Rupam Banerjee Email & Phone Number

Nagpur, MH, IN

San Francisco, US

San Francisco, US

New York, New York, US

• Part of Fraud Strategy & Analytics team for Marcus Lending PortfolioManaged 3 line of businesses: Personal Loans, Marcus Pay (Buy Now Pay Later) and Line of Credit for Small Businesses
• Optimized existing fraud strategies by identifying redundant and low performing rules and onboarded new Fraud Vendors leading tosmoother customer experience (additional ~2M in annual revenue) and reduction in overall.
• Automated E2E testing for deploying new Fraud strategies across all the products saving 50 man-hours per month.
• Developed automated systems using Python and Tableau to proactively identify unusual spikes across all products and stop fraudulent activities saving $3M in losses per year
• Designed KPI reporting framework for Lending portfolio in Tableau which is used by leadership for key decision making.

Riverwoods, IL, US

• Part of Fraud Operations Analytics team for Discover Credit Card Products
• Developed critical reports that helped track different types of frauds across various segments and devise strategies to prevent them and automate the entire process leading to saving ~$250,000 per month.
• Automated the manual categorization of customer complaints and feedbacks, saving 90 man-hours per month.
• Streamlined the process of extraction of structured and unstructured Credit Bureau data and loading it into a table in Snowflake using Python for analysts and agents to be able to use it for customer profiling.
• Performed A/B Tests on implementation of new fraud strategies and features in a product leading to a reduction in fraud rate by 2.5% and increase in self-service rate by 8%.
• Conducted trainings and documented step-by-step process of transitioning to Air9, Airflow and Snowflake leading to quicker and convenient switchover for my team.

Buffalo, NY, US

• Worked as Research Assistant for Department ProfessorsProject 1: Prediction of Ticket Sales for an Ice-Hockey StadiumDescription:
• Performed exploratory data analysis and created 20+ user interactive dashboards in Tableau to visualize trends and impact of potential variables affecting ticket sales.
• Implemented Regression and Tree models using Python to predict the ticket sales and identify the key features.
• Automated the entire pipeline starting from pulling the data from AWS RedShift, running the model to visualizing the key business metrics important for decision making.Project 2: Trends in Medical ReferralsDescription:
• Scraped 100K records of doctor details like ratings and reviews from doctor rating websites using Python.
• Manipulated and merged huge historical referral datasets (~100 GB) with scraped data in AWS Redshift.

Bengaluru, Karnatka, IN

Part of Data Engineering Team for a financial services clientRoles and Responsibilities:- Performed ETL (Extract-Transform-Load) activities from different sources to gather information and designed data flows for BI reports.- Optimized performance of a critical set of monthly ETL jobs by reducing its execution time by 30%, improving complex SQL queries.

Master'S Degree, Management Information Systems, General

B.E, Electronics And Communication