• Lead a team accountable for overall planning, implementation, and effectiveness of professional development strategies and initiatives. 
• Designing and maintaining data systems and databases; this includes fixing coding errors and other data-related problems.
• Mining data from primary and secondary sources, then reorganizing said data in a format that can be easily read by either human or machine.
• Preparing reports for executive leadership that effectively communicate trends, patterns, and predictions using relevant data.
• Collaborating with programmers, engineers, and organizational leaders to identify opportunities for process improvements, recommend system modifications, and develop policies for data governance.
• Creating appropriate documentation that allows stakeholders to understand the steps of the data analysis process and duplicate or replicate the analysis if necessary.
• Establish, direct, and maintain a learning management system that ensures effective learning outcomes using E –Learning and M – Learning.

• Huge Data-sets are extracted, compiled and tracked data, and analyzed data to generate reports.
• Dividing the project to multiple modules. Allocating the start and end dates for each module.
• Developing and Maintenance of the Industrial projects.
• Involved in developing various Hardware applications using Python, Embedded C with Arduino and Raspberry’s.
• Helping students for their final year project to do their own.

• Lead a group project to build a Natural Language Processing model to optimize headlines
• Built a Machine Learning Model to forecast oil prices for the Commodities Team
• Built Dashboards using PowerBI to review efficiency of a rules system for FX Team
• Implemented a tool to monitor Vendor Error Capture Rates
• Worked on a project to implement a tool to capture provincial loans data

• Design, implementation, and deployment of large scale facial recognition system
• Detection and removal of outliers to increase accuracy while simultaneously reducing the memory consumption of the facial recognition system
• Expanded the datalab’s documentation repository and promoted it to a centralized body of knowledge
• Communicated consistently with stakeholders to align expectations 

• Responsible for Data loads and ETL implementation
• Completely Automated Product Production deployment processes using SQL stored procedures
• Worked with SQL dynamic queries for data implementation
• Designed many SSIS packages with SQL 2012 for the data load
• Worked with Cubes, Performed Testing for the release of new patch for the product betterment
• Provided Training to the Resources on same product

• Collect and perform computational and statistical analysis of biological data. Quality check and troubleshoot data issues and queries
• Analyze and interpret results, and provide concise data reports and data visualisations
• Lead infrastructure teamOversee the School’s servers day-to-day operational and technical support for a wide range of internal and external applications
• Responsible for provisioning, installation/configuration, operation, and maintenance of IT Tools and Software
• Provide scientific or technical guidance and support to staff and students
• Coordinate School’s activities/events website design, content and development 

• Produced monthly club-member reports using advanced Excel spreadsheet functions.
• Created Microsoft Excel formulas to streamline data entry and collection.
• Curated Powerpoint presentations for superior use.
• Assessed, cleaned and structured new data sources (Spark Scala, Apache Hive, PowerBi)

• Developed audience development strategy for Immigration social media channels which increased followers by 30% year over year. 
• Created strategy based on data analysis to lower rates of immigration fraud in India via marketing campaign, and reduced rates by 15% year over year. 
• Started this journey in the field of data analysis at Datacamp by learning a number of new languages such as Python and doing projects by Datacamp.
• Mainly the projects involved pre-existing fed data-sets, that needed to be analysed using various tools and technologies.

•  Contributed in the organizational data-driven strategy by providing ad hoc insights and creating comprehensive datasets to respond to different business lines: marketing, sales, IT, audit, compliance, engineering
• Analyzed customer behavior towards credit cards and digital products
• Devised comparative targeting experiments centered around user adoption and retention of digital products and credit cards multiservices
• Designed and developed data pipelines to catalyze targeting campaigns 
• Worked closely with POs and UX to translate the experiment proposals to actionable decisions and plans for client targeting on offer releases
• Assessed their effectiveness to maximize the results of future campaigns (Tableau, Hive, Excel)  
• Reduced duplicated work and enabled customizability by modularizing  targeting campaigns ETL processes and extracting their core functionalities (Spark Scala, ScalaDoc)

• Creating dashboard in Excel and Tableau for data reporting using pivot tables and VLOOKUP.
• Error review of resources.
• Conducting feedback session to improve process workflow and error handling.
• Preparing production and quality data of process.

