P yT o rc h , E nse m ble	 	\nM eth od s\nD eep  L ea rn in g: N eu ra l N etw ork s, C N Ns, R N Ns,	 	\nL S T M , L L M , R AG , T ra n sfo rm ers\nN atu ra l L an gu ag e P ro ce ssin g ( N LP ): T ex t	 	\nA naly tic s, S en tim en t A naly sis , T o p ic  M od eli n g,	 	\nN ER , W ord  E m bed din gs ( W ord 2V ec, G lo V e),	 	\nT ra n sfo rm er M od els  ( B ER T, G PT)\nD ata  V is u ali z a tio n : M atp lo tli b , S ea b orn , P lo tly ,	 	\nT ab le a u , P ow er B I\nD ata b ase  M an ag em en t: S Q L D ata b ase s ( M yS Q L,	 	\nPostg re S Q L)\nFra m ew ork s : -  D ja n go ,  F la sk	\nC ER TIF IC ATE S	\nGre a t L ea rn in g : -  D ata  S cie n ce\nC od esp yd er T ech n olo g ie s : -   D ata  S cie n ce  ,  A L/M L\nSim pli le a rn  : -  G en ara tiv e  A I\nG re a t L ea rn in g :  -  O ra cle  S Q L\nGre a t L ea rn in g : -  P yth on\nG re a t L ea rn in g : -  H TM L ,  C SS ,  J a va S crip t	\nIN TE R EST S\nAL/M L ,  G en ara tiv e  A L ,  L arg e L an gu ag e\nM od els (L L M )	\nPR O FE SSIO N AL E X PE R IE N CE\nSen io r 	F in an cia l 	A dvis o r	\nC on ce n tr ix\np re se n t	 |  	P un e,	 I n dia	\nW ork  a s a  f in an cia l a d vis o r o n  i n su ra n ce  p ro ce ss	 	\na n d r e sp on sib le  f o r h an dl t h e c la im  t o  i n clu de	 	\nn eg atia tio n  a n d s e ttle m en t ,  r e vie w  a n d e va lu ate  a ll	 	\nw ork  r e la te d  a cc id en t r e p ort&#039;s  f o r c o m ple te n ess a n d	 	\ncla rit y  o f d ata  ,  A naly se d  d ata  a s n eed ed  t o  e n su re	 	\nc o m pli a n ce  w it h  p oli c y  a n d r e g u la to ry  r e q u ir e m en ts\nS kills  u se d  : -  1 . D ata  A naly sis  ,  2  .  F in an cia l A naly sis\nP R O JE C TS\nHou se  	P ric e  	P re d ic tio n  	:-  	M L 	( D ata  	C le a n in g 	, 	\nF ea tu re  	E ngin eerin g 	,  H yp erp ara m ete r 	T un nin g 	)	\np re se n t\n1.I m port P ack ag es\n2 .I m port a n d E D A\n3.D ata  V is u ali z a tio n :\n4.E nco d in g D ata\n5 .M od eli n g\nD ig it  	a n d 	A lp h ab et 	R eco gn it io n  	:-  	S V M  	, A N N 	, C N N	\n1.I m port L ib ra rie s a n d L oad  D ata se t:\n2 .P re -p ro ce ss D ata\n3 .C re a te  M od els\n5 .E va lu ate  M od els\n6 .P re d ic t D ig it s  a n d A lp h ab ets\nN ex t 	W ord  	P re d ic tio n  	:-  	N atu ra l 	L an gu ag e 	\nP ro ce ssin g 	(N LP )	\n1.D ata  P re p ara tio n\n2.T o ken iz a tio n\n3.S eq u en ce  G en era tio n\n4.B uild  L S T M  M od el\n5.T ra in  T he L S T M  M od el\n6 .E va lu ate  T he M od el\n7.G en era te  P re d ic tio n\nA dva n ce d  	S to ck  	P atte rn  	P re d ic tio n :-  	L S T M  	wit h  	\nth e 	A tte n tio n  	M ech an is m	\n1.S etu p I n sta lle d  a n d i m porte d  T en so rF lo w , K era s,	 	\ny fin an ce .\n2 .D ata  P re p ara tio n\n3B uilt  L S T M  m od el\n4 .E nhan ce m en ts\n5 .T ra in in g\n6.E va lu atio n\n7.P re d ic tio n  o n  F o re ca ste d  n ex t 4  d ays&#039;  s to ck  p ric e s.\n8 .U se r I n pu t  E nab le d  d yn am ic  p re d ic tio n  f o r	 	\nsp ecif ie d  d ate s.\n\nLA N GUAG ES\nEngli s h  ,  M ara th i ,  H in di	\nD EC LA R ATIO N\nI h ere b y d ecla re  t h at t h e d eta ils  a n d i n fo rm atio n\ng iv e n  a b ove  a re  c o m ple te  a n d t r u e t o  t h e b est o f m y\nkn ow le d ge	\nV iv e k ku m ar&nbsp;M oh an &nbsp;G hod m are', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-06-24 05:31:33', 0),
(371, 87, 1, 4, NULL, '1_87_196203955669730bbf0935_Asmiya_Begum_N-Developer-Connected_Vehicle.pdf', 'Asmiya Begum N-Developer-Connected Vehicle.pdf', 'Asm iy a  B eg u m  N\nA ndro id  D eve lo p er\n	C hen nai		+ 91 9 003606100		asm iy a b eg u m .n m r@ gm ail.c o m	\nasm iy a -b eg u m\nasm iy a -b eg u m	\nE xp erie n ce d  A ndro id  D eve lo p er w it h  3 .3  y e ars  o f e x p ertis e  i n  b u ild in g h ig h -q u ali t y  a p pli c a tio n s t h ro u gh  c le an\nco d e a n d b est p ra ctic e s. P ro fic ie n t i n  u sin g d iv e rs e  l i b ra rie s a n d f r a m ew ork s t o  a d dre ss  r e al- w orld  c h alle n ges.\nD ed ic a te d  t o  m ain ta in in g s tr u ctu re d  c o d e o rg a n iz a tio n  a n d c o n sis te n tly  i m pro vin g c o d e q u ali t y . A ctiv e ly  s e ek in g a\nn ew  r o le  t o  e x p an d k n ow le d ge o f e m erg in g t e ch n olo gie s a n d c o n tr ib u te  t o  s o lv in g u se r c h alle n ges.\nW ORK  E X PER IE N CE\nH TC G lo b al S erv ic e s\nM ob ile  A ppli c a tio n  D eve lo p er	\nS ep  2 023 -  P re se n t	\nChen nai	\n	h tt p s:// w ww.h tc in c.c o m /	\nHTC  G lo b al S erv ic e s p ro vid es I T  a n d B usin ess  P ro ce ss  S erv ic e s a n d S olu tio n s t h at h elp  b u sin ess e s m ak e d ig it a l\nch an ge h ap p en .	\nColla b ora te d  o n  f e atu re  i m ple m en ta tio n  f o r t h e H orm an n p ro je ct.\nW ork ed  f o r t h e P en sk e c li e n t o n  i m ple m en tin g s u pply  c h ain  m an agem en t f e atu re s, i n clu din g o rd er t r a ck in g\nan d w atc h li s t f u n ctio n ali t ie s.\nW ork ed  o n  t h e g o ogle  m ap s t o  t r a ck  t h e s h ip m en ts  i n  a p pli c a tio n .\nIm ple m en te d  M SA L i n  a n  A ndro id  a p p t o  f a cili t a te  s e cu re  u se r a u th en tic a tio n  v ia  A zu re  A D, h an dli n g t o k en\na cq u is it io n  a n d r e n ew al f o r a cce ss in g p ro te cte d  A PIs .	\nG ofr u gal T ech n olo gie s P vt L td\nA ndro id  D eve lo p er	\nF eb  2 021 -  J u n  2 023	\nC hen nai	\n	h tt p s:// w ww.g o fr u ga l.c o m /	\nGofr u ga l i s  a  s o ft w are  c o m pan y t h at p ro vid es r e ta il /  P O S s o lu tio n s f o r s m all a n d m ed iu m  s iz e d  b u sin ess e s a cro ss\nv a rio u s i n du str ie s.	\nD eve lo p ed  m ob ile  a p pli c a tio n  w it h  h ig h -p erfo rm an ce  b arc o d e a n d Q R c o d e s c a n nin g.\nE nab le d  o ffli n e c a p ab ili t y  a n d u tili z e d  a d va n ce d  a lg o rit h m s f o r e ffic ie n t c o m pu ta tio n .\nU pgra d ed  c a m era  s c a n nin g f r o m  G M S V is io n  t o  C am era X  f o r f a ste r b arc o d e d ete ctio n .\nExp erie n ce d  i n  A ndro id  f e atu re s l i k e R xJa va , M VVM , D ata  B in din g, B ro ad ca st R ece iv e rs , F C M , C on te n t\nPro vid ers , O kH tt p , R etr o fit ,N av ig atio n ,a n d K otli n  s p ecif ic  f e atu re s s u ch  a s C oro u tin es, K otli n  S eria li z a tio n .\nIn te g ra te d  w it h  t h e p rin te r s d k t o  s u pp ort t h e i n  a p p p rin tin g. U tili z e d  M VVM  a rc h it e ctu re  f o r m ob ile  a p p\ndeve lo p m en t a n d s e p ara te d  a p p d ata , U I, a n d a p p l o gic  f o r b ett e r c o d e o rg a n iz a tio n  a n d m ain ta in ab ili t y .\nIm ple m en te d  s h are d  v ie w  m od els  f o r i m pro ve d  s c a la b ili t y  a n d c o d e r e u sa b ili t y .\nE xp erie n ce d  w ork in g o n  i m age l o ad in g t a sk s u sin g G li d e,a n d C oil.\nE nhan ce d  m ob ile  a p p s e cu rit y  b y e n cry p tin g b oth  a p p a n d u se r d ata .\nP erfo rm ed  s e cu rit y  t e stin g i n  Z A P , M OBSF  , S Q L m ap .\nG ain ed  e x te n siv e  k n ow le d ge o f m ult it h re ad in g a n d m em ory  m an agem en t f o r o p tim iz e d  a p p p erfo rm an ce .\nA uto m ate d  r e le ase  b u ild  a n d d ep lo ym en t i n  p la ysto re  u sin g f a stla n e.	\nP ro je cts\nI n ve n to ry  C on tr o l\nM ob ile  P O S I n ve n to ry  C on tr o l A ppli c a tio n\n	h tt p s:// p la y.g o ogle .c o m /s to re /a p ps/d eta ils ?id =co m .g o fr u ga l.s to ck m an agem en t&amp; pli = 1\nG oS u re  i s  a n  i n ve n to ry  c o n tr o l a p pli c a tio n  t h at e n ab le s u se rs  t o  p erfo rm  a ll i n ve n to ry -r e la te d  o p era tio n s i n\nP O S. I t  c o n sis ts  o f f o u r m od u le s: s to ck  t a k in g, G RN  ( G ood s R ece ip t N ote ), s to ck  p ic k , a n d s to ck  r e fill . T hese\nm od u le s p ro vid e f u n ctio n ali t ie s f o r m an ag in g s to ck  c o u n ts , r e co rd in g i n co m in g g o od s, p ic k in g i t e m s f o r\nord ers , a n d r e p le n is h in g s to ck .\nIt  i s  a  s tr o n g a n d r e li a b le  a p pli c a tio n  t h at c a n  h an dle  a  l a rg e c u sto m er d ata b ase  w it h ou t s lo w in g d ow n o r\nca u sin g a n y p erfo rm an ce  i s s u es.\nIt  e ffic ie n tly  m an ages e x te n siv e  c u sto m er d ata  w hile  m ain ta in in g h ig h  p erfo rm an ce  l e ve ls .\nIt  i s  a  u se r-fr ie n dly  a p pli c a tio n  t h at w ork s o n  b oth  m ob ile  d evic e s a n d P D A  d evic e s.\nIt  a llo w s u se rs  t o  s c a n  b arc o d es u sin g e it h er t h e d evic e &#039;s  b u ilt - in  b arc o d e s c a n ner o r t h e c a m era . T his  m ak es i t\ne asy  t o  c a p tu re  i n fo rm atio n  a n d m an age i n ve n to ry  e ffe ctiv e ly .\nIt  k eep s d ata  s a fe  a n d s e cu re  i n  b oth  o ff li n e a n d o n li n e m od es, p re ve n tin g a n y l o ss  o f i n fo rm atio n .\nIt  i s  a  n ativ e  A ndro id  a p pli c a tio n  u sin g K otli n , t a rg etin g A ndro id  d evic e s	\nP ric e  C heck er ( K IO SK )\nPric e  a n d L oya lt y  P oin ts  C heck in g A ppli c a tio n\n	h tt p s:// p la y.g o ogle .c o m /s to re /a p ps/d eta ils ?id =co m .g o fr u ga l.g o ch eck .r e le a se\nG oC heck  i s  a  p ric e  t a g  c h eck in g a p pli c a tio n  d esig n ed  t o  b e p la ce d  o n  t h e r a ck s i n  r e ta il s h op s.\nIt  e q u ip p ed  w it h  a  b arc o d e s c a n ner. W hen  a  b arc o d e i s  s c a n ned , i t  d is p la ys t h e d eta ils  o f a n y o ffe rs  a va ila b le\na n d t h e c o rre sp on din g l o ya lt y  p oin ts  f o r t h e c u sto m er.\nI t  s u pp orts  b oth  b arc o d e s c a n nin g a n d c a m era  s c a n nin g f u n ctio n ali t ie s. U se rs  c a n  c h oose  t o  s c a n  b arc o d es\nu sin g a  b arc o d e s c a n ner o r u tili z e  t h e d evic e &#039;s  c a m era  t o  c a p tu re  a n d p ro ce ss  b arc o d e i n fo rm atio n  w it h in  t h e\nap pli c a tio n . T his  p ro vid es f le x ib ili t y  i n  s c a n nin g m eth od s f o r e ffic ie n t a n d c o n ve n ie n t u se .\nIt  i s  a  n ativ e  A ndro id  a p pli c a tio n  u sin g K otli n , t a rg etin g A ndro id  d evic e s.	\nH orm an n S erv ic e  S u pp ort A pp\nD oor I n sta lla tio n  S erv ic e  S u pp ort A ppli c a tio n\n	h tt p s:// p la y.g o ogle .c o m /s to re /a p ps/d eta ils ?id =co m .h orm an n .s e rv ic e su pp orta p pli c a tio n &amp; hl= en &amp; gl= U S\nThe H orm an n s e rv ic e  s u pp ort a p pli c a tio n  i s  d esig n ed  t o  a ss is t i n sta lle rs  a n d s e rv ic e  e n gin eers  b y p ro vid in g\nhelp fu l i n sta lla tio n  a n d t r o u ble sh ootin g i n fo rm atio n .\nIt  i n clu des s e arc h ab le  f a u lt  c o d es, p ara m ete r c o d es, q u ic k  s ta rt t ip s, c o m mon  i s s u es, a n d s c h em atic s.\nIt  f e atu re s m od u le s t o  d is p la y c ir c u it  i m ages, d oor i n sta lla tio n  i n str u ctio n s, a n d t r o u ble sh ootin g g u id es w it h in\nt h e a p p i n te rfa ce .\nA  m od u le  a llo w in g t h e p la yb ack  o f i n str u ctio n al v id eo s d ir e ctly  f r o m  Y ou T ube U RLs w it h in  t h e a p pli c a tio n .	\nSu pply  C hain  I n sig h t\nO rd ers  t r a ck in g a p pli c a tio n  f o r s u ppli e r\n	h tt p s:// w ww.p en sk e.c o m /\nSu pply  C hain  I n sig h t i s  a n  a p pli c a tio n  t h at a llo w s u se rs  t o  t r a ck  l o ad s, o rd ers , v ie w  d eta ile d  o rd er i n fo rm atio n\nalo n g w it h  t im eli n es.\nIt  f e atu re s a n  i n fo rm ativ e  d ash board  w here  u se rs  c a n  v ie w  c o m pan y-s p ecif ic  i n sig h ts  o n  l o ad s, o rd ers ,\nw atc h li s ts , a n d l a te  o rd ers .\nIt  i s  i n te g ra te d  w it h  G oogle  M ap s t o  t r a ck  o rd ers  i n  r e al- tim e.\nT he a p p&#039;s  n etw ork  c a lls  a re  s e cu re d  u sin g t h e M ic ro so ft  A uth en tic a tio n  L ib ra ry  ( M SA L), w hic h  p erio d ic a lly\nr e fr e sh es t o k en s t o  p re ve n t v u ln era b ili t ie s.	\nP ers o n al P ro je cts\nS tr e am Vers e\nM ovie  S tr e am in g A ppli c a tio n\n	h tt p s:// g it h ub.c o m /A sm iy a B eg u m /S tr e am Vers e\nS tr e am Vers e  i s  a  m ovie  s tr e am in g p la tfo rm  t h at h as b een  d eve lo p ed  u tili z in g t h e e x o p la ye r f r a m ew ork .\nIt  f e atu re s a  u se r-fr ie n dly  h om e s c re en  w here  u se rs  c a n  e x p lo re  a  c a ro u se l s h ow ca sin g t h e l a te st a n d m ost\np op u la r m ovie s, a s w ell a s b ro w se  m ovie s c a te g o riz e d  a cco rd in g t o  d if fe re n t g en re s.\nIt  f e atu re s a  d ed ic a te d  v id eo  s tr e am in g i n te rfa ce  b u ilt  o n  t h e p ow erfu l e x o p la ye r f r a m ew ork . T his  i n te rfa ce\nb oasts  a  c u sto m  p la ye r l a yo u t t h at g re atly  e n han ce s t h e u se r e x p erie n ce . U se rs  c a n  e asily  a d ju st m ed ia  v o lu m e,\nsc re en  b rig h tn ess, s e ek  f o rw ard  o r b ack w ard  i n  t h e v id eo, c h an ge t h e s c re en  o rie n ta tio n , a n d e ve n  l o ck  t h e\nsc re en  t o  p re ve n t a cc id en ta l t o u ch es, e n su rin g a  s e am le ss  a n d e n jo ya b le  s tr e am in g e x p erie n ce .	\nS ketc h Flo w\nD ra w in g A ppli c a tio n\n	h tt p s:// g it h ub.c o m /A sm iy a B eg u m /S ketc h F lo w\nS ketc h F lo w  i s  a  m ob ile  a p p t h at l e ts  y o u  c re ate  a rt u sin g v a rio u s b ru sh es a n d c o lo rs . Y o u  c a n  c h an ge\nb ack gro u n ds, u n do, r e d o, a n d c le ar. I t  a llo w s s a v in g d ra ft s  f o r l a te r a n d e x p ortin g a rt t o  s p ecif ic  f o ld ers  a n d\nfo rm ats . Y ou  c a n  a ls o  s h are  y o u r c re atio n s w it h  o th er a p ps s e am le ss ly .	\nW eath erF ore ca st\nW eath er F ore ca stin g A ppli c a tio n\n	h tt p s:// g it h ub.c o m /A sm iy a B eg u m /W eath erF ore ca st\nIt &#039;s  a  w eath er f o re ca stin g a p pli c a tio n  t h at a llo w s u se rs  t o  s e arc h  f o r l o ca tio n s o r p in  t h em  o n  a  m ap  t o  r e tr ie ve\nth e w eath er s u m mary  f o r t h ose  a re as.\nIt  i n clu des a  f e atu re  f o r b ook m ark in g l o ca tio n s, a llo w in g u se rs  t o  e asily  a cce ss  b ook m ark ed  l o ca tio n s\nw hen eve r n ee d ed .\nT he a p pli c a tio n  i s  d eve lo p ed  u sin g J e tp ack  C om pose , p ro vid in g s u pp ort f o r b oth  l i g h t a n d d ark  m od es.	\nA ch ie ve m en ts\n-  D eve lo p ed  a  u se r-fr ie n dly  a p p i n te rfa ce  t h at r e su lt e d  i n  i n cre asin g u se r e n gagem en t.\n-  S u cce ss fu lly  i n tr o d u ce d  r o b u st s e cu rit y  m ea su re s, s e tt in g a  h ig h er s ta n dard  f o r d ata  p ro te ctio n .\n- E xce lle d  i n  m an ag in g a n d c o n tr ib u tin g t o  p ro je cts  i n  a  r e m ote  w ork  e n vir o n m en t, w hile  s e am le ss ly  o p tim iz in g\npro je ct e ffic ie n cy  t h ro u gh  e ffe ctiv e  c o lla b ora tio n  w it h  i n te rn al a n d i n te g ra tio n  t e am s.\nS tr e n gth\n-  P ro b le m  s o lv in g\nSu cce ss fu lly  a d dre ss e d  i n tr ic a te  t e ch n ic a l c h alle n ges t h ro u gh ou t t h e d eve lo p m en t o f t h e i n ve n to ry  c o n tr o l\nap pli c a tio n , l e ad in g t o  a  s ig n if ic a n t i m pro ve m en t i n  a p p p erfo rm an ce .\n- C olla b ora tio n\nC olla b ora te d  w it h  t e am  m em bers  t o  s u cc e ss fu lly  c o m ple te  p ro je cts  o n  t im e a n d w it h in  t im eli n e. A ctiv e ly  l i s te n ed  t o\nfe e d back  a n d i n co rp ora te d  c o n str u ctiv e  c rit ic is m  i n to  m y w ork .\n- A dap ta b ili t y\nP ro ve n  a b ili t y  t o  a d ap t q u ic k ly  t o  c h an gin g p rio rit ie s a n d t ig h t d ea d li n es, s u cce ss fu lly  c o m ple tin g a  h ig h pre ss u re\np ro je ct t h at r e q u ir e d  l e arn in g n ew  l i b ra ry  a n d c o lla b ora tin g w it h  t e am .\nSkills\nP ro gra m min g L an gu age s\n- K otli n  -  J a va  -  X M L	\nAndro id  D eve lo p m en t\n- A ndro id  S D K  -  J e tp ack  C om pose  -\nJ e tp ack  L ib ra rie s -  T hir d  P arty\nL ib ra rie s	\nD ata  P ers is te n ce\n- S h are d P re fe re n ce s -  E ncry p te d\nS h are d P re fe re n ce s -  D ata sto re  -\nP ro to D ata sto re  -  A ndro id  K ey S to re  -\nI n te rn al S to ra ge -  E xte rn al S to ra ge	\nD ata b ase s\n- R oom  -  R ealm  -  S Q Lit e  -  O bje ctB ox	\nD ep en den cy  I n je ctio n\n- H ilt  -  K oin	\nU I a n d D esig n  P att e rn s\n- T ra d it io n al D esig n  ( X M L) -  M od ern\nD ecla ra tiv e  ( J e tp ack  C om pose ) -\nD esig n  P att e rn s (  M VVM  ,  M VP )	\nN etw ork in g a n d A PIs\n-  R etr o fit  - O kH tt p  -  R estfu l A PI&#039;s  -\nW eb Sock et S erv ic e s	\nM ult it h re ad in g a n d C on cu rre n cy\n- C oro u tin es -  R X Ja va  -  L iv e D ata  -\nK otli n  F lo w s	\nM ed ia  a n d M ult im ed ia\n-  E xo p la ye r -  C am era  A PI&#039;s  (  G M S\nCam era  V is io n , C am era X ) -  I m age\nL oad in g ( G li d e, P ic a ss o , C oil)  -\nG oogle  C od e S ca n ners	\nD eve lo p m en t T ools  a n d V ers io n\nC on tr o l\n- G it H ub -  G ra d le  -  C I/ C D  (  J e n kin s,\nF astla n e )  -  G oogle  P la y C on so le  -\nA pp C en te r	\nD eb u ggin g T ools\n-  A ndro id  D eb u gger -  E m ula to rs  -\nA ndro id  P ro file r -  N etw ork\nIn sp ecto r -  C ra sh  L og -  F ir e b ase\nC ra sh ly tic s	\nA naly tic s\n- F ir e b ase  A naly tic s -  Z oh o A pptic s	\nT estin g\n- E sp re ss o  -  M ock it o  -  U I T estin g -\nU nit  T estin g	\nE ve n t H an dli n g a n d N av ig atio n\n- N av ig atio n  C on tr o lle r	\nA pp C om pon en ts\n-  B ro ad ca st R ece iv e rs  -  F C M\n(F ir e b ase  C lo u d M ess a g in g) -  W ork\nM an ager -  C on te n t P ro vid ers	\nS ecu rit y  T ools\n-  S on arQ ube -  Z A P -  M OBSF  -  S Q L\nM ap\nE du ca tio n\nA la g ap p a C hett ia r G ove rn m en t C olle ge  o f E n gin eerin g a n d T ech n olo g y\nE le ctr o n ic s a n d C om mun ic a tio n  E ngin eerin g\n8.5	\n2 017 -  2 021	\n	h tt p :// a cce te d u .i n /	\nLan gu age s\nE n gli s h\nP ro fe ss io n al\nT am il\nN ativ e', 2, 2, 1, 'Recruiter', 'Assigned', 'SL', 1, 'N', 14, '2024-07-17 03:14:02', NULL, '2024-07-20 03:14:02', 0, NULL, '2024-07-17 02:47:23', 0),
(372, 88, 1, 4, NULL, '1_88_17804139016697576b05be0_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', 'Assigned', 'SL', 1, 'N', 14, '2024-07-17 05:41:07', NULL, '2024-07-20 05:41:07', 0, NULL, '2024-07-17 05:32:27', 0);
INSERT INTO `resume` (`id`, `screeningId`, `adminId`, `candidateId`, `candidateDetailsId`, `resumeName`, `resumeOriginalName`, `resumeContent`, `isSkillScreened`, `isResumeScreened`, `isCron`, `isCandidate`, `isStatus`, `candidateShortlist`, `isInterviewAssign`, `enableInterviewReport`, `gptLanguageId`, `interviewAssignDate`, `psychoAssignDate`, `interviewValidity`, `isPsychoAssign`, `psychoValidity`, `created`, `createdBy`) VALUES
(373, 89, 73, 34, NULL, '73_89_17437761646697641053c39_Asmiya_Begum_N-Developer-Connected_Vehicle.pdf', 'Asmiya Begum N-Developer-Connected Vehicle.pdf', 'Asm iy a  B eg u m  N\nA ndro id  D eve lo p er\n	C hen nai		+ 91 9 003606100		asm iy a b eg u m .n m r@ gm ail.c o m	\nasm iy a -b eg u m\nasm iy a -b eg u m	\nE xp erie n ce d  A ndro id  D eve lo p er w it h  3 .3  y e ars  o f e x p ertis e  i n  b u ild in g h ig h -q u ali t y  a p pli c a tio n s t h ro u gh  c le an\nco d e a n d b est p ra ctic e s. P ro fic ie n t i n  u sin g d iv e rs e  l i b ra rie s a n d f r a m ew ork s t o  a d dre ss  r e al- w orld  c h alle n ges.\nD ed ic a te d  t o  m ain ta in in g s tr u ctu re d  c o d e o rg a n iz a tio n  a n d c o n sis te n tly  i m pro vin g c o d e q u ali t y . A ctiv e ly  s e ek in g a\nn ew  r o le  t o  e x p an d k n ow le d ge o f e m erg in g t e ch n olo gie s a n d c o n tr ib u te  t o  s o lv in g u se r c h alle n ges.\nW ORK  E X PER IE N CE\nH TC G lo b al S erv ic e s\nM ob ile  A ppli c a tio n  D eve lo p er	\nS ep  2 023 -  P re se n t	\nChen nai	\n	h tt p s:// w ww.h tc in c.c o m /	\nHTC  G lo b al S erv ic e s p ro vid es I T  a n d B usin ess  P ro ce ss  S erv ic e s a n d S olu tio n s t h at h elp  b u sin ess e s m ak e d ig it a l\nch an ge h ap p en .	\nColla b ora te d  o n  f e atu re  i m ple m en ta tio n  f o r t h e H orm an n p ro je ct.\nW ork ed  f o r t h e P en sk e c li e n t o n  i m ple m en tin g s u pply  c h ain  m an agem en t f e atu re s, i n clu din g o rd er t r a ck in g\nan d w atc h li s t f u n ctio n ali t ie s.\nW ork ed  o n  t h e g o ogle  m ap s t o  t r a ck  t h e s h ip m en ts  i n  a p pli c a tio n .\nIm ple m en te d  M SA L i n  a n  A ndro id  a p p t o  f a cili t a te  s e cu re  u se r a u th en tic a tio n  v ia  A zu re  A D, h an dli n g t o k en\na cq u is it io n  a n d r e n ew al f o r a cce ss in g p ro te cte d  A PIs .	\nG ofr u gal T ech n olo gie s P vt L td\nA ndro id  D eve lo p er	\nF eb  2 021 -  J u n  2 023	\nC hen nai	\n	h tt p s:// w ww.g o fr u ga l.c o m /	\nGofr u ga l i s  a  s o ft w are  c o m pan y t h at p ro vid es r e ta il /  P O S s o lu tio n s f o r s m all a n d m ed iu m  s iz e d  b u sin ess e s a cro ss\nv a rio u s i n du str ie s.	\nD eve lo p ed  m ob ile  a p pli c a tio n  w it h  h ig h -p erfo rm an ce  b arc o d e a n d Q R c o d e s c a n nin g.\nE nab le d  o ffli n e c a p ab ili t y  a n d u tili z e d  a d va n ce d  a lg o rit h m s f o r e ffic ie n t c o m pu ta tio n .\nU pgra d ed  c a m era  s c a n nin g f r o m  G M S V is io n  t o  C am era X  f o r f a ste r b arc o d e d ete ctio n .\nExp erie n ce d  i n  A ndro id  f e atu re s l i k e R xJa va , M VVM , D ata  B in din g, B ro ad ca st R ece iv e rs , F C M , C on te n t\nPro vid ers , O kH tt p , R etr o fit ,N av ig atio n ,a n d K otli n  s p ecif ic  f e atu re s s u ch  a s C oro u tin es, K otli n  S eria li z a tio n .\nIn te g ra te d  w it h  t h e p rin te r s d k t o  s u pp ort t h e i n  a p p p rin tin g. U tili z e d  M VVM  a rc h it e ctu re  f o r m ob ile  a p p\ndeve lo p m en t a n d s e p ara te d  a p p d ata , U I, a n d a p p l o gic  f o r b ett e r c o d e o rg a n iz a tio n  a n d m ain ta in ab ili t y .\nIm ple m en te d  s h are d  v ie w  m od els  f o r i m pro ve d  s c a la b ili t y  a n d c o d e r e u sa b ili t y .\nE xp erie n ce d  w ork in g o n  i m age l o ad in g t a sk s u sin g G li d e,a n d C oil.\nE nhan ce d  m ob ile  a p p s e cu rit y  b y e n cry p tin g b oth  a p p a n d u se r d ata .\nP erfo rm ed  s e cu rit y  t e stin g i n  Z A P , M OBSF  , S Q L m ap .\nG ain ed  e x te n siv e  k n ow le d ge o f m ult it h re ad in g a n d m em ory  m an agem en t f o r o p tim iz e d  a p p p erfo rm an ce .\nA uto m ate d  r e le ase  b u ild  a n d d ep lo ym en t i n  p la ysto re  u sin g f a stla n e.	\nP ro je cts\nI n ve n to ry  C on tr o l\nM ob ile  P O S I n ve n to ry  C on tr o l A ppli c a tio n\n	h tt p s:// p la y.g o ogle .c o m /s to re /a p ps/d eta ils ?id =co m .g o fr u ga l.s to ck m an agem en t&amp; pli = 1\nG oS u re  i s  a n  i n ve n to ry  c o n tr o l a p pli c a tio n  t h at e n ab le s u se rs  t o  p erfo rm  a ll i n ve n to ry -r e la te d  o p era tio n s i n\nP O S. I t  c o n sis ts  o f f o u r m od u le s: s to ck  t a k in g, G RN  ( G ood s R ece ip t N ote ), s to ck  p ic k , a n d s to ck  r e fill . T hese\nm od u le s p ro vid e f u n ctio n ali t ie s f o r m an ag in g s to ck  c o u n ts , r e co rd in g i n co m in g g o od s, p ic k in g i t e m s f o r\nord ers , a n d r e p le n is h in g s to ck .\nIt  i s  a  s tr o n g a n d r e li a b le  a p pli c a tio n  t h at c a n  h an dle  a  l a rg e c u sto m er d ata b ase  w it h ou t s lo w in g d ow n o r\nca u sin g a n y p erfo rm an ce  i s s u es.\nIt  e ffic ie n tly  m an ages e x te n siv e  c u sto m er d ata  w hile  m ain ta in in g h ig h  p erfo rm an ce  l e ve ls .\nIt  i s  a  u se r-fr ie n dly  a p pli c a tio n  t h at w ork s o n  b oth  m ob ile  d evic e s a n d P D A  d evic e s.\nIt  a llo w s u se rs  t o  s c a n  b arc o d es u sin g e it h er t h e d evic e &#039;s  b u ilt - in  b arc o d e s c a n ner o r t h e c a m era . T his  m ak es i t\ne asy  t o  c a p tu re  i n fo rm atio n  a n d m an age i n ve n to ry  e ffe ctiv e ly .\nIt  k eep s d ata  s a fe  a n d s e cu re  i n  b oth  o ff li n e a n d o n li n e m od es, p re ve n tin g a n y l o ss  o f i n fo rm atio n .\nIt  i s  a  n ativ e  A ndro id  a p pli c a tio n  u sin g K otli n , t a rg etin g A ndro id  d evic e s	\nP ric e  C heck er ( K IO SK )\nPric e  a n d L oya lt y  P oin ts  C heck in g A ppli c a tio n\n	h tt p s:// p la y.g o ogle .c o m /s to re /a p ps/d eta ils ?id =co m .g o fr u ga l.g o ch eck .r e le a se\nG oC heck  i s  a  p ric e  t a g  c h eck in g a p pli c a tio n  d esig n ed  t o  b e p la ce d  o n  t h e r a ck s i n  r e ta il s h op s.\nIt  e q u ip p ed  w it h  a  b arc o d e s c a n ner. W hen  a  b arc o d e i s  s c a n ned , i t  d is p la ys t h e d eta ils  o f a n y o ffe rs  a va ila b le\na n d t h e c o rre sp on din g l o ya lt y  p oin ts  f o r t h e c u sto m er.\nI t  s u pp orts  b oth  b arc o d e s c a n nin g a n d c a m era  s c a n nin g f u n ctio n ali t ie s. U se rs  c a n  c h oose  t o  s c a n  b arc o d es\nu sin g a  b arc o d e s c a n ner o r u tili z e  t h e d evic e &#039;s  c a m era  t o  c a p tu re  a n d p ro ce ss  b arc o d e i n fo rm atio n  w it h in  t h e\nap pli c a tio n . T his  p ro vid es f le x ib ili t y  i n  s c a n nin g m eth od s f o r e ffic ie n t a n d c o n ve n ie n t u se .\nIt  i s  a  n ativ e  A ndro id  a p pli c a tio n  u sin g K otli n , t a rg etin g A ndro id  d evic e s.	\nH orm an n S erv ic e  S u pp ort A pp\nD oor I n sta lla tio n  S erv ic e  S u pp ort A ppli c a tio n\n	h tt p s:// p la y.g o ogle .c o m /s to re /a p ps/d eta ils ?id =co m .h orm an n .s e rv ic e su pp orta p pli c a tio n &amp; hl= en &amp; gl= U S\nThe H orm an n s e rv ic e  s u pp ort a p pli c a tio n  i s  d esig n ed  t o  a ss is t i n sta lle rs  a n d s e rv ic e  e n gin eers  b y p ro vid in g\nhelp fu l i n sta lla tio n  a n d t r o u ble sh ootin g i n fo rm atio n .\nIt  i n clu des s e arc h ab le  f a u lt  c o d es, p ara m ete r c o d es, q u ic k  s ta rt t ip s, c o m mon  i s s u es, a n d s c h em atic s.\nIt  f e atu re s m od u le s t o  d is p la y c ir c u it  i m ages, d oor i n sta lla tio n  i n str u ctio n s, a n d t r o u ble sh ootin g g u id es w it h in\nt h e a p p i n te rfa ce .\nA  m od u le  a llo w in g t h e p la yb ack  o f i n str u ctio n al v id eo s d ir e ctly  f r o m  Y ou T ube U RLs w it h in  t h e a p pli c a tio n .	\nSu pply  C hain  I n sig h t\nO rd ers  t r a ck in g a p pli c a tio n  f o r s u ppli e r\n	h tt p s:// w ww.p en sk e.c o m /\nSu pply  C hain  I n sig h t i s  a n  a p pli c a tio n  t h at a llo w s u se rs  t o  t r a ck  l o ad s, o rd ers , v ie w  d eta ile d  o rd er i n fo rm atio n\nalo n g w it h  t im eli n es.\nIt  f e atu re s a n  i n fo rm ativ e  d ash board  w here  u se rs  c a n  v ie w  c o m pan y-s p ecif ic  i n sig h ts  o n  l o ad s, o rd ers ,\nw atc h li s ts , a n d l a te  o rd ers .\nIt  i s  i n te g ra te d  w it h  G oogle  M ap s t o  t r a ck  o rd ers  i n  r e al- tim e.\nT he a p p&#039;s  n etw ork  c a lls  a re  s e cu re d  u sin g t h e M ic ro so ft  A uth en tic a tio n  L ib ra ry  ( M SA L), w hic h  p erio d ic a lly\nr e fr e sh es t o k en s t o  p re ve n t v u ln era b ili t ie s.	\nP ers o n al P ro je cts\nS tr e am Vers e\nM ovie  S tr e am in g A ppli c a tio n\n	h tt p s:// g it h ub.c o m /A sm iy a B eg u m /S tr e am Vers e\nS tr e am Vers e  i s  a  m ovie  s tr e am in g p la tfo rm  t h at h as b een  d eve lo p ed  u tili z in g t h e e x o p la ye r f r a m ew ork .\nIt  f e atu re s a  u se r-fr ie n dly  h om e s c re en  w here  u se rs  c a n  e x p lo re  a  c a ro u se l s h ow ca sin g t h e l a te st a n d m ost\np op u la r m ovie s, a s w ell a s b ro w se  m ovie s c a te g o riz e d  a cco rd in g t o  d if fe re n t g en re s.