• Understanding the operational challenges faced by clients, and implementing data driven reports to address their issues.
• Identify opportunities for optimization of energy consumption, using analytical means
• Conducted pre-voir dire research to identify biases of potential jurors
• Updated and directed attorneys about unfavorable jurors throughout voir dire as the venire changes

•  Collaborate with the business stakeholders and SME to gather requirements.
• Innovative Tableau dashboard and stories presented the insights of analysis and articulate business solutions which reduced the overheads by 20%.
• Increased productivity in terms of resource utilization by 15%.
• Predicted impact on profitability by 30% using Machine Learning models.

•  Labeling is an R&D activity that contributes to the development of the Automatic Driver Assistance System in the Automotive industry. 
• We generate the schematic data by analyzing and marking attributes on video files that are captured by a camera. 
• The labeled data will be used as a reference in the development or evaluation for the camera, radar sensor, and algorithm.
• The scope of our activity is to set up and run a complete labeling production line by transferring competence from the onshore team.

• Designed and developed schema data models. 
• Analysed the company’s data over size 200,000 to provide the better insight of the products. 
• Developed database objects, including tables, views and materialised views using SQL. 
• Developed an interactive visualisation prototype of network graph showing how different data are related in a timeline. 
• Designed, developed, and implemented dashboard using tableau. 
• Tools used: Python, Tableau, Git. 

• Created DLBR, HLBR to implement Edifecs Encounter management systems for Medicare and Medicaid Markets.
•  Monitored the data coming from different sources and check if 837 files are generated by Edifecs according to market specific requirements.
• Made sure whether generated 837 files were compliant through HIPAA level 5. 
• Used SQL to pull claims according to the scenario required and validated the data to see whether Edifecs is populating the same values and fields.
•  Performed UAT testing against the current market specific requirements. 

• Process large amounts of data for statistical modeling and graphical analysis, using R programming from the SAP Hana database.
• Identify relationships and trends in data, as well as any factors that could affect the results of the Market Mix Model.
• Developed an understanding of fields to which statistical methods are to be applied to determine whether methods and results are appropriate.
• Developed ROI analysis and Recommendation of products for futuristic predictions that can be visualized in Tableau.

• Collects, cleans, transforms and validates data as a process for arriving at conclusions
• Developed algorithm to convert insurance-orientated ICD-9 codes to clinical practice meaningful disease classification
• Conducted data analysis using logistical model, LDA, KNN, tree classification and random forest method to identify high readmission risk patient and improved the accuracy
• Using Sentiment Analysis and built a Word Cloud and identified how many positive and negative responses are coming from the public
• Proposed solutions to improve system efficiencies and reduce total expenses

• Worked on primary websites for validation data.
• Working on over match hit-app to match the target information with the give candidate information.
• Check the location of the target whether it is in the navigable range.
• Involves verification of data of different markets like the USA, Canada. 

• Working on data provided based on customer feedback reports by diffrent comapnies for theor product launch
• Generating reports on Future performance of the product.
• Rigorously worked with 60 tables across 5 schemas. Handled large sized data like 60 million records across 30 attributes, 2 million records across 250 attributes.
• Effective experience of data import/export, wrangling, pre-processing, cleaning, tabulation, manipulation, visualization, building machine learning models and working with data frames, matrices, lists and use of packages in R and Python.