\nIt  f e atu re s a  d ed ic a te d  v id eo  s tr e am in g i n te rfa ce  b u ilt  o n  t h e p ow erfu l e x o p la ye r f r a m ew ork . T his  i n te rfa ce\nb oasts  a  c u sto m  p la ye r l a yo u t t h at g re atly  e n han ce s t h e u se r e x p erie n ce . U se rs  c a n  e asily  a d ju st m ed ia  v o lu m e,\nsc re en  b rig h tn ess, s e ek  f o rw ard  o r b ack w ard  i n  t h e v id eo, c h an ge t h e s c re en  o rie n ta tio n , a n d e ve n  l o ck  t h e\nsc re en  t o  p re ve n t a cc id en ta l t o u ch es, e n su rin g a  s e am le ss  a n d e n jo ya b le  s tr e am in g e x p erie n ce .	\nS ketc h Flo w\nD ra w in g A ppli c a tio n\n	h tt p s:// g it h ub.c o m /A sm iy a B eg u m /S ketc h F lo w\nS ketc h F lo w  i s  a  m ob ile  a p p t h at l e ts  y o u  c re ate  a rt u sin g v a rio u s b ru sh es a n d c o lo rs . Y o u  c a n  c h an ge\nb ack gro u n ds, u n do, r e d o, a n d c le ar. I t  a llo w s s a v in g d ra ft s  f o r l a te r a n d e x p ortin g a rt t o  s p ecif ic  f o ld ers  a n d\nfo rm ats . Y ou  c a n  a ls o  s h are  y o u r c re atio n s w it h  o th er a p ps s e am le ss ly .	\nW eath erF ore ca st\nW eath er F ore ca stin g A ppli c a tio n\n	h tt p s:// g it h ub.c o m /A sm iy a B eg u m /W eath erF ore ca st\nIt &#039;s  a  w eath er f o re ca stin g a p pli c a tio n  t h at a llo w s u se rs  t o  s e arc h  f o r l o ca tio n s o r p in  t h em  o n  a  m ap  t o  r e tr ie ve\nth e w eath er s u m mary  f o r t h ose  a re as.\nIt  i n clu des a  f e atu re  f o r b ook m ark in g l o ca tio n s, a llo w in g u se rs  t o  e asily  a cce ss  b ook m ark ed  l o ca tio n s\nw hen eve r n ee d ed .\nT he a p pli c a tio n  i s  d eve lo p ed  u sin g J e tp ack  C om pose , p ro vid in g s u pp ort f o r b oth  l i g h t a n d d ark  m od es.	\nA ch ie ve m en ts\n-  D eve lo p ed  a  u se r-fr ie n dly  a p p i n te rfa ce  t h at r e su lt e d  i n  i n cre asin g u se r e n gagem en t.\n-  S u cce ss fu lly  i n tr o d u ce d  r o b u st s e cu rit y  m ea su re s, s e tt in g a  h ig h er s ta n dard  f o r d ata  p ro te ctio n .\n- E xce lle d  i n  m an ag in g a n d c o n tr ib u tin g t o  p ro je cts  i n  a  r e m ote  w ork  e n vir o n m en t, w hile  s e am le ss ly  o p tim iz in g\npro je ct e ffic ie n cy  t h ro u gh  e ffe ctiv e  c o lla b ora tio n  w it h  i n te rn al a n d i n te g ra tio n  t e am s.\nS tr e n gth\n-  P ro b le m  s o lv in g\nSu cce ss fu lly  a d dre ss e d  i n tr ic a te  t e ch n ic a l c h alle n ges t h ro u gh ou t t h e d eve lo p m en t o f t h e i n ve n to ry  c o n tr o l\nap pli c a tio n , l e ad in g t o  a  s ig n if ic a n t i m pro ve m en t i n  a p p p erfo rm an ce .\n- C olla b ora tio n\nC olla b ora te d  w it h  t e am  m em bers  t o  s u cc e ss fu lly  c o m ple te  p ro je cts  o n  t im e a n d w it h in  t im eli n e. A ctiv e ly  l i s te n ed  t o\nfe e d back  a n d i n co rp ora te d  c o n str u ctiv e  c rit ic is m  i n to  m y w ork .\n- A dap ta b ili t y\nP ro ve n  a b ili t y  t o  a d ap t q u ic k ly  t o  c h an gin g p rio rit ie s a n d t ig h t d ea d li n es, s u cce ss fu lly  c o m ple tin g a  h ig h pre ss u re\np ro je ct t h at r e q u ir e d  l e arn in g n ew  l i b ra ry  a n d c o lla b ora tin g w it h  t e am .\nSkills\nP ro gra m min g L an gu age s\n- K otli n  -  J a va  -  X M L	\nAndro id  D eve lo p m en t\n- A ndro id  S D K  -  J e tp ack  C om pose  -\nJ e tp ack  L ib ra rie s -  T hir d  P arty\nL ib ra rie s	\nD ata  P ers is te n ce\n- S h are d P re fe re n ce s -  E ncry p te d\nS h are d P re fe re n ce s -  D ata sto re  -\nP ro to D ata sto re  -  A ndro id  K ey S to re  -\nI n te rn al S to ra ge -  E xte rn al S to ra ge	\nD ata b ase s\n- R oom  -  R ealm  -  S Q Lit e  -  O bje ctB ox	\nD ep en den cy  I n je ctio n\n- H ilt  -  K oin	\nU I a n d D esig n  P att e rn s\n- T ra d it io n al D esig n  ( X M L) -  M od ern\nD ecla ra tiv e  ( J e tp ack  C om pose ) -\nD esig n  P att e rn s (  M VVM  ,  M VP )	\nN etw ork in g a n d A PIs\n-  R etr o fit  - O kH tt p  -  R estfu l A PI&#039;s  -\nW eb Sock et S erv ic e s	\nM ult it h re ad in g a n d C on cu rre n cy\n- C oro u tin es -  R X Ja va  -  L iv e D ata  -\nK otli n  F lo w s	\nM ed ia  a n d M ult im ed ia\n-  E xo p la ye r -  C am era  A PI&#039;s  (  G M S\nCam era  V is io n , C am era X ) -  I m age\nL oad in g ( G li d e, P ic a ss o , C oil)  -\nG oogle  C od e S ca n ners	\nD eve lo p m en t T ools  a n d V ers io n\nC on tr o l\n- G it H ub -  G ra d le  -  C I/ C D  (  J e n kin s,\nF astla n e )  -  G oogle  P la y C on so le  -\nA pp C en te r	\nD eb u ggin g T ools\n-  A ndro id  D eb u gger -  E m ula to rs  -\nA ndro id  P ro file r -  N etw ork\nIn sp ecto r -  C ra sh  L og -  F ir e b ase\nC ra sh ly tic s	\nA naly tic s\n- F ir e b ase  A naly tic s -  Z oh o A pptic s	\nT estin g\n- E sp re ss o  -  M ock it o  -  U I T estin g -\nU nit  T estin g	\nE ve n t H an dli n g a n d N av ig atio n\n- N av ig atio n  C on tr o lle r	\nA pp C om pon en ts\n-  B ro ad ca st R ece iv e rs  -  F C M\n(F ir e b ase  C lo u d M ess a g in g) -  W ork\nM an ager -  C on te n t P ro vid ers	\nS ecu rit y  T ools\n-  S on arQ ube -  Z A P -  M OBSF  -  S Q L\nM ap\nE du ca tio n\nA la g ap p a C hett ia r G ove rn m en t C olle ge  o f E n gin eerin g a n d T ech n olo g y\nE le ctr o n ic s a n d C om mun ic a tio n  E ngin eerin g\n8.5	\n2 017 -  2 021	\n	h tt p :// a cce te d u .i n /	\nLan gu age s\nE n gli s h\nP ro fe ss io n al\nT am il\nN ativ e', 2, 2, 1, 'Recruiter', 'Assigned', 'SL', 1, 'N', 14, '2024-07-17 11:06:38', NULL, '2024-07-20 11:06:38', 0, NULL, '2024-07-17 06:26:24', 0),
(374, 90, 73, NULL, NULL, '73_90_1488666637669766d93dd45_Bhushan_Bende_Developer_Connected_Platform_(1).pdf', 'Bhushan Bende_Developer_Connected Platform (1).pdf', 'Bhushan	Bende	\nSoftware	Engineer	\nRoles	:Senior	Software	Engineer	\nE-mail:	bhushanyahoo@gmail.com	\nMobile:	9405708908	\nProfessional	Synopsis:	\n	Experience	inPython	Developer	,Building	APIand	Data	Pipeline	,with	PRDomain	\n	Experience	onworking/building	Python-Fast	API	hosted	onLambda	connected	with	Elastic	Search	\n	Building	ETL	&amp;ELT	Data	Pipeline	inPython	with	AWS	Managed	Streaming	Application	Flink,	Self	Managed	Flink	and	AWS	Lambda	\n	5years	ofFunctional	and	Automation	Testing	experience	inInvestment	Banking	Domain	,Payment	Domain	and	Media	Monitoring.	\n	Keen	understanding	onCapital	Market	and	Money	Market.	\n	Well	versed	knowledge	ofPayments	system	and	Gateway	transaction	\n	Well	versed	inallphases	ofSoftware	Development	Life	Cycle	(SDLC)	and	Software	Testing	Life	Cycle	(STLC).	\n	Experience	inTesting	Web	Based	Application,	Windows	Based	Application	,Web-Service	and	Database	.	\n	Extensive	Knowledge	inwriting	Functional	and	Regression	Test-cases	,maintaining	and	modifying	test	cases.	\n	Proficient	inautomation	using	Selenium	Web-driver	with	Java	programming	language	.	\n	Extensive	knowledge	ofwriting	scripts	using	Element	locators	,Web-driver	methods	and	Java	Programming	.	\n	Generating	defect	report	and	interacting	with	developers	toresolve	the	defects.	\n	Having	good	exposure	todefect	management,	raising	defect/bugs.	\n	Having	good	time	management	towork	ondifferent	types	ofreleases	simultaneously	(BAU/OOC/Strategic).	\n	Has	rigorously	worked	onAPI	Testing	and	API	Test	Automation	with	JavaScript	-Mocha	Framework	\n	Extensive	knowledge	onvarious	testing	methodologies	like	UAT,	SIT,	Regression	testing,	Sanity	testing,	Smoke	testing,	and	\nFunctional	testing	.	\n	Experience	inusing	Test	Management	tool	HP-ALM,	JIRA	,Rally	.	\n	Great	exposure	toMS-OFFICE	suite	,Google	Suite	.	\n	Worked	extensively	onautomating	BFS	applications	from	enhancing	the	Automation	framework	inEclipse	using	Maven	tocommitting	\nthe	code	toBitBucket	/GITHUB	and	storing	test	artefacts	inJIRA	after	every	sprint	completion	.	\n	Have	working	experience	inCI/CD	model.	\n	Has	Good	Understanding	onEvent	Driven	System,	that	takes	data	asevent	process	it.	\n	Worked	onsetting	upKAFKA	and	KINESIS	for	Data	Stream	Processing	\n	Worked	onBuilding	Data	Pipeline	inPython	and	Deploying	itonAWS	Lambda	\n	Has	good	interpersonal,	communication	and	organizational	skill	with	ability	tointeract	effectively	with	colleagues	atalllevel.	\nTech	Stack:\nLanguages:	Python,	Core	Java,	SQL	,Javascript-NodeJS	\nOperating	System:	Windows,	Linux	,MacOS	\nTest	Management	Tool:	HP-ALM,	JIRA	,Rally	\nData	Base	Tools:	DBeaver,	MySQL,	Microsoft	SQL	Server	.,Google	Big	Query,	ElasticSearch	\nKnowledge	And	Worked	On:	API	Testing	with	POSTMAN,	API	Performance	Testing	with	JMeter	,ETL	Testing,	GCP,	AWS	EC2,	AWS	Lambda,	\nAWS	KINESIS,	Kafka,	Data	Streaming	Project,	API	Contract	Testing,	Docker	\nVersioning	Tool:	GIT	\nCertification:	GIT	(Udemy)	,AWS	API	GATEWAY(AWS),	GCP	KAFKA(GOOGLE),	Streaming	Pipeline	Using	Pyspark	and	Kakfa	\nAutomation	Framework	:BDD	-Cucumber,	TDD-	TestNG,	JavaScript	Mocha	\nAPI	Development	Framework	:Fast	API	Python	\nDeployment	Framework	:Zappa	\nAutomation	Tools:	Selenium	Web-driver,	Jenkins	,TestNG,	Cucumber	\nDeployment	Stack:	Kubernetes,	AWS	EKS	\nEmployment	Detail:	\nName	OfCompany	:Onclusive,	Mumbai	\nDesignation	:Senior	Software	Engineer	(Data	Engineer)	\nDuration	:19Oct	2022	ToCurrent	\nName	OfCompany	:TSYS	,Pune	\nDesignation	:Automation	Developer	\nDuration	:17May	2021	To	18Oct	2022	\nName	OfCompany	:Altimetrik,	Pune	\nDesignation	:Automation	Quality	Engineer	\nDuration	:18Jan	2021	To15May	2021	\nName	ofCompany	:Cognizant	Technology,	Pune	\nDesignation	:Test	Professional	\nDuration	:26June	2018	TO	15Jan	2021\n\nOnclusive	\nProject	1:	\nName	:Data	Platform	\nDesignation	:Senior	Software	Engineer	\nProject	Description	:Onclusive	isaMedia	Monitoring	Company.	Which,	monitors	the	Articles	,Content,	News,	Radio,	Youtube	and	also	TV	\nChannel.	Tofind	out	the	sentiment	for	the	particular	product	inmarket.	\nWhere	we	have	multiple	sources	who	pushes	Petabyte	ofdata	into	our	system	we	stream	that	into	MSK	Kafka	and	then	into	AWS	Kinesis	,using	\nData	Pipeline	asaconsumer	we	fetch	itand	process	ittoElastic	Search.(Elastic	stack)	\nAfterwards	this	used	for	sentiment	analysis	ofmarket	and	further,	using	API	this	Data	isfetch	and	given	toDown-Stream	Application	for	ML/AI	\npipeline.\nRole/Responsibility:	\n	ToDevelop	API	that	connects	with	Elastic-Search	and	fetch	out	data	with	relevant	query	that	we	build	run	time	.	\n	We	dohave	lots	ofAPI	that	exports	the	for	articles	based	onuser-query,	Iworked	onDeveloping	and	maintaining	API	\n	Todevelop	Data	Pipeline	Fetching	data	from	Apache	Kafka	and	AWS	Kinesis	then	transforming	and	Pushing	ittoStorage.(with	hosted	\nservice	onAWS	Lambda)	\n	Interm	tomodernize	these	pipeline	and	improving	the	performance	we	have	shifted	toApache	Flink	and	Apache	Beam	Pipeline	\no	Where	itfetch	data	from	Kafka,	using	UDF	we	modify	and	transform	this	data	and	push	itback	toElastic	Sink.	\no	Elastic	Sink	isself	managed	service	that	push	data	toElastic	Search	\n	Responsible	for	developing	and	deploying	the	API-P	oller	onAWS	ECS	tofetch	data	from	various	API	sources,	transform	it,and	store	it	\ninto	S3before	pushing	ittoKinesis	for	further	processing.	\nOther	Responsibilites	:	\n	Taking	part	inDesigning	Data	Pipeline	\n	Modernizing	Data	Pipelines	\no	Earlier	we	were	using	AWS	Kinesis	for	our	Data	Streaming,	now	we	have	designed	the	pipeline	touse	Kafka	which	has	good	\nRetention	period	and	also	tomaintain	the	AWS	Cost	itwill	becheaper	than	Kinesis.	\n	Adding	Layer	for	Open-Telemetry	intoServerless	AWS	Lambda	tocapture	telemetry	data	for	Failure	Analysis	\n	Deploying	StateFullset	ElasticSearch	InKubernetes	\n	Streaming	Data	Processing	On	Apache	Beam	Pipeline	\nProject	2:	\nName	:Data	Platform	\nDesignation	:Automation	Developer	\nProject	Description	:Onclusive	isaMedia	Monitoring	Company.	Which,	monitors	the	Articles	,Content,	News,	Radio,	Youtube	and	also	TV	\nChannel.	Tofind	out	the	sentiment	for	the	particular	product	inmarket.	\nWhere	we	have	multiple	sources	who	pushes	Petabyte	ofdata	into	our	system	we	stream	that	into	MSK	Kafka	and	then	into	AWS	Kinesis	,using	\nBroadcast	pipeline	asaconsumer	we	fetch	itand	process	ittoElasticSearch.	\nAfterwards	this	used	for	sentiment	analysis	ofmarket	and	further,	using	API	this	Data	isfetch	and	given	toDown-Stream	Application	for	ML/AI	\npipeline.\nRole/Responsibility:	Worked	asaAutomation	Architect	\n	ToDevelop	API	Automation	Framework	based	onNodeJS-JavaScript.	\n	Inclusion	ofBDD	inNode-JS	Framework.	\n	Maintaining	Automation	Framework	asaQA	Engineer	for	allthe	In-scope	API	\n	Completing	Testing	using	Manual	Testcases	and	Automation	\nOther	Responsibilites	:	\n	Taking	part	inDesigning	Data	Pipeline	\n	Modernizing	Data	Pipelines	\no	Earlier	we	were	using	AWS	Kinesis	for	our	Data	Streaming,	now	we	have	designed	the	pipeline	touse	Kafka	which	has	good	\nRetention	period	and	also	tomaintain	the	AWS	Cost	itwill	becheaper	than	Kinesis.	\n	Adding	Layer	for	Open-Telemetry	intoServerless	AWS	Lambda	tocapture	telemetry	data	for	Failure	Analysis\n\nTSYS	:Project	Worked	On	\nProject	1:	\nName	:UCP	-Global	Payments	\nDesignation	:Automation	Developer	\nProject	Description	:	\nAsaglobal	payments	we	wants	our	Merchants	has	full	capabilities	toselect	their	transaction	gateway	asper	their	own	\nconvenience	sothat	they	can	decide	their	security	level	and	transaction	changes	asper	area	they	are	serving	.Asaresult	we	have	created	aGlobal	\nPlatform	when	Global	Payment	will	board	Merchants	onUnified	Platform	(Unified	Commerce	Platform)	that	itwill	gives	right	toMerchants	toselect	\ngateway	without	any	code	changes.	\nHere	we	asaGlobal	Payments	will	take	care	ofinternal	transformation	and	Merchant	just	need	toplug	out	APIs	and	start	\nplaying	the	business	without	worrying	about	their	internal	transaction	transformation.	\nProject	2:	\nName	:Propay	Enterprise	Integration	\nDesignation	:Automation	Developer	\nProject	Description	:	\nAsTSYS,	AGlobal	Payments	Company,	we	act	asamediator	between	payment	gateways,	platform	and	Merchant.	\nMindBody	asaclient	comes	toGlobal	Payments	with	ask	that	they	want	tomigrate	their	allMerchant	toPROPAY	platform.	