• Data Analyzing
• Tagging in documents
• Outsourcing
• Photo editing in photoshop
• Task assign 

• Efficiently developed and presented 2 machine learning models in R catering multiple requirements like self-trade feature promotion and retention improvement. Models resulted in 23% incremental lift in self-trade feature users and 12% increased retention respectively. 
• Implemented SOO strategy – Designed and coded over 60 events to be communicated at various stages in customer and business life-cycle with cool off and governance implementation. 70% events gained positive response. 
• Assisted in building genome-based recommender system, core part of organization’s product, that provided personalized stock-recommendations for a customer.
• Programmed Multi-Armed Bandit algorithm with Reinforced Learning that helped client in effective and personalized targeting for campaigns and also 30% decrease in unfruitful communication costs.
• Redesigned fully automated and self-reactive ETL process using Pentaho Data Integration BI software which resulted into 50% reduction in time. Created smart kettle jobs and transformations for fetching 60 tables daily from client server with email alerts at important checkpoints. 
• Developed an automated KPI monitoring/reporting Dashboard using Knowage, an open source business analytics tool. Single-handedly took care of dashboard backend – ETL flows, tables, SQL coding.
• Adept at advanced scripting (DDL, DML, sub-queries, JOINS), creating Stored Procedures, managing multiple Schemas, Tables, Views in MySQL Workbench.

• Obtain data from other departments in certain periods. 
• Monitor and audit data quality.
• Present data.
• Take part in improvement projects done to support analyses.
• Carry out any other related responsibilities when directed by superior.

• maintain company database
• assist in creation of templates in Microsoft excel, word and powerpoint
• data and integrity checks, clean data, extract and ensure data is ready for use in templates
• data dump into template shells, customise for client needs
• prepare visualisations and tables for use in word or powerpoint reports and dashboards
• prepare word and powerpoint reports and dashboards for Media Analysts
• train and troubleshoot for Media Analysts in database, excel, word and powerpoint

• Customizing Data of the Products related to the client requirements.
• Search for the Data on  Search Engines and Edit or Customize it according to the Product.
• Upload the Data of the Products on the E-commerce Site like Amazon, E bay, Shopify and Etc.
• Handle Seller accounts and Vendor accounts to maintain and manage products.
• Upload Images and Edit bullet Points Via Seller or vendor accounts.
• Raise the Tickets for the product which has been not published on the site to get published and to be on the top page.

• Worked on large number of data sets for a Project in a food and beverages Industry
• Converted data into actionable insights by predicting and modeling future outcomes. 
• utilized MS-SQL,Tableau, and other dashboard/visualization tool sets for analysis.
• Implemented various statistical technique.
• Using AWS data analytics tool AMAZON KINESIS SERVICES.

• Analyses company data and make the report on how company was performing in the current situatuon.
• Document data quality and traceability documents for each source interface. 
• Establish standards of procedures. 
• Generate weekly and monthly asset inventory reports. 

• Chat bot Development (Microsoft Bot Framework)
• News Recommendation Engine
• Information extraction from PDF
• REST API development and integration

• Developing and implementing machine learning algorithms for specific determinations about system performance. 
• Data quality assurance, data cleaning and curation, data visualization, and data production. 
• Collaborating with marketing professionals for writing market insights reports 
• Responsible for development of new programs, analyses current programs and processes. 
• Experienced in writing complex SQL queries in performing Data analysis using window functions, joins, improving performance by creating partitioned tables. 
• Performing data cleaning and data transformation activities using Python. Guiding team members in implementation and execution of machine learning models at different levels of project life cycle. 

•  Identify, analyze, and interpret the complex data sets
• Develop and implement databases, data collection systems, optimize efficiency and quality
• Acquire data from primary  data sources and maintain databases through researching 
• Performed data quality in Talend Open Studio. 

• Solving complicated business problems for organizations, leveraging conventional & new age data sources and a wide array of tools & techniques. 
• Liaising with the clients and stakeholders to understand their requirements, challenges etc. and keeping them up to date on the progress of our proposed solution. 
• Staying connected to the Analytics industry trends- big data, cutting edge technologies, open source tools etc. and leveraging them to develop learning modules. 
• Responsible for preparing scheduled and ad-hoc reports, and actively participate in different implementation projects as per the organizational roadmap.