We	GPAPI	handles	their	\nTransaction,	Merchant	Boarding	Requirement	and	other	POS	devices	requirement	within	Single	Request.	\nArchitecture	works	like	take	abase	request	from	Merchant(Mindbody	Merchant)	segregate	and	convert	that	request	into	required	request	form	\nDownstream	I.ePROPAY,	TransIT,	SoundPayment,	PAX	Portal,	Express.	Receive	the	response	and	send	ittomerchant.	\nAsnumber	ofFinancial	entities	comes	into	picture	with	this	project,	ithas	avery	huge	scope.	Itincludes	payment	processing	and	merchant	\nprocessing.\nRole/Responsibility:	\n	Asbeing	aintegral	part	ofEnterprise	Integration	Team	my	responsibilities	were	related	togather	and	understand	the	latest	\nchanges/requirements	for	the	Gateway	Release	.	\n	Write	functional	and	regression	test	cases.	Used	POSTMAN	for	API	Testing	\n	Execute	manually	functional	and	regression	pack,	manage	test	cases	inRally	\n	Raise	defect	and	communicate	with	developers	toresolve	it.	\n	Reporting	Bugs,	verifying	logs,	verifying	server-side	services,	verifying	data,	generating	SQL	scripts	for	Database	changes.	\n	Verify	other	dependent	systems	are	receiving	proper	transaction	message	and	help	them	for	payments	booking	scenarios.	\n	Create	and	Execute	Automat	ion	Test	Scripts,	inNodeJS	based	framework	inJavaScript	.	\n	Verify	API-Integration	working	asexpected	\n	API	Performance	testing	with	JMete	r	\n	Generating	Sign-off	report	with	notifying	that	everything	isworking	fine	with	allnew	changes,	sothat	allnew	requirements	should	be	\nlive	inproduction	inupcoming	bi-weekly	release.	\n	Handling	multiple	developers	overseas.	\n	Communicating	with	Dev-ops	team	tocheck	new	build-changes,	DB-changes,	services	side	changes.	\n	Experience	inworking	with	Agile	and	CI/CD	testing	Models	.	\nAltimetrik	:Projet	Worked	On	:	\nProject	:	\nName	:CitiBank	-High	Value	Payments	\nDesignation	:Quality	Engineer	\nProject	Description	:	\nFew	High	Valued	Customers	are	tied	up	with	CitiBank,	they	transact	huge	amount	ofmoney	per	Business	Day.	We	have	\ncreated	DashBoards	tokeep	atrack	ontheir	transactions	and	check	and	observe	what	isthe	status	for	that	payment	and	transactions,	Inthe	form	\nonGraphs	and	Tabular	Data	we	are	displaying	data	.	\nRoles/Responsibility	:	\n	Write	Test	Cases	For	various	Dash-Board	showing	different	Types	ofData	Analysis	for	Payments.	\n	Analyse	Requirement	From	JIRA/BRD/FRD	\n	DB	Testing	with	high	number	ofHigh	Valued	Payment	with	Different	Types	OfMOP	(Mode	OfPayments)	\n	UITesting	-Verify	Data	Calculation	and	computation	for	the	Data	from	DB	iscorrect.	\n	Functional	And	Regression	Testing.	\n	Create	UIAutomation	Framework	Based	onJava	Selenium	BDD	-Cucumber.\n\nCognizant	:Project	Worked	On:	\nProject	1:	\nName	:Global	Markets	(Global	Securities	Lending)-	Trade	Execution	and	Management	(Short	&ndash;Selling)	\nClient:	Credit	Suisse	\nProject	Type	:Functional	And	Automation	Testing	\nDuration:	24Sept	2018	toJan	2021	\nProject	Description:	\nCredit	Suisse	uses	anapplication	toBook	trades	for	Short	Selling.	Where	Borrow,	Loan	and	Collateral	Trades	were	booked	\nevery	day,	this	isavery	heavy	application	asitisused	bynumber	ofusers	allover	the	Globe.	\nRole/Responsibility:	\n	Togather	and	understand	the	latest	changes/requirements	for	the	release	from	Business	Requirement	Documents.	\n	Write	functional	and	regression	test	cases.	\n	Execute	manually	functional	and	regression	pack,	manage	test	cases	inQuality	Centre	-HP	ALM	\n	Raise	defect	and	communicate	with	developers	toresolve	it.	\n	Reporting	Bugs,	verifying	logs,	verifying	server-side	services,	verifying	data,	generating	SQL	scripts	for	Database	changes.	\n	Verify	other	dependent	systems	are	receiving	proper	trade	message	and	help	them	for	trade	booking	scenarios.	\n	Create	and	Execute	Automated	Test	Scripts,	and	verifying	results.	\n	Verify	API-Integration	working	asexpected	\n	API	Performance	testing	with	JMete	r	\n	Generating	Sign-off	report	with	notifying	that	everything	isworking	fine	with	allnew	changes,	sothat	allnew	requirements	should	be	\nlive	inproduction	inupcoming	bi-weekly	release.	\n	Taken	initiative	toenhance	automation	ofWeb	Based	Application	using	Selenium	WebDriver	with	IDE	Eclipse	.		Handling	multiple	developers	overseas.	\n	Communicating	with	Dev-ops	team	tocheck	new	build-changes,	DB-changes,	services	side	changes.	\n	Experience	inworking	with	Agile	and	CI/CD	testing	Models	.	\nProject	2:	\nName	:Security	Financing	Transaction	Regulation	\nClient:	Credit	Suisse	\nProject	Type	:Functional	Testing	\nDuration:	Jan	2020	toJan	2021	\nProject	Description:	\nThis	isaglobal	change	where	every	Investment	Bank,	needs	toreport	their	allEurope	based	transaction,	tothe	certain	\nReporting	Entity.	\nRole/Responsibility:	\n	Togather	and	understand	the	change	from	Business	Requirement	Documents.	\n	Write	functional	and	regression	test	cases.	\n	Execute	manually	functional	and	regression	pack.	\n	Raise	defect	and	communicate	with	developers	toresolve	it.	\n	Verifying	logs,	verifying	server-side	services,	verifying	data,	generating	SQL	scripts	for	Database	testing.	\n	Verify	other	dependent	systems	are	receiving	proper	trade	message	and	help	them	for	trade	booking	scenarios.	\nProject	3:	\nName:	Fixed	Income	Securities	\nClient:	Credit	Suisse	\nProject	Type:	Functional	Testing/API	Testing	\nDuration:	March	2020	toMay	2020	\nProject	Description:	\nFixed	Income	securities	tobeimplemented	for	certain	Client/Counterparties	with	specified	entity	directions,	\nFor	that	combination	ofClient	and	Fixed	Income	Securities	system	calculating	rate	and	fetching	them	from	API	end	point.\n\nRole/Responsibility:	\n	Togather	and	understand	the	changes.	\n	Verify	API-Integration	working	asexpected.	\n	Write	and	execute	manual	and	regression	pack.	\n	Verify	logs,	DB	testing	reporting	defect	\n	Performance	testing	for	API	with	JMeter	.	\nAcademic	Details:	\nSr.No	Qualification	University/Board	Passing	Year	Percentage	\n1.	Executive	PDGM	MIT	SDE	2022	Grade	A	\n2.	Bachelor	inComputer	Application	Amravati	University	2017	68%	\n3.	HSC	Maharashtra	State	Board	2014	62.46%	\n4.	SSC	Maharashtra	State	Board	2012	82.55%	\nOther	Qualification	Details:	\nSerialNo.	Qualification	University	/Board	Passing	Year	Percentage	\n1.	Eng-Typing	30	Maharashtra	State	Council	ofExamination,	Pune	Dec-2012	65%	\n2.	Eng-Typing	40	Maharashtra	State	Council	ofExamination,	Pune	Dec-2012	51%	\n3.	MS-CIT	Maharashtra	State	Board	OfTechnical	Education,Mumbai	July-2010	92%	\nSelf-Learning	Project:\n	Project	1:Text	files	reader.	(Text	tospeech).	(Using	python	and	GTTS	library)		Project	2:QR	code	generator	(Using	Python)		Project	3:Speech	totext	(Using	Python	and	Google	Speech	Recognition	Library)	\nAchievement:	\n	Awarded	as&ldquo;Pillar	OfThe	Month	&ldquo;(Cognizant	May	2019)		Best	&ldquo;Student	ofYear	&rdquo;(CMCS	2017)	\nPersonal	Details:	\nName:	Bhushan	Ashokrao	Bende	Dob:	18/01/1996	Permanent	Address:	Old	Gilani	Nagar,	Yavatmal	445001	Maharashtra	Current	Address:	Venkat-Padmavati	PGbehind	Persistent,	Hinjewadi	,411057	Pune	Strength:	Good	Communication,	Quick	learner	Hobby:	Cooking,	Gardening	Languages	known:	English,	Marathi,	Hindi	\nMobile	+91	9405708908	\nEmail:	Primary:	bhushanyahoo@gmail.com	\nDeclaration:	Ihereby	declare	that	the	above	information	istrue	tothe	best	ofmy	knowledge	and	allnecessary	documents	will	beprovided	as&amp;	\nwhen	required.	\nSignature:	Bhushan	Ashokrao	Bende	\nDate:	Place:	Pune', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', NULL, NULL, NULL, NULL, 0, NULL, '2024-07-17 06:38:17', 0),
(375, 91, 73, 42, NULL, '73_91_177430066066976972d99cf_Ajay_Chaudhari_-_HMI_Developer.pdf', 'Ajay Chaudhari - HMI Developer.pdf', '/  	\nA JAY  C H AU DH ARI\nSoft w are  D eve lo p er	\narc h au d hari1 4 0 2@ gm ail. c o m	h ttp s:/ /w ww.lin ke d in .c o m /in /a ja y -\nc h au d hari- 0 15 6 ba16 9/	\nK an ag aw a, J a p an	\nS U M MARY\nExp erie n ce d  S oft w are  D eve lo p er w it h  o ve r 4 .3  y e ars  s p ecia liz in g  in  A nd ro id -\nbase d  A uto m otiv e  In fo ta in m en t s y ste m s 	 \n 	\nP ostg re S Q L,  a n d  O doo.  I  a m  e ag er t o  c o lla b ora te  o n a d va n cin g  c u ttin g -e d ge	 	\nte ch no lo g y a n d  d eliv e rin g  e xc e p tio nal  r e su lt s .\nE X PER IE N CE\nOnsit e  D eve lo p m en t E ngin eer\nTata  C on su lt a n cy S erv ic e s L td	\n0 5/2 0 24	&nbsp;	K an ag aw a,  J a p an	\nA ssig ned  F e atu re :  R ad io  	 	\nR ad io ,  P od ca st)\nO nsit e  S PO C f o r R ad io  f e atu re ,  C lie n t c o m mun ic a tio n,  M an ag e S O P /  Q LU	 	\n/ M ain lin e d eliv e rie s f o r N is sa n  V eh ic le s,  B ug  t r ia g in g  a n d  f ix in g\nW ork in g  w it h  c ro ss-fu n ctio nal  t e am s s u ch  a s X peri,   L G ,  G oog le ,  B osc h ,	 	\netc .\nT e ch S ta ck:  A nd ro id ,  K otlin ,  J a va ,  A O SP,  A ASP	\nS yste m s E ngin eer\nTata  C on su lt a n cy S erv ic e s L td	\n0 1/2 0 22 	&nbsp;	G an d hin ag ar,  In d ia	\nN is sa n  IV I  f e atu re s:  T e le m atic s 	 	\nC onnm an  \nF i,   a n d  H ots p ot).\nH M I  d eve lo p m en t t h at w ork s w it h  A O SP a n d  H AL p ro vid ed  b y L G  a n d	 	\nB osc h ,  f e atu rin g  1 0 0\nB uilt  p yth o n s c rip t t h at r e d uce d  S ST R g en era tio n t im e b y 8 0 %\nTe ch S ta ck:  A nd ro id ,  K otlin ,  J a va	\nJ r. A pplic atio n  E ngin eer\nTin yE R P P vt. L td	\n1 0 /2 0 20  	&nbsp;	A hm ed ab ad ,  In d ia	\nO doo:  E R P B usin ess S uit e  o f o p en -s o urc e  b usin ess a p ps c o ve rin g  C RM ,	 	\neC om merc e ,  A cco un tin g ,  In ve n to ry ,  P O S e tc\nD eve lo p m en t o f c u sto m  m od ule s a s p er c lie n ts &#039;  n eed s.  A ddre sse d  m ain ly	 	\ng en eric  &amp;  s p ecif ic  is su e s d urin g  d ata b ase  u p gra d es.  1  g en eric  f ix  c a n	 	\nre so lv e  r o ug hly  1 0  C lie n ts  d ata b ase  u p gra d e is su e s\nTe ch S ta ck:  P yth o n,  P ostg re sq l,   J S ,  U bun tu	\nP yth on /O doo D eve lo p er\nBro w se ln fo  P vt. L td	\n0 3 /2 0 20  	&nbsp;	A hm ed ab ad ,  In d ia	\nD eve lo p ed  C usto m  L ib ra ry  m an ag em en t O doo A pp,  P ro d uct Q ualit y	 	\nA ssu ra n ce  A pp u sin g  g en eric  m od ule s\nC ontr ib ute d  t o  e xis tin g  O doo A pps lik e  B atc h  P ay m en t d urin g  in vo ic in g\nTe ch S ta ck:  P yth o n,  J S ,  O doo	\nE D U CATIO N\nBach elo r o f E ngin eerin g\nSA L E n g in eerin g  A nd  T e ch nic al I n stit u te , G TU	\n04 /2 0 17  	&nbsp;	A hm ed ab ad ,  In d ia	\nGP A	\n8.2 7	10	\nC om pute r E ng in eerin g  M ajo r	\nS KIL LS\nTe ch S ta ck\nA nd ro id	J av a	K otlin	P yth on	\nO doo	P ostg re sq l	M atp lo tL ib	\nN um py	O pen C V	Pan d as	S eab orn	\nS kle arn	G it	\nT e ch nic al  E xp ert is e\nA uto m otiv e  I n fo ta in m en t f o r C CS\nER P S oft w are  	M ac h in e L e arn in g	\nP R O JEC TS\nAuto m atic  A tte n dan ce  S yste m	\nhttp s:/ /g it h ub .c o m /A jja rv is /A uto m atic _A tte n d an ce _S\ny ste m	\nF ace  R eco g nit io n-b ase d  A uto m atic  A tte n d an ce	 	\nS yste m  u sin g  C CTV  f o r r e al- tim e s tu d en t	 	\natte n d an ce .	\nTe ch S ta ck:  P yth o n,  T kin te r,  X lr d ,  X ls x w rit e r,	 	\nO pen C v	\nIn diM on ey : A n E xp en se  T ra cke r A pp	\nhttp s:/ /g it h ub .c o m /A jja rv is /In d iM oney	\nA nd ro id  E xp en se  T ra cke r A pp f o r e ffic ie n tly	 	\nm onit o rin g  o f e xp en se  a n d  in co m e w it h  le ss e ffo rts	\nT e ch S ta ck:  A nd ro id ,  S Q Lit e ,  G oog le  M L k it	\nA C H IE V EM EN TS	\nPala d in  o f t h e I V IT  C ham pio n s\nRece iv e d  b eca u se  o f h ig h p erfo rm an ce  o n	 	\ncrit ic a l  p hase  o f t h e p ro je ct\nD ig it a l M ile sto n e a t T C S\nCle are d  c o d in g  c h alle n g es in  P yth o n a n d	 	\nd em onstr a te d  c o m pete n cie s in  A gile	 	\nm eth o d olo g y.\nIn nova to r M ile sto n e a t T C S\nCle are d  c o d in g  c h alle n g e o n M ach in e	 	\nLe arn in g	\nwww .enhancv .com	\n	\nPow er ed b y	\nE		q	\n\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;	\n&bull;\n&bull;\n&amp;\n\n', 2, 2, 1, 'Recruiter', 'Assigned', 'SL', 1, 'N', 14, '2024-07-18 14:32:36', NULL, '2024-07-21 14:32:36', 0, NULL, '2024-07-17 06:49:22', 0),
(376, 91, 73, 36, NULL, '73_91_135311370066976972d9bda_Arjun_V_Menon_-_HMI_Developer.pdf', 'Arjun V Menon - HMI Developer.pdf', '. \n. \n 	 	\nARJUN V MENON	 	\nSoftware Engineer 	 	\n +91 9744816460	  	\n\ncom	 	 	\n https://www.linkedin.co\nm/in/arjun	-menon	-	\n937159141/	 	 	\n 	\n 	\nAn  inspired  android  developer  dedicated  to  continuously  developing, \nimplementing,  and  adopting  new  technologies  to  maximize  development \nefficiency  and  produce  innovative  applications.  I  have  a  total  technical \nexperience of more than 4 years &amp; passionate to	wards solving problems. 	 	\n \n 	Skills	 	\n Native Android Development ( Java , Kotlin) 	 	 \n JSON, RESTful web services. 	 	 \n Retrofit, Volley, Coroutines. 	 	 \n SQL Lite, Room DB, MySql, Shared Preferences. 	 	 \n Markup language (XML). 	 	 \n Version Control (Git, Bitbuket, SVN, Gerrit). 	 	 \n Project Management (Jira, Jenkins, Polarion, Confluence). 	 	 \n AOSP 	 	 \n Android HMI 	 	 	 	\n 	\nWork History	 	\n Senior Software Enginner	 	\nTata Elxsi, Bangalore	 	\n Worked on Android Map application using Mapbox for automotive 	 	\n Worked on Telematics CV2X project, In Android Telematics Service \nApplication. 	 	\n Testing and Debugging on Hardware for Android Telematics. 	 	\n Worked on Android HMI for Launcher App. 	 	\n Skills: Jira 	- Confluence 	- Polarion 	- Gerrit 	- AOSP 	- BinderIPC 	- Android 	\nFramework 	- Java 	- Mqtt 	- AIDL 	 	\n Programmer Analyst	 	\nCognizant, Bangalore	 	\n Worked on Google Play Protect Project. 	 	\n Worked on android security and android reverse engineering. 	 	\n Worked on Identifying security threats and malware in Playstore. 	 	\n Worked Android Malware analysis. 	 	\n Skills: Jira 	- Android Studio 	- Reverse Engineering 	- Java 	- Kotlin 	 	\n 	\n2022	-11 	- Current	 	\n2021	-09 	- 2022	-11	 	\narjunvenumenon@gmail.\n\n. \n. 	\n Software Engineer	 	\nQuest Global, Trivandrum	 	\n Software development in Android Automotive HMI 	 	\n Worked on Phonebook team of HMI, Version control using SVN. 	 	\n Developed features for Phonebook and Contacts of HMI. 	 	\n Testing and debugging of Build in Hardware. 	 	\n Skills: Jira 	- Gerrit 	- AOSP 	- BinderIPC 	- Android Studio 	- AIDL 	 	\n Software Engineer	 	\nAutocon India Pvt. Ltd, Kochi	 	\n Developed new features for proprietary Android applications used on \nphones and tablets; worked with developers to develop toptier solutions \nfor restaurant and retail customers 	 	\n Uses Coroutines for long	-running tasks (database and network access) 	 	\n Maintaine	d long and short	-range deliverables with product 	\nmanagement team according to product roadmaps 	 	\n Created custom mobile applications using native technologies 	 	\n Database access through Room persistence library. 	 	\n Android Developer	 	\nTradeasy Technologies, Kannur	 	\n Created custom mobile applications for retail customers 	 	\n Documented architecture and implementation for internal and external \nconsumption 	 	\n Applied various techniques to locate bugs and errors in applications 	 	\n Designed and built sales applications for Android platform 	 	\n Provided dedicated support and timely issue resolution to clients \nfollowing successful app launch. 	 	 	\n 	\nEducation	 	\n B-tech: 	Electronics And Communication Engineering	 	\nKannur 	University 	- Kannur	 	\nPercentage: 63 	 	\n 12th: 	Science	 	\nChapparapadava HSS 	- Kannur	 	\nPercentage: 70% 	 	\n 10th Std	 	\nChapparapadava HSS 	- Kannur	 	\nPercentage: 85% 	 	 	\n 	\nAccomplishments	 	\n  Conducted Android App Development workshops in various colleges 	 	\n Participated in workshop on Internet of Things by Innovians Technologies 	 	\n Participated in Cannovation 2018 startup exhibition of Kannur University 	 	\n 	 	 	\n. 	\n2021	-04 	- 2021	-09	 	\n2020	-08 	- 2021	-04	 	\n2019	-03 	- 2020	-08	 	\n2014	-07 	- 2018	-05	 	\n2011	-06 	- 2013	-03	 	\n2010	-06 	- 2011	-03', 2, 2, 1, 'Recruiter', 'Assigned', 'SL', 1, 'N', 14, '2024-07-17 13:02:52', NULL, '2024-07-22 13:02:52', 0, NULL, '2024-07-17 06:49:22', 0),
(377, 91, 73, 40, NULL, '73_91_89661268866976972d9da4_Gowtham_Mohanraj_HMI_Developer_Resume_1_(1).pdf', 'Gowtham    Mohanraj HMI Developer Resume 1 (1).pdf', 'ED U C ATIO N\nG OW TH AM  SA SSIS TA N T M AN AG ER	 	C O NTA C T+91 6 383311446go w tth am s6 @ gm ail.c o m ch en naiS K IL LS	Pro je ct M an ag e m en t	 	\nT eam work\nT im e M an ag e m en t\nLe ad ers h ip\nE ffe ctiv e  C om mun ic a tio n\nC rit ic a l  T hin kin g	\nV ELA LA R C O LLE G E O F\nEN GIN EER IN G A N D T EC H NO LO GY\nEle ctr o nic s &amp;  C om mun ic a tio n -  7 5%2 010  -  2 01 32009PO NNU M ATR IC U LA TIO N H R S E C\nSC H O OL\nHig h er s e co nd ary  e d uca tio n -  8 5%W ORK  E X PER IE N CEPR O JE C TS	 	P R O FIL EDyn am ic   an d  in no vativ e   in fo ta in m en t  sy ste m  exp ert  w it h  o ve r  4  ye ars   o f\nexp erie n ce   in   deve lo pin g  an d   im ple m en tin g  cu ttin g-e d ge   in   au to m otiv e\nin d ustr y  a n d  in fo rm atio n s y ste m s.  O ve r a ll  1 0 y e ars  o f e xp erie n ce  in  S o ft w are\nin d ustr y .  P ro ve n  a b ili t y  to  le ad  c ro ss-fu n ctio nal  te am s  a n d  m an ag e  p ro je cts\nfr o m  co nce p t  to   co m ple tio n,  en su rin g  se am le ss  in te gra tio n  of  m ult im ed ia ,\nn av ig atio n,  an d   co nnectiv it y   fe atu re s.  Adep t  at  le ve ra g in g  ad van ce d\nte ch no lo gie s t o  e n han ce  u se r e xp erie n ce  a n d  d riv e  m ark e t c o m petit iv e n ess.\n2 023 -  P R ESE N TM on tr a  - T I c le an  m ob il it y  p riv ate  l im it e dA ssis ta n t m an ag er	 	\nP ro d uct d eve lo p m en t &amp;  R eq uir e m en ts  h an d lin g	  -  C en tr a l R &amp; D	The  cre atio n   an d   exe cu tio n   of  m an ual  te st  ca se s  fo r  all  m od ule s  an d\nap plic a tio n s o f v e h ic le  t e le m atic s.\nT he c re atio n  o f  v e h ic le  a le rts  a n d  in fo rm atio n  th ro u g h th e te le m atic s c lo u d\nfo r m ob il e  a p plic a tio n s a n d  O EM .\nFu n ctio n al  a n d  in te g ra tio n  te stin g  o f  a p plic a tio n  fe atu re s a t  b oth  th e te st\nb en ch  a n d  v e h ic le  l e ve ls  u sin g  a  C AN  A naly ze r.\nC usto m iz in g  th e te le m atic s d ash b oard  a n d  m an ag in g  it   a cco rd in g  to  re al-\nt im e f ie ld  i s su es a n d  s e rv ic e  r e q uir e m en ts .\nD eve lo p m en t  te stin g  o f  v e h ic le  fe atu re s s u ch  a s g eo fe n cin g ,  liv e  tr a ckin g ,\nan d  v e h ic le  a le rts  a n d  A nd ro id  d eve lo p m en t i n  i n fo ta in m en t s y ste m .\nTele m atic s p erfo rm an ce  a n aly sis  t h ro u g h v a rio u s c o m petit iv e  b en ch m ark in g .\nSu p port t h e v e n d or s e le ctio n  p ro ce ss a n d  m an ag e v e n d ors  t o  e n su re  t im ely\nd eliv e ry  a n d  t h e r e q uir e d  q ualit y .\nG ood  k n ow le d ge a n d  u n d ers ta n d in g  o f  E V  a rc h it e ctu re  w it h  m ult ip le  C AN\nnetw ork s i n  t h e v e h ic le .\nP re p ara tio n   of  8D  re p orts   in   co ord in atio n   w it h   pro d uctio n   an d   cro ss-\nfu n ctio n al t e am s t o  s o lv e  c rit ic a l q ualit y  i s su es.\nE xp ertis e  i n  p re p arin g  S co p e o f R eq uir e m en ts  d ocu m en ts .\nT eam  s iz e  :  2\nI n it ia tin g  a n d  im ple m en tin g  U D S p ro to co l  a cro ss  a ll  ve h ic le  d ow nstr e am\nE C Us, c o n sid erin g  a ll a sp ects  a n d  v e rtic e s.\nS u p portin g  t h e d eve lo p m en t o f a  s in g le  c lo u d  p la tfo rm  f o r v a rio u s t e le m atic s\nu n it s .\nA ctiv e ly  in vo lv e d  in  t h e im ple m en ta tio n  a n d  v a lid atio n  o f	  t e le m atic s f e atu re s	\nsu ch  a s :\n D eep  l o g ger -	  V erif ic a tio n  a n d  v a lid atio n  o f e ach  v e h ic le  d ata  p oin t.	1.\n D eep  u p d ate r -	  D eve lo p m en t o f U D S p ro to co l i n  a ll E C Us t o  s u p port	\nF ir m ware  O ve r-T he-A ir  	(F O TA	) u p d ate s.	\n2.\nD eep  c o m man d er -  D eve lo p m en t o f v e h ic le  I m m ob il iz a tio n  s y ste m s.	3.	\nT O OLS	 	CA N oe\nC A N an aly ze r\nB us M aste r\nP -C A N\nJT A G\n\nDoco m o I n te rto u ch  I n d ia  L td  ,  B an g alo re , I n d ia	 	IT  S u p port E n g in eer	M S O utlo ok c o n fig ura tio n , b acku p  ,  r e sto re  a n d  t r o u b le sh ootin g .\nM an ag e D om ain  e n vir o n m en t f o r t w o s it e s t h ro u g h r e m ote  s u p port.\nW ir e le ss n etw ork in g  i n  D om ain  e n vir o n m en t.\nA sse m blin g , h ard w are  u p  g ra d atio n  a n d  t r o u b le sh ootin g .\nPro vid in g  s u p port t o  i n sta llin g  O S f o r t h e u se r m ach in es a n d  s e rv e rs .	\n G em alt o  M id dle  E ast F Z  L LC , D ub ai, U .A .E	                              	2 016 - 2 020	 	 2013- 2 016	 	IS S/N etw ork  a n d  S u p port E n g in eer	R esp on sib le   fo r	   	LA N  an d  W AN  n etw ork   op era tio n s,  sy ste m  d is a ste r	\nre co ve ry ,  data b ase   an d   sy ste m  backu p ,  Pla ye d   ke y  ro le   in   backu p\nm an ag em en t o f I T  d ep artm en t.\nC IS C O   :  Rou te rs ,  Sw it c h es,  Serv e r,  wir e le ss  devic e s,  an d   Acce ss\nte ch nolo g ie s.\nS tr o n g  t r o u b le sh ootin g  s k il ls  o n  L A N , W AN  a n d  W ir e le ss t e ch nolo g ie s.\nM an ag ed  u se r a cco u n ts  w it h  ( A D ) A ctiv e  D ir e cto ry  f o r t h e u se rs  t o  p ro vid e\ncre atio n ,  d ele tio n ,  u se r p erm is sio n  a n d  m an ag ed  u se r s e cu rit y  w it h  g ro u p\np olic ie s\nG ood  e xp erie n ce  i n  i n sta llin g  a n d  m ain ta in in g  t h e v ir tu al w ork sta tio n s	\n        	( E 2C )\nH an d lin g  P K I a n d  V PN  b ase d  s e cu rit y  i s su es.  p erfo rm  t r o u b le sh ootin g  e n d -\nto -e n d  b etw een  t h e s it e s.  P ro vid in g  t r a in in g  fo r t h e u se rs  t o  c o n fig ure  t h e\nce rtif ic a te  a n d  s e cu re  d om ain  w it h  t w o f a cto r a u th en tic a tio n .\nP erfo rm in g   Reg is tr a tio n   an d   Auth orit y   dutie s  to   in clu d e  ce rtif ic a te\ne n ro lm en t a n d  r e vo ca tio n .\nM an ag ed  A cce ss C on tr o l  S yste m  to  m ain ta in  a ll  th e b ad ges o f  u se rs  a n d\nvis it o rs .  T o p ro vid e p erm is sio n s fo r  th e re co m men d ed  d ep ortm en t  a n d\nse cu re d  a re a.\nIn sta llin g  G em alt o  B om gar  a p plic a tio n  fo r  a ll  th e m ach in es in  p ro d uctio n\nare a.	\nK in g sto n  I n fo  s o lu tio n s,B an g alo re .	                                       	2 020 -	  2 023	            	\n        \n       	 T est E n g in eer	\n 	\nperfo rm in g  v a lid atio n  o n  i n fo ta in m en t f e atu re s i n  a ll p ossib le  c o n d it io n s.\nV alid atin g  d if fe re n t m od ule s l ik e  U SB ,F M ,H M I a n d  P hon e	 	\nP erfo rm in g  th e ra p id  v a lid atio n  te sts   fo r  a ll  te st  c o n d it io n s  a n d  in va lid\nc a se s	 	\nP re p arin g  s o ft w are  v a lid atio n  s ta tu s r e p ort .\nD eve lo p m en t a n d  v a lid atio n  o f i n te g ra te d  T ele m atic s a n d  C lu ste r.	\n 	\nI h ave  a ctiv e ly  in it ia te d  a n d  d eve lo p ed  F O TA  im ple m en ta tio n  in  3 W  ( L 5 M ,\nL5 N ),  T ra cto r,  S C V,  a n d  H CV.  S u cce ssfu lly ,  I  h ave  g iv e n  a  d em o w it h  t w o\nve rtic e s.	 	\nI p ro p ose d  F O TA  e n tr y -le ve l c o n d it io n s a n d  c h ecklis ts  b ase d  o n  i n d iv id ual\nE C U a n d  v e h ic le  b eh avio u r,  e n su rin g  n o im pact o n  t h e e n d  c u sto m er a n d\nm ain ta in in g  v e h ic le  p erfo rm an ce .	\nL A N G UAG ES	Engli s h	 	\nIE LT S w it h  b an d  6\nT am il	 	\nS TA C K H O LD ER S	Sib ro s ,  N esh  ,  C onnectm  ,\nP ric o l  ,  E le ctr o nik a ,  A W EV ,\nSo na C om sta r ,E xid e	 	\n      \nO TH ER  I N FO	Passp o rt n o  - K 2849988	 	\nH obbie s - S ke tc h in g &amp;\nG ard en in g	 	\nT han ks	 	G O W TH AM  S A KTH IV EL	,  C hen nai,  2 4 J u n e 2 024', 2, 2, 1, 'Recruiter', 'Assigned', NULL, 0, 'N', 14, '2024-07-18 09:14:48', NULL, '2024-07-21 09:14:48', 0, NULL, '2024-07-17 06:49:22', 0);
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(378, 91, 73, 33, NULL, '73_91_161939989266976972da127_HMI_Developer-Shailendra_Semwal.docx', 'HMI Developer-Shailendra Semwal.docx', '\r\nShailendra Semwal\r\n# 3047 Janapriya Havens\r\nYalanka, Bangalore-560065)\r\n✉E-mail Id  shailendarsemwal@gmail.com☎Contact No +91-8548074898\r\n  LinkedIn: https://www.linkedin.com/in/shailendrasemwalCareer Objective:\r\nTo work with maximum potential in a challenging and dynamic environment, with an opportunity of working with diverse group of people and enhancing my professional skills with learning and experience for career growth.\r\nExperience Summary:\r\nWith 8 years of experience in Android Application Development, Android Automotive, and AMS Engineering Application Support, I bring a wealth of expertise to my roles. I have working navigation systems for Scania trucks, kitchen management apps for restaurant chains, and provided critical support for engineering applications at Black &amp;amp; Veatch.\r\nTechnical Skills:\r\nTools &ndash; Git SVN, ADB tools, QFIL Tools, AOSP\r\nLanguage &ndash;  JAVA, Kotlin, Java(Android SDK)\r\nDatabase &ndash; SQLite, MySQL.\r\nTechnology &ndash; Android,AOSPOperating System &ndash; Windows, Mac,LinexIDE &ndash;Android Studio, Eclipse,Microsoft PowerBITicketing Tools- ServiceNow, Jira, Conference, Figma\r\nAreas Of Expertise:\r\n&bull;    Familiar with the Android SDK, Eclipse, Google services and APIs.\r\n&bull;    Knowledge of SQLite, MySQL or Oracle database management system.\r\n&bull;    Proficient in design, problem-solving, and debugging.\r\n&bull;    Proficient with Developer Console in publishing and managing the application.\r\n&bull;    Knowledge in integrating web services, TCP and UDP socket programming.\r\n&bull;    Familiarity with HERE SDK Navigation. \r\n&bull;    Knowledge of Android AOSP Automotive ROM  Development.\r\n&bull;    Knowledge of Android build system.\r\n&bull;    Knowledge of Android boot process Deep Analysis.\r\n&bull;    Knowledge of Car Api, Car Services, VHAL.\r\n&bull;    Knowledge of Car Launcher.\r\n&bull;    Knowledge of Boot Animation.\r\n&bull;    Knowledge of SELinux.\r\n&bull;    Knowledge of Car Settings.\r\n&bull;    Knowledge of System UI.\r\n&bull;    Knowledge of Mobile Penetration Testing of Android Application.\r\nOrganization Experience\r\nEmployer :  L&amp;amp;T Technology Services Ltd\r\nDuration : March 2021 &ndash; Till now\r\nDesignation : Senior Engineer(Android  Developer)\r\n Project Name: -Navigation\r\nClient: Scania \r\nAs part of our Android automotive project, we are developing a navigation app specifically tailored for Scania trucks. This app aims to provide Scania truck drivers with reliable and efficient navigation assistance to optimize their driving experience. Our focus is on creating a user-friendly interface that takes into account the unique requirements of truck drivers, such as vehicle dimensions, weight restrictions, and specific road regulations. The navigation features will include truck-specific routing options, real-time traffic updates, and points of interest relevant to truck drivers, such as rest areas and truck stops. To ensure seamless integration with Scania trucks, we are collaborating closely with the client to understand their specific needs and requirements. Our development process involves leveraging the latest technologies and best practices in Android automotive development to deliver a high-quality and robust navigation solution. By working closely with Scania and leveraging our expertise in Android development, we aim to create a navigation app that enhances the driving experience for Scania truck drivers, improving efficiency and safety on the road. \r\nDDU,RIG,QFIL Tools, AOSP, Gadget Testing, HERE SDK, JIRA, Figma, Coverity static analysis.\r\nEmployer :  Barbeque Nation Hospitality Ltd\r\nDuration : August2020 &ndash; Till now\r\nDesignation : Assistant Manager(Android  Developer)\r\nProject Name:-KDS:( Hospitality Management)\r\nhttps://play.google.com/store/apps/details?id=com.bbqn.relayProject based on Hospitality Management.\r\nProject Name:- Samiksha:( ERP)\r\nhttps://play.google.com/store/apps/details?id=com.app.bbqn.samikshaEmployer :  DFoE (Digital Future of Education Pvt. Ltd.)\r\nDuration : February 2020 &ndash; August2020\r\nDesignation : Android  Research Engineer\r\nProject Name:-FRI:( Hospitality Management)\r\nhttps://play.google.com/store/apps/details?id=com.dfoe.friclienthttps://play.google.com/store/apps/details?id=com.dfoe.frimasterhttps://play.google.com/store/apps/details?id=com.dfoe.frikitchenTechnologies used:&nbsp; JSON, REST, TCP and UDP Socket Programming, SQLite Db.\r\nProject based on Hospitality Management.\r\nPayment Gateway integration using Stripe Payment, PayU.\r\ncommunication protocols Socket.\r\nOrganization Experience\r\nEmployer : Ayshwarya syndicate LLP, Bangalore\r\nDuration :August 2019 &ndash; November 2019\r\nDesignation :Software Developer\r\nProject Name:-Spark IN:\r\nhttps://play.google.com/store/apps/details?id=com.assccl.spark.coopProject based on Banking Consumer Account.\r\nPush notification is implemented using Google Firebase.\r\nPayment Gateway integration using Paytm, Razor pay;\r\nImplemented finger print access security and Device lock security.\r\nHere customer can create Health Insurance, Debit and Credit Cards, Bill Payment.\r\nEmployer :  Technoforte Software (p) Ltd\r\nDuration :  August  2018 &ndash; August  2019\r\nDesignation : Associate Engineer -Software. \r\nClient: Toyota\r\nProject Name:- Polygon:\r\nManufacturer of inventory management &amp;amp; parts tracking systems for real-time inventory control    &amp;amp; tracking serial number, date tracking, trace the movement of materials.\r\nAn Integrated ZebraBarCode scanner, library to scan the barcode.\r\nDesigned the database, UI pattern, data-flow between different modules.\r\nTesting the end to end app, database &amp;amp; web-services.\r\nEmployer : Pronto Software Solutions (p) Ltd, Bangalore\r\nDuration :  November 2016 &ndash; August 2018\r\nDesignation : Associate Software Engineer\r\nProject Name:- Sangama:\r\nClient: Karnataka Forest Department - Belagavi Circle.\r\nhttps://play.google.com/store/apps/details?id=com.pronto.sangamaSangama is an application which is designed to help the officers monitor and Update their work status online/offline.Key Features of the app are as follows: \r\nProject Name:- Cricket Score Pad:\r\nhttps://play.google.com/store/apps/details?id=com.pronto.scorepadCricket Score Pad comes closest to the cricket score card you have filled manually all this years. A scorer&rsquo;s delight, Cricket Score Pad&#039;s neat, clean and intuitive design ensures the cricket score book stays upto-the-ball without you breaking a sweat. Use Cricket Score Pad to score multiple match formats (T20 or ODI) or even custom make your own match.\r\nDesign UI pattern &amp;amp; database.\r\nIdentify and correct fix bugs\r\nEmployer : SPH Vibhava Private (p) Ltd, Bangalore\r\nDuration :  April 2016 &ndash; October 2016\r\nDesignation : Software  Developer\r\nProject Name:- SmartPropertyHunt:\r\nCertified Course\r\n4  month Java &amp;amp; Testing Training In &ldquo;ABC For java &amp;amp; Testing&rdquo; in Bangalore\r\n4 month .Net Technology Training in DUCAT Gwalior.\r\n5 month  C,C++,Core Java Training In GLOBAL ICS Delhi\r\n2 Month  Android Training in Falgee Software Development Pvt Ltd Bangalore.\r\nAcademic Background\r\nYear(s) Qualification  Board/University College/ Institute Percentage\r\n2015  Bachelor of Engineering \r\n(Information Technology) Rajiv Gandhi Proudyogiki   Vishwavidyalaya Bhopal\r\n(Madhya Pradesh)\r\nRustamji Institute of  Technology  BSF Academy Tekanpur Gwalior \r\n(Madhya Pradesh)\r\n 7.75 CGPA \r\n2012           Diploma\r\n(Computer Engineering)\r\nBoard Of Technical Education Delhi(B.T.E) BSF Polytechnic STS \r\nTigri Camp, New Delhi    68.00%\r\nPersonal Details Name : Shailendra Semwal\r\nFather&rsquo;s Name : Prakash Chandra Semwal\r\nMother&rsquo;s Name : Prabha Devi Semwal\r\nDate of birth : 06/11/1992\r\nNationality : Indian\r\nLanguages known : English, Hindi (read, write and speak)\r\nPermanent Address : Tehri Garhwal Uttarakhand \r\nDeclaration I do hereby confirm that the details furnished above are true to the best of my knowledge. I bear the responsibility for the correctness of the above-mentioned particulars.\r\nPlace: Bengaluru\r\nDate: (Shailendra Semwal)\r\n', 2, 2, 1, 'Recruiter', 'Un-assigned', NULL, 0, 'N', 14, '2024-07-17 07:24:54', NULL, '2024-07-20 07:24:54', 0, NULL, '2024-07-17 06:49:22', 0),
(379, 91, 73, 38, NULL, '73_91_208471020366976972da32d_HMI_Developer-Swapnil_Thamake.pdf', 'HMI Developer-Swapnil_Thamake.pdf', 'Sw ap nil  T h am ake  \nTe am  L e ad  \n                                             \nap plic a tio n i m pro ve m en ts . C urre n t p ro je ct w ork in g  o n F o rd  C re d it  ( ﬁ nte ch ) a n d  L a st p ro je ct w as w ork e d\n                                       \nsw ap 3848@ gm ail .c o m  \n\nPune, I n d ia  \nlin ke d in .c o m /in /s w ap nil - t h am ake -2 14314a0  \nWORK  E X PER IE N CE \nTe am  L e ad  \nTe ch  M ah in d ra  \n04/2 022 -  P re se n t\n, \n  Pun e \nFo rd  C re d it  A pplic a tio n : ( F in te ch ) \nLe ad in g  t o  m y 2  b ud dy&#039;s  a n d  d eve lo pin g  M obil e  A pplic a tio n\nis  b ase d  o n ﬁ nan cia l a n d  a cco unt m an ag em en t s e rv ic e s \nUse  s k il ls  C ode o ptim iz a tio n, A pplic a tio n s e cu rit y , d esig n\npatte rn s a n d  r e so lv e  l o w  p erfo rm an ce  i s su es. \n                 \n           \nAsso cia te  C onsu lt a n t \nCap gem in i I n d ia  \n02/2 020 -  0 4/2 022\n, \n  Pun e \nHSB C B an k I n dia  \nWork e d  o n F in an ce  D om ain  &amp;  B an kin g  d o m ain  a p plic a tio n.\nIm ple m en te d  s o rt in g , s e arc h in g  a lg o rit h m s a n d  d esig n\npatte rn s. \n                         \nQR c o de, T ra n sa ctio n h is to ry , R ais e  d is p ute . \nAnd ro id , K otlin , R xJav a , D ag ger 2 ,M VP, R etro ﬁ t, J e n kin s,\n                    \nConte xt, H ooks. \nApplic a tio n E ng in eer -  M obil e  A pplic a tio n\nDeve lo per \nRaw  E n g in eerin g  I n d . P vt. L td . \n08/2 018 -  0 1/2 020\n, \n  Vir a r -  M um bai \nIn  R aw  E ngin eerin g i  h ave  w ork e d  o n s p o rt s  d o m ain  p ro je cts  \n                   \n                             \nso rt in g  a n d  s e arc h in g  a lg o rit h m s. \n                 \nRetro ﬁ t, J e n kin s, G it , A W S, X M PP,F ir e b ase , C ra sh ly tic s \nMobil e  A pplic a tio n D eve lo per \nG.N .R eatil  S e rv ic e s P vt. L td .( Z ap m art .c o m ) \n05/2 016 -  0 7/2 018\n, \n  Mum bai \nZa p m art  i s  O nlin e G ro ce ry  P ro du ct B ase d  C om pan y \nReq uir e m en t &amp;  A naly sis , D esig n a n d  D eve lo p A pplic a tio ns,\nWrit e  A PI&#039;s , W ork  o n B ack -e n d  a n d  D B. \nWork e d  o n z a p m art  a p plic a tio n w hic h  b ase d  o n o nlin e\ngro ce ry  s to re . D eve lo ped  o rd er t ra ck in g  f u nctio nalit y  u sin g\nGoogle  M ap . \nAnd ro id , j a v a , V olle y, G it , B it b uck e t, S Q LLit e , F ir e b ase ,\nCra sh ly tic s. \nSK IL L S  \nAnd ro id  S D K \nJav a  \nGit h u b  \nSQ Lit e  \nRest A PI \nMyS Q L \nFir e b ase  \nRxJav a  \nSo narQ  \nAW S \nMVC \nMVVM  \nRO OM  \nJIR A  \nMock it o  \nSyste m  D esig n \nKotlin  \nMult iT h re ad in g  \nJe tp ack  \n \n    \nAlg o rit h m s \nRetro ﬁ t \nData  s tru ctu re  \nFir e b ase  \nRxJav a  \nLiv e d ata  \nReact N ativ e  \nTyp esc rip t \n    \n \n \n  \nPR O FE SSIO NAL P R O JE C TS \nFo rd  C re d it\n ( 0 4/2 022 -  P re se n t)\n \nHSB C b an kin g\n ( 0 3/2 020 -  0 4/2 022)\n \nHaw ks A re n a F a rm  S ta te  &amp;  S acra m en to  K in g &#039;s\n ( 0 1/2 019 -  0 1/2 020)\n \nJD  P ow er\n ( 0 8/2 018 -  1 2/2 018)\n \nMed ic a lw ale  D octo r A pp\n ( 0 3/2 018 -  0 7/2 018)\n \nza p m art .c o m\n ( 0 8/2 016 -  0 1/2 018)\n \nED UCATIO N \nMCA  ( M aste r i n  C om pute r A pplic a tio n) \nKIT &#039;S  I M ER  K olh ap ur \n07/2 013 -  0 6/2 016\n, \n  Kolh ap u r,M ah ara sh tra , I n dia  \nBCA  \nGopal K ris h n a G okh ale  C olle g e K olh ap ur \n06/2 009 -  0 4/2 012\n, \n  Kolh ap u r ,  M ah ara sh tra  ,  I n dia  \n12th  \nS.M .L o hia  C olle g e, K olh ap ur \n06/2 007 -  0 2/2 009\n, \n  Kolh ap u r \n10th  \nJyo tir lin g  v id ya m an d ir  V ad an ag e \n06/2 002 -  0 3/2 007\n, \n  Kolh ap u r \nIN TER EST S \nPho to gra p hy \nSin g in g  \nCric k e t \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s \nAch ie ve m en ts /T a sk s 	\nUnitTest	\nMVP\nAOSP	\nSplunk	CSS	  Jacoco	\n8369096660	\nMobile Application Developer with 8 years of experience in coding, team lead, architecture design and\non HSBC Bank on financial domain . I have also worked on Sports, Health Care, Automative and E-Commerce.	\nReact Native, Typescript, Android, Kotlin, MVVM,\nJWT, Jetpack, Coroutine, Git, Splunk\nDeveloped application with key features like money transfer,\nNexus, SonarQ, Git, SSL pinning, React Native,\nDeveloped application for NBA teams and Automative App\nLive score update with xmpp protocol. Used multithreading,\nAndroid, Java, Kotlin, RxJava, Dagger2, MVP, AOSP,', 2, 2, 1, 'Recruiter', 'Assigned', NULL, 0, 'N', 14, '2024-07-18 04:51:19', NULL, '2024-07-21 04:51:19', 0, NULL, '2024-07-17 06:49:22', 0),
(380, 91, 73, 37, NULL, '73_91_151717347666976972da4c3_Muhammed_Shihab_HMI_Developer.pdf', 'Muhammed Shihab_HMI Developer.pdf', 'MUHAMMED SHIHAB V K	 	\nSenior Engineer Android	 HMI	 	\nThrissur, Kerala, India	 	\n+91	-9526199466	 	\nShihabvk99@gmail.com	 	\nlinkedin.com	/muhammedshihabvk	 	\ngithub.com/muhammedshihabvk	 	\nhackerrank	.com/muhammedshihabvk	 	\nProfile	 	\nEnergetic, Creative, and 	curiosity	-driven Android/Mobile	/HMI 	Developer with 4+ years of experience, I have a deep understanding 	\nof the Android ecosystem	 with 	different	 domain	s like 	Retail	(Leading brands)	 and 	Automotive	(OEM	), including the latest tools and 	\ntechnologies.  I  specialize  in  building  robust  and  efficient  Android  applications  that  provide  seamless  user  experiences.  I  ha	ve 	\nextensive knowledge in various mobile development languages, including Java, Kotlin, and Dart. 	I have experience in working with 	\nAndroid Studio, the Android SDK, and popular libraries.	 	\n \nCore Qualifications	 	\n▪ 	Native 	Android development	 	\n▪ 	Quality assurance	 	\n▪ 	App	 development life cycle	 	\n▪ 	User experience design	 	\n▪ 	Information architecture	 	\n▪ 	Agile software development methodologies	 	\nSkills	 \n▪ 	Programming Languages: Java, Kotlin, Dart	 	\n▪ 	Android Development: Android SDK, Android Studio, \nGradle, Retrofit, RxJava,	 Coroutine,	 Picasso, Glide. 	 	\n▪ 	Tools and Technologies: Git, GitHub, Bitbucket, JIRA, \nFirebase, RESTful APIs, JSON, Google Maps API.	 	\nProfessional experience	 	\nMahindra	 &amp; Mahindra	, Automotive, 	Coi	mbatore,	 Tamil Nadu	              	         	        	Sep 20	23-Present	 	Senior Engineer 	&ndash; Android HMI	 	\nI work	 as an Android Developer, focusing on creating user interfaces and functionality like battery 	\nmanagement, vehicle 	drive mode	, and gallery	, using	 structured	 MVVM architecture	 for Mahindra 	\nBorn 	Ele	ctric Vehicles	. I also worked on connecting our app with car systems using CAN signals. In 	\nteam  meetings,  I  shared  ideas  and  kept  everyone  updated  on  our  progress  and  any  new \ndevelopments. 	Working closely with the product team, I made sure our technical solutions aligned 	\nwith business needs. Even with tight deadlines, I successfully delivered results. I&#039;m known for being \nfriendly,  respectful,  and  always  ready  to  lend  a  hand.  When  faced  with 	challenges,  I&#039;m  good  at 	\nbreaking them down, finding solutions, and making decisions. Whether I&#039;m working independently \nor with a team, I&#039;m effective and adaptable.	 	\n \nSkills	:  Java,  Kotlin,  Android,	 Service,	 Content 	Provider,	 Broadcast	 Receivers	, Retrofit,  M	QTT	, 	\nMVVM,  ViewModel,  LiveData,	 Coroutine,	 Flow,	 Datastore,  Hilt, 	Car	 &amp; CarPropertyManager	 Libs	, 	\nCAN/Ethernet  Signals,	 Glide,  Git	, GitHub	, Canoe	 17,  QFIL  &amp;  Ren	esas(	Device  Flashing)	, Tera  Term, 	\nLottie Animation, Adobe After Effect for Lottie Json with Bodymovin	, Figma, Visure	, LeapX	. 	\nLitmus	7 Systems Consulting,	 Retail, Kochi	,Kerala	                                  	       	            	 Jul 2019	-Sep 2023	 	\nSenior Engineer 	&ndash; Android	 	\nI  made  a 	user	-friendly  e	-commerce  app  for  Android  that  makes  shopping  easy.  I  worked  with 	\ndifferent teams to make sure the app met all the needs and worked well. We added features like \nproduct listings, search, and payment. I also helped junior developers learn and	 grow. I&#039;m good at 	\nall parts of making an app, like testing and putting it on the app store.	 	\n \nSkills: 	Java,Kotlin,Dart,Android,Flutter,	MVVM,  MVP,  ViewModel,  LiveData,  REST  APIs,  Postman, 	\nRecyclerView,  Glide,  WebView  Retrofit/Fast	-Android	-Networking,    Gson/Jackson  Serialization, 	\nRxJava,  Moengage(Analytics,  geofence,  Notification  center),    Chucker(API  logger),Auth  Token \nHandling  with  OkHttp	 Authenticator,  Firebase(Auth,  Crashlytics)  Zendesk  (Chat),  Google  Maps, 	\nCheckout.com  (Payment),  Ticketing  Systems  (Jira/ServiceNow),  and  Git  VCS  (Bitbucket/GitHub \nRemote).	 	\nL3 Associate POS Engineer	 	\nI managed store software like Oracle Micros Point of Sale for retail shops. Every day, I did \nmaintenance for these systems. I worked with different teams to fix any problems, like POS \ndevelopers and database admins. I managed tickets and solved issues, eve	n outside of regular 	\nhours. I also made sure updates were done smoothly and used PowerShell to automate tasks for \nstores in the US and Canada.	 	\n 	\nEducation	 	\nBachelor of Technology (7.07cgpa) \nComputer science and Engineering \nKMEA Engineering College, IN APJ Abdul \nKalam Technological University 	2019	 	\n \nHobbies	 	\nPhotography, Badminton, Listening \nMusic	, Travelling,	 	\n \nLanguage	 	\nEnglish, Malayalam	 	\n \nPersonal Data	 	\n28yrs, DOB 28 March 1996 	S/O Kadher	 	\n9383	-9181	-5394(Aadhaar IN)', 2, 2, 1, 'Recruiter', 'Assigned', 'SL', 1, 'N', 14, '2024-07-18 04:21:20', NULL, '2024-07-21 04:21:20', 0, NULL, '2024-07-17 06:49:22', 0),
(381, 91, 73, NULL, NULL, '73_91_129574815666976972da797_Rajat_Dogra-HMI_Developer_2.pdf', 'Rajat Dogra-HMI Developer 2.pdf', 'RA JA T D O GRA\nAndro id  A pplic a tio n  D eve lo p er	\n8329268366 / 9545898398	kakar ajat10@gmail.com	\nhttps://www .linkedin.com/in/r ajat-dogra-a24409105	Bangalore, White	\nSU M MARY\nEnthusiastic Andr oid Developer with a pr oven tr ack record in leading Andr oid IVI	 	\nsolutions and enhancing user e xperience. Skilled in Core Java, Kotlin, Android	 	\nSDK, and Android Application De velopment. Recognized for boosting customer	 	\nsatisfaction through innovative Andr oid Automotive solutions and str eamlining	 	\ndevelopment pr ocesses. Exceptional pr oblem-solving abilities and a passion for	 	\ndeveloping cutting-edge applications. Eager to contribute to impactful pr ojects	 	\nin line with the company&#039;s mission and vision.\nE X PER IE N CE\nIT  A naly st\nTata Consultancy Services	\n01/2019 - Pr esent	&nbsp;	Bangalore	\nBoosted customer satisfaction b y	 20%	 by leading the tr ansition to Andr oid	 	\nAutomotive for IVI solutions thr ough developing POCs.\nDeveloped multiple Andr oid IVI applications enhancing vehicle inter activity	 	\nand user experience.\nLed 	requir ement analysis	 for (5+ years) major pr ojects, streamlining	 	\ndevelopment and documentation pr ocesses.\nIncreased code performance b y 	20%	 by addr essing pr oduction defects using	 	\nJIRA and GitLab CI/CD .\nExperience of agile methodology such as 	SCRUM 	and 	KANBAN	.	\nDeveloped 	5+	 Andr oid applications, o verseeing full lifecycle de velopment	 	\nfrom 	concept	 to 	deplo yment	.	\nOversaw a team of 	7 developers ensuring timely and quality deliver able.	\nSK IL LS\nCor e Java	Kotlin	Andr oid Application De velopment	\nAndroid SDK	Android Jetpack	Android Testing	MVVM	\nUI/UX Design	RESTful APIs	XML	JSON	UML Diagr ams	\nGitlab CI/CD	GIT	Problem-Solving	Debugging	\nBug T racking	Requir ement Analysis	Softwar e Design	\nST R EN GTH S	\nIn nova tiv e  A ndro id  S o lu tio n s\nPr oven tr ack record in leading Andr oid IVI solutions and enhancing user	 	\nexperience.\nE ffe ctiv e  P ro b le m -S o lv in g S kil ls\nEx ceptional pr oblem-solving abilities in identifying and addr essing	 	\nproduction defects e\nStr e a m lin in g D eve lo p m en t P ro ce sse s\nRecognized for str eamlining development and documentation pr ocesses	 	\nfor major projects.\nPassio n  f o r C u ttin g-E d ge A pplic a tio n s\nEager to contribute to impactful pr ojects and develop cutting-edge	 	\napplications in line with company &#039;s vision.	\nE D UCA T IO N\nBach elo r o f E n gin eerin g i n  C om pute r	 	\nS cie n ce\nUniversity of Mumbai	\n2014 - 2018	&nbsp;	\nA CH IE V EM EN TS	\nEmplo yee of the Month\nRecognized as &#039;Emplo yee of the Month&#039; 5 times	 	\nover a span of 5+ years, sho wcasing	 	\nexceptional performance and contribution to	 	\nthe pr oject.\nHigh Performance Ratings\nReceived the highest performance r ating	 	\nconsistently over a period of 5+ years for	 	\noutstanding skill, work quality , deliverables,	 	\nownership and dedication.\nNominated for Ex cellent Work Award\nNominated for an e xcellent work awar d by TCS	 	\nJapan pr esident in r ecognition of e xceptional	 	\ncontributions.\nIVI Solution Pioneer\nLed Andr oid Automotive tr ansition, developed	 	\ncritical POCs\nAndroid IVI De velopment\nCreated andr oid IVI apps for cars lik e 	Nissan	 	\nAriya	, Nissan Rogue	, enhancing user	 	\nexperience\nE\nOptimized memory usage, impr oved	 	\napplication performance signi\nInno vative Publication\nPublished on auto colorization of gr ayscale	 	\nimages and videos using deep learning in	 	\nICSCET	\nPU BLIC A T IO N S\nAuto m atic  I m ag e a n d V id eo  C olo riz a tio n	 	\nu sin g D eep  L e a rn in g\n2018 International Confer ence on Smart City	 	\nand Emerging Technology(ICSCET)\nRaja t D ogra	\n2018	&nbsp;	\nhttps://ieee xplore.ieee.or g/document/8537308	\n10.1109/ICSCET .2018.8537308	\nE		\nq		\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n&bull;\n\n\n\n	\n)\n)\n)\n)\n)\n)\n)', 2, 2, 1, 'Recruiter', 'Un-assigned', 'SL', 0, 'N', 14, NULL, NULL, NULL, 0, NULL, '2024-07-17 06:49:22', 0),
(382, 91, 73, 39, NULL, '73_91_72373439366976972dabf1_Suresh_HMI_Developer.pdf', 'Suresh_HMI Developer.pdf', 'Suresh_Android Developer	 	\n \n \n \nSuresh Reddy B	 	 	 	 	 	 	 	 	 	Mobile	                     	 	\n 	 	 	 	 	 	 	 	 	 	    	+91 8309076590	                     	\nAndroid Developer	 	\nsuresh.bhumireddy94@gmail.com	                                                                               	 	\n \nProfessional Summary:	 	\n	 		 	\nas a 	Android	 Developer 	for	 Sasken Technologies P	vt Ltd	, Banglore	  . 	\n	 Worked as a 	Android Developer	 from 	 CssCorp	 Pvt	 Ltd	  from 	August	,20	20	 to 	25 Oct,	20	21.	 	\n	  Worked as a 	Android Developer	 from 	 Nextbrain Technologies 	Pvt	 Ltd	  from June,201	8 	\nto Ju	ly,20	20	. 	\n	 Worked as a 	Android Developer	 from 	 KRYPTOBLOCKS 	from June,2017 to 	June,2018.	 	\n	 Significant experience in Developing Mobile (Android) Application and Designing.	 	\n	 An effective communicator with excellent relationship building &amp; interpersonal skills. \nPossess a flexible &amp; detail oriented attitude.	 	\n \n \nMajor Strengths:	 	\n➢ 	Designing a	nd programming 	Android	 apps	 using with UI Components and CoreJava	. 	 	\n➢ 	End to end application development including requirement study and designing.	 	\n➢ 	Implement effective customer satisfaction strategies by identifying the root causes of \ncustomer problems.	 	\n➢ 	Clie	nts management	 	\n➢ 	Adapt in defect analysis and time managed work.	 	\n➢ 	Excellent analytic, design and problem solving skills.	 	\n➢ 	Ability to do disciplined and time managed work.	 	\n➢ 	Strictly adhere to the quality standards, following 	Android	 development guidelines and 	\nQuality system.	 	\n 	\n \nTechnical Background:	 	\n 	\n✓ 	Languages	: CoreJava, Android	,Kotlin	 	\n✓ 	Platform	: Windows,	 Linux	 	\n✓ 	Database	: Sqlite,Room.	 	\n✓ 	Framework	: Android 	SDK	 	\n✓ 	IDE:	 Android Studio	 	\nHaving 6.5 years of experience in Android Application development and currently working	\n,AOSP and Android Framework\n\n✓ 	Tools:	 Bug Tracker ,Active Collab,Gitlab	,Mantis Tracker.	 	\n✓ 	Architecture:	 MVVM, MVP, Clean Architecture.	 	\n \n \nEducational Qualification:	 	 	\n 	Completed B.Tech(E.C.E) from Madanapalle institute of Technolgy and Science 	(JNTU) 	\n,Madanapalle 	in the year 2016.	 	\n 	Completed +2  from	Sri Siddartha Junior College(A.P. board), Andhra 	Pradesh in year	2012.	 	\n 	Completed 10	thwith SathyaSai High School	 (A.P. board), Andhra Pradesh in 	year 2010.	 	\nProfessional Experience	: 	\nProject 1: 	OLA HMI ( Human Machine 	- Interface)	 	\nClient	: OLA Electric 	 	\nRole : Android Firmware Developer	 	\nProject Details:	 	\n OLA 	Electric is a electric scooter which is already available in the market and upgrowing scooter. 	\nEvery part of the scooter is controlled by CAN IDs and it includes sensors for all parts of the \nscooter.	 	\n \nRole: 	worked on HMI and display of the 	scooter,indicators,start buttons ,brakes and side stand 	\n.we used Kanzi UI for display and code base is Android and services.Worked on Wifi feature and \nbluetooth functionality.	 	\n \nProject 	2: SHIKHAR	 	\nClient	: Hindustan Unilever Ltd.	 	\nRole : Android Developer	 	\nPro	ject Details:	 	\nThis  is  a 	Business  to  Business  Android  application  by  Hindustan  Unilever  Ltd.  The  base 	\nfunctionality  of  this  app  is  to  deliver  the  parcels  to  local  stores  or  local  outlets  which  are  tied  up \nto  Unilever.  The  customer  can  order  products  and  do 	payments  in  installment  method  .This  is  a 	\nbig  program  run  by  HUL  where  the  billing  of  ordered  products  will  be  done  by  IKEA.Based  on \ncustomer  purchase  he  can  get  reward  points  and  can  utilise  those  points  while  ordering  the \nproduct.We have integrated you p	ayment and SBI banking process to this application.\n\nProject 	3: Thobey Driver	 	\nRole: 	Developer	 	\nProject Details:	 	\nThis is a laundry service app which includes three panels as they are customer, driver and vendor. \nDriver  can  receive  orders  from  customer  and  a	ssigned  by  vendor,where  thi	s  app  includes 	\nhardware 	printer  integration	 using  AIDL	 and  Google  directions  and  tracking  facility  of 	\ncustomer.  Once  an  order  is  assigned  by  vendor  then  this  driver  will  go  to  customer  location  and \nhe will collect cloths and gene	rate one QRcode for that pickup bag. Then he will deliver the cloths 	\nto same location after laundry.	 	\n \nProject 	4:  DROPR: Delivery and Transportation Service	 	\nRole: 	Developer	 	\nDescription:	 	\nThis is Indian parcel Delivery Appication with 100km Range.By using th	is app customer can assign 	\norder to driver by giving pickup and Drop locations using Google maps Drag and Drop methods as \nwell as Auto Complete address. We can deliver up to 20 Delivery Locations with parcel images \nupload option. While Driver is on Deliver	y ,Customer can able to track the Driver and can able to 	\ncontact via phone. Implemented Offline payment and Online payment (Razorpay payment \ngateway)	 	\nPlaystore Link: 	https://play.google.com/store/apps/details?id=com.app.dropr	 	\n \nProject 	5: DROPR Delivery 	Partner	 	\nRole: 	Developer	 	\nDescription:	 	\nThis app mainly used for track order status,parcel delivery app, can get order from the \ncustomer.By using change order status, He can able to change status also.View order information \nof particular order and should comp	lete order with Digital signature for verification purpose. We 	\ncan view order information of particular order and Notifies order status using push notification.	 	\n \nPlaystore Link: 	 https://play.google.com/store/apps/details?id=com.app.droprdriver	 	\n \nProject 	6: Laparalah Rider	 	\nRole: 	Developer	 	\nDescription:	 	\nAfter payments are made by our customers online, digital delivery orders with details such as\n\norder ID, order items, vendors, customer delivery addresses are generated through our \nmainframe and distributed to o	ur delivery teams so that they can pick up the orders and make 	\ndelivery to our customers. Driver can track customer location also.	 	\nDriver will get orders in two ways ,Manually assign ( admin or vendor can assign order manually \nby using assign to option) an	d Automation (order will assign automatically to the nearest 	\ndriver).Both cases driver will notified using push notification.	 	\n 	 	\nPlaystore Link: 	https://play.google.com/store/apps/details?id=com.app.laparlahdriver	   	\n \nProject 	7: Dumbo Delivery 	- cambodia	 	\nRol	e: 	Developer	 	\nDescription:	 	\nThis is Cambodia parcel Delivery Appication.By using this app customer can assign order to driver \nby giving pickup and Drop locations using Google maps Drag and Drop methods as well as \nAutocomplete address. We can deliver up to 20	 Delivery Locations with parcel images upload 	\noption. While Driver is on Delivery ,Customer can able to track the Driver and can able to contact \nvia phone. Implemented Offline payment and Online payment (Paypal payment gateway).	 	\n 	 	\nPlaystore Link: 	https://play.google.com/store/apps/details?id=com.app.dumbodelivery	 	\n \nProject 	8: Antflip Customer	 	\nRole: 	Developer	 	\nDescription:	 	\nThis is Indian parcel Delivery Appication with 100km Range.By using this app customer can assign \norder to driver by giving pickup 	and Drop locations using Google maps Drag and Drop methods as 	\nwell as Auto Complete address. We can deliver up to 20 Delivery Locations with parcel images \nupload option. While Driver is on Delivery ,Customer can able to track the Driver and can able to \ncon	tact via phone. Implemented Offline payment and Online payment (Razorpay payment 	\ngateway)	 	\nPlaystore Link: 	https://play.google.com/store/apps/details?id=com.app.antflip	 	\n \nProject 	9: Antflip 	- Driver\n\nRole: 	Developer	 	\nDescription:	 	\nThis app mainly used for track	 order status,parcel delivery app, can get order from the 	\ncustomer.By using change order status, He can able to change status also.View order information \nof particular order and should complete order with Digital signature for verification purpose. We \ncan 	view order information of particular order and Notifies order status using push notification.	 	\n 	 	\nPlaystore Link: 	 https://play.google.com/store/apps/details?id=com.app.antflip_driver 	 	\n  \n 	 	 	 	 	 	 	 	 	 	 	 	\n                                                                                                                             	                   	 	\n \n \n \n \n \n \n \n \n \n \n                                                                                                     	                                                 	Signature', 2, 2, 1, 'Recruiter', 'Assigned', 'SL', 1, 'N', 14, '2024-07-18 05:55:13', NULL, '2024-07-21 05:55:13', 0, NULL, '2024-07-17 06:49:22', 0),
(383, 91, 73, 46, NULL, '73_91_177508792766976972daed9_Tabassum_Sayyad-HMI_Developer.docx', 'Tabassum Sayyad-HMI Developer.docx', '\r\nTABASSUM\r\nRESUME\r\n617855199279617855319294Experience Summary and Skill Set\r\nExperience Summary and Skill Set\r\ntabassum.sayyad1@gmail.comContact No: +91-9834112268\r\nResult oriented professional with 8.6 years of versatile experience in Android, Kotlin and Java technology.\r\nCurrently functioning as a Lead product Engineer with Harman.\r\nWorking on Android Automotive domain HMI, DCSM, Android Auto, CarPlay.\r\nWorked on AOSP code.\r\nInvolved pro-actively in various phases of Software Development Life Cycle in terms Analysis, Design, Development, Testing, Implementation, and Maintenance &amp;amp; Support.\r\nProficient experience in developing applications using Android using Java, Kotlin, React Native.\r\nHighly dedicated to produce professional work with highest quality and creativity.\r\nCommitment, hardworking, can grasp things quickly and think strategically.\r\nSUMMARY:\r\nGood knowledge of Android Framework API and Core Java and Kotlin.\r\nKnowledge of Design Patterns(MVP,MVVM), UI Material design(Recycler View, Coordinate layout and Constraint layout)\r\nExperience on remote data via REST and SOAP\r\nUnderstanding of JSON,XML parsing\r\nExperience in payment gateway\r\nExperience in third party libraries Retrofit, Volley, Picasso and Glide\r\nExcellent analytical and logical programming skills with a good understanding at the conceptual level\r\nGood in problem solving, communication skills and good team player\r\nAbility to learn new technologies and work in a dynamic environment and under pressure situations.\r\nHave working experience in agile and waterfall development process.\r\nExperience in Git and have basic knowledge of Jenkins configuration management tools.\r\nExperience to publish Apk on Google play store.\r\nComprehensive knowledge of React Native platform and core principle\r\nCommand over Kotlin.\r\nUsed Live Data\r\nImplemented Kotlin Coroutines for Thread Management.\r\nWorked using Room DB\r\nUsed data classes, Extension function\r\nWorked on RxjavaWorked on Jetpack component\r\nCOMPUTER SKILLS:\r\nLanguage/Platform: Kotlin, Core Java, Android, React Native, JavaScript, Apex\r\nDatabase: SQLite, Room Database, MySQL.\r\nOperating System: Win 10, Microsoft Win 7, Win 8, Ubuntu, Harmony OS\r\nEnvironment /Tools: Eclipse, Android Studio,STS, Android SDK, Git,Gerrit, BitBucketGitLab(Github),BugZilla, JIRA, Jenkins, SonarQube,VS code\r\n\r\nHarman. &ndash; BangaloreMay 2023 &ndash; Present\r\n    Project: PSA \r\n Client: Stellantis Description: The Android Automotive application for car brand called Peugeot, where car driver can   control climate, connect to mirroring projection like Android Auto or Car Play via Bluetooth or USB, able to play music by connecting to USB or Bluetooth, by projection user can connect voice call like incoming or outgoing call.\r\nTechnology: Android SDK, Java\r\n    Role:\r\n  Some of the key responsibilities while executing this project are as listed below -\r\nImplementation of features.\r\nFixing Framework Defects.\r\nWipro Ltd. &ndash; Pune, MHOCT 2020 &ndash; May 2023\r\nProject: ZRPL\r\nDescription: This application provides Wipro employees with substantial savings on ecommerce products. Employees can use this app to log in using their Wipro credentials and buy the product. This app provides a variety of brands, many of which provide substantial discounts on premium brands.\r\nTechnology: Android SDK, Kotlin, React Native\r\n    Role:\r\nPrepare solution based on understanding of the challenges.\r\nImplementation of the solution\r\nWorked in different module such as the product management, Address management and the Cart Module\r\n    Project: HR Direct\r\nDescription: The employee HR capabilities are accessed using this application. Once logged in, the user has access to timesheet, last six months&#039; worth of salary slips, and leave management. Here, employees can use the app to access their leaves and request leaves. Additionally, this application allows you to view and download an employee&#039;s pay slip.\r\nTechnology: Android SDK, Kotlin, React native\r\n    Role:\r\nUnderstand the various challenges faced by employee, management and HR and document the challenges in detail.\r\nDesign and development of the solution\r\nImplementation of the solution\r\nDelivered the project with 0 post-delivery defect\r\nTech Mahindra &ndash; Pune, MHAug 2019 &ndash; Oct 2020\r\n    Project: Messaging App\r\n   Client: HMD Global\r\nDescription: This application offers its users chat (RCS) and texting (MMS, SMS). Everyone has access to group texts and the ability to share images, GIFs, Emojis, videos, and voice communications.\r\nTechnology: Android SDK, Java\r\n     Role:\r\nDesign and development of the solution.\r\nImplementation of the solution.\r\nDevelopment of user friendly UI/UX added additional features like auto deletion of messages, auto texting at scheduled time and other features.\r\nBlue Planet Info Solutions (India) Pvt. LtdJan 2016 &ndash; Aug 2019\r\n \r\nWorked on various products across multiple domains. Product were developed using Android, React native and Java. Below is the list of products developed.\r\nSmartCookie Application which is a student teacher reward system\r\nOne Bay TouchPill Box\r\nTravel PillBoxVirtual PillBoxiTake-med\r\nSafety on Wheels\r\nKnow Your Medi\r\nEducation\r\nAmrutvahini College of Engineering, SangamnerBE in Information Technology | 2012-2015 | Percentage : 60%\r\nPVVP College of Engineering, LoniDiploma in Information Technology | 2009-2012 | Percentage : 67.25%\r\nSharda Kanya Vidya Mandir, RahataSecondary (12th Standard) | 2002-2003 | Percentage : 45.00%\r\nChandak Kanya Vidya Mandir, SinnarSecondary (10th Standard) | 2000-2001 | Percentage : 54.00%\r\nPersonal Details\r\nFull Name:Tabassum Abdul Latif Sayyad\r\nDate Of Birth:22nd May 1986\r\nGender:Female\r\nNationality:Indian\r\nLanguages Known:English, Hindi and Marathi\r\nAddress:Rabiya Nagar, behind Shri Hari hospital, Rahata 423107, Maharashtra.\r\nDeclaration\r\nI hereby declare that above mentioned information is genuine and true to the best of my knowledge.\r\nDate:/  / 2024Sincerely\r\nPlace:  Rahata(Tabassum Sayyad)\r\n', 2, 2, 1, 'Recruiter', 'Assigned', 'SL', 1, 'N', 14, '2024-07-19 10:40:37', NULL, '2024-07-22 10:40:37', 0, NULL, '2024-07-17 06:49:22', 0),
(384, 91, 73, 41, NULL, '73_91_30871182466976972db136_Vishwas_HMI_Developer.pdf', 'Vishwas HMI Developer.pdf', 'Pag e 1  o f 2  \nWORK  E X PER IE N CE :  \nMah in d ra  &amp;  M ah in d ra  L td  (  M ah in d ra  S o ft w are  D efin ed\nVeh ic le  C en te r )  \nSen io r S o ft w are  E n g in eer (  L 7-O pera tio nal  )  \n10 /2 0 23 -  P re se n t\n, \n  Coim bato re  \nFu ll  T im e \nWork e d  a s H M I  D eve lo p er  fo r  M ah in d ra  V eh ic le s a t M SD VC b y E le vatin g  c lu ste r\nfe atu re s w it h  k o tlin  &amp;  J a v a. \nEn han ce d  IV I  M ed ia   ap plic a tio n  b y  im ple m en tin g   ad van ce d  so urc e   se le ctio n\nfe atu re s a n d  f u lf illin g  n ew  r e q uir e m en ts ,  o p tim iz in g  f u nctio nalit y  t o  m eet s p ecif ic\npro je ct o b je ctiv e s. \nSp earh ead ed  th e d eve lo p m en t  o f  S en try  M od e,  P ark  A pp,  M yV eh ic le ,  A m bie n t\nLig hts   IV I \nApplic a tio ns,  in co rp ora tin g   esse n tia l  fe atu re s  to   en han ce   use r\nexp erie n ce  a n d  S ecu rit y . \nSu cce ssfu lly   in te g ra te d   Vid eo   Pla y e r,  Exo   Pla y e r  &amp;  sc re en sh o t  fu nctio n\nim ple m en ta tio ns,  e n ric h in g  th e a p plic a tio n w it h  se am le ss  m ult im ed ia  p la y b ack\nca p ab ilit ie s. \nIm ple m en te d  s e ekb ar f u nctio nalit y  w it h in  t h e a p plic a tio n,  e n han cin g  u se r c o ntro l\nan d  n av ig atio n t h ro ug h v id eo  p la y b ack . \nLe ve ra g ed   JIR A  to   cre ate   co m pre h en siv e   te st  se ts ,  stre am lin in g   th e  te stin g\npro ce ss a n d  e n su rin g  t h o ro ug h c o ve ra g e o f U I e le m en ts  a n d  f u nctio nalit ie s. \nCond ucte d  U I  t e stin g  a n d  in stru m en ta tio n t e stin g  t o  id en tif y  a n d  re ctif y  is su es,\nth ere b y e n han cin g  t h e o ve ra ll  u sa b ilit y  a n d  p erf o rm an ce  o f t h e a p plic a tio n. \nExp ert  in  a ctiv e ly  re so lv in g  B ug s fo r  a  w id e a rra y  o f  a p plic a tio ns,  s p ecia liz in g  in\nboth   se lf - d eve lo p ed   ap plic a tio ns  an d   fo r  In -V eh ic le   In fo ta in m en t  (  IV I  )\nap plic a tio ns. \nUtiliz e d  C A N oe a n d  V eh ic le  S p y s o ft w are  to  p erf o rm  c o m pre h en siv e  h ard w are\nte stin g  o f (C A N )  a n d  (E C U )  s ig nals  f o r V eh ic le  T e stin g ,  e n su rin g  s y ste m  r e lia b ilit y\nan d  f u nctio nalit y  t h ro ug h d eta ile d  s ig nal  a n aly sis  a n d  t ro ub le sh o otin g . \nCap gem in i  En g in eerin g   (  R &amp; D Su b sid ia ry   of \nCap gem in i\nGro u p  )  \nSo ft w are  E n g in eerin g  L e ad  (  P ro fe ssio nal  I / B 1 )  \n04/2 0 23 -  1 0 /2 0 23\n, \n  Ban g alo re  \nFu ll  T im e \nSp ecia liz e d   in   co nnectiv it y   wit h   Apple   devic e s  an d   work e d   on  Apple &#039;s\nte ch no lo gie s s u ch  a s iA P1,  iA P2 a n d  A pple  C ar P la y . \nMan ag ed   a  te am  fo r  deve lo p m en t  of  Apple   co nnectiv it y   fo r  Auto m otiv e\nin fo ta in m en t a n d  m an ag in g  A pple &#039;s  c e rt if ic a tio n p ro ce ss g lo b ally . \nSp earh ead ed   th e  Connectiv it y   dom ain   fo r  sm art   pho ne  in te g ra tio n  w it h\nau to m otiv e  in fo ta in m en t a n d  p ro je ctio n t e ch no lo gie s. \nSp earh ead ed  th e  In fo ta in m en t  sy ste m  an d  re sp onsib le   fo r  han d lin g   m ult ip le\nap plic a tio ns  a n d  re sp onsib le  fo r  d eve lo p m en t  o f  A nd ro id  In fo ta in m en t  S yste m\nwhic h  in clu d es w ork in g  w it h  w ir e le ss p ro to co ls . \nHan d le d  a  t e am  fo r  d esig n a n d  d eve lo p m en t fo r  S m art  P ho ne C onnectiv it y  a n d\nPro je ctio n t e ch no lo gie s in  C onnecte d  C ars . \nHav e  g o od  u nd ers ta n d in g  o f  iA P1,  IA P2,  A O SP  A nd ro id  C ar  P la y  C ontro l  B onjo ur\nse rv ic e  a n d  p erf o rm an ce  t u nin g  o f A pple  C ar P la y  s o lu tio n f o r M Fi  c e rt if ic a tio n. \nSK IL LS  /  T O OLS  :  \nAnd ro id  A pplic a tio n D eve lo p m en t \nCore  J a v a \nGen eric  F ra m ew ork  \nHA L L a y e r \nJa v a 8  \nC P ro gra m min g  L a n g uag e \nC++ \nAnd ro id  T e le p ho ny \nAUTO SA R \nIn fo ta in m en t H ard w are  T e stin g  \nSo narc u b e \nJIR A  \nMVVM  \nIn stru m en ta tio n T e stin g  (  U I T e stin g  )  \nRo om  D ata b ase  \nPerf o rm an ce  T e stin g  \nAD AS \nJIR A  X -R ay  \nGIT H U B \nKotlin  \nKotlin  C oro utin es \nLIN UX \nAnd ro id  S D K \nNav ig atio n C om ponen t \nAuto m otiv e  I n fo ta in m en t \nAO SP  \nAnd ro id  A uto  P ro je ctio n \nApple  C ar P la y  \nTh ir d  P art y  L ib ra rie s &amp;  A PI&#039;s  \nMult im ed ia  I n fo ta in m en t \nFig m a(U I/ U X) \nFlu tte r \nGoogle  P la y  S to re  \nDart  P ro gra m min g  \nBin d er I P C  \nApplic a tio n S ecu rit y  \nSA ST /  D AST \nAnd ro id  F ra m ew ork  \nAnd ro id  A pp D eve lo p m en t \nAID L /  H ID L \nUnit  T e stin g  \nPen etra tio n T e stin g  \nTe le m atic s \nPro je ctio n T e ch no lo gy \nConnectiv it y  \nGIT  \nGIT H U B \nCA N oe \nVeh ic le  S p y \nRA D -G ig asta r \nPR O JE C TS :  \nCogniz a n t :  G oogle  P la y  P ro te ct (  G .P .P  )\n ( 1 2 /2 0 20  -  0 4/2 0 20 )\n \nCap gem in i  :  H A RM AN  (  T o yo ta  T A S70 0 )\n ( 0 4/2 0 23 -  1 0 /2 0 23)\n \nMah in d ra  &amp;  M ah in d ra  :  M ah in d ra  E le ctric  S U Vs H M I I V I\nApplic a tio ns (  B E.0 5,  B E.0 7,  B E.R A LL-E ,  X U V.e 8 ,  X U V.e 9\n ( 1 0 /2 0 23 -  P re se n t)\n Ach ie ve m en ts /T a sk s \nTa sk s \nhk.v is h w as2 0 23@ gm ail.c o m  \n+91 :  7 9 75 35 0 95 8  \nBan g alo re ,  I N DIA  \nlin ke d in .c o m /in /v is h w as-h -k -0 610 4616 6 \nVIS H W AS H  K  \nAnd ro id  A uto m otiv e  H M I / F ra m ew ork / I n fo ta in m en t\nDeve lo p er \nAn e n th usia stic  M ob ile  A pplic a tio n D eve lo p er  (  S o ft w are  E n g in eer  L e ad  )  w it h  a\nro b ust  A nd ro id  Secu rit y   &amp;  p ro gra m min g  exp osu re   h av in g  clo se   to  4  ye ars   o f\nexp erie n ce  in  A nd ro id  H M I/ S D K,  R eve rs e  e n g in eerin g  w it h  h an d s o n e xp ert is e  in\nko tlin ,  J a v a,  F lu tte r,  A nd ro id  S tu d io ,  G IT ,  J IR A  a n d  A uto m otiv e  P ro je ctio n D om ain\nConnectiv it y .  C urre n tly  w ork in g  a s a  S en io r E n g in eer in  M ah in d ra  &amp;  M ah in d ra  \nin  t h e\nAuto m otiv e  so ft w are  la n e a s  a  d ed ic a te d  a n d  fo cu se d  H M I  e n g in eer  p rim arily\nfo cu sin g  o n d eve lo p in g  I V I a p plic a tio ns f o r N ext-G en  M ah in d ra  E V  V eh ic le s.\n\nPag e 2  o f 2  \nWORK  E X PER IE N CE :  \nCog niz a n t T ech nolo g y S o lu tio n s (  C TS )  \nTe ch nic a l  L e ad  (  A pplic a tio n D eve lo p m en t &amp;  A nd ro id  S ecu rit y\nLe ad  )  \n12 /2 0 20  -  0 4/2 0 23\n, \n  Ban g alo re  \nFu ll  T im e \nExp ert is e   in   re ve rs e -e n g in eerin g   an d  co d e-le ve l  se cu rit y   au d it in g ,  as  w ell  as\nexp erie n ce  in  h an d lin g  o b fu sc a te d  c o d es o f a n d ro id  a p plic a tio ns. \nGood  E xp osu re  in  c o nd uctin g  S ecu rit y  T e stin g  o f  b oth  S A ST a n d  D AST a n d  to\nsa fe g uard  a p plic a tio n c o d e f ro m  m alw are  s u ch  a s s p yw are ,  p his h in g ,  r a n so m ware ,\ntro ja n s,  b ack d oor,  r o otin g  a n d  o th er c y b er t h re ats . \nPerf o rm in g  in te rn al  a n d  e xte rn al  v u ln era b ilit y  a sse ssm en ts  a n d  p erf o rm in g  d ata\nan aly sis  a n d  c re atin g  d ete ctio n r o utin es f o r d if fe re n t in te rn al  p ip elin es. \nExp erie n ce  in  M alw are  a n aly sis  o n A nd ro id  M ob ile  p la tfo rm ,  id en tif y  t h re ats  a n d\ncla ssif y  t h em  a cco rd in g  t o  t h eir  f a m ily . \nCond ucte d  M alw are  A ud it in g  o f c lo se  t o  1 0 ,0 00 A nd ro id  A pplic a tio ns in  t h e\nMuW S,  P SL t ra ck s a s a  S M E. \nED UCA TIO N :  \nM.T ech  (  U niv ers it y  V is v esv ara y a C olle g e o f E n g in eerin g  )  \nCom pute r S cie n ce  &amp;  E n g in eerin g  \n10 /2 0 18  -  1 2 /2 0 20\n, \n  Ban g alo re  \n8.9 3 C G PA\n  PU BLIC A TIO NS :  \nTru st M an ag em en t f o r S erv ic e -O rie n te d  S Io T S yste m s \nPub lis h er :  A CM  D ig it a l  L ib ra ry  \nhttp s:/ /d oi.o rg /10 .1 14 5/3 4 46999.3 4 476 35  \nTa sk s \nGra d e', 2, 2, 1, 'Recruiter', 'Assigned', 'SL', 1, 'N', 14, '2024-07-18 11:32:30', NULL, '2024-07-21 11:32:30', 0, NULL, '2024-07-17 06:49:22', 0);
