Education
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2021 - 2022
University at Buffalo, The State University of New York
Masters in Data Science (STEM)
GPA: 4.0/4.0 (Gold Medallist) Courses: Introduction to Probability Theory | Numerical Mathematics for Computing | Statistical Learning and Data Mining | Programming & Database Fundamentals | Introduction to Machine Learning | Data Intensive Computing
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2014 - 2018
Netaji Subhas Institute of Technology, New Delhi, India
Bachelors in Engineering – Electronics and Communication Engineering
CGPA: First Division
Experience
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2022 - 2022
PayPal Inc. (Internship) | San Jose, California - United States of America
Decision Scientist Intern – Consumer Fraud Risk Strategy
• Leveraged Click Stream Data to perform behavioral analysis during new customer onboarding to detect large scale real-time bot attacks
• Processed huge volumes of Risk Instrumentation data (~250Million sessions/day) to research user interactions using Big Query processing
• Performed Exploratory Data Analysis to engineer and extract features with high differential power out of 50+ unique factors and variables
• Implemented a supervised learning model to predict 2x more carding attacks saving millions of dollars in transactional operation costs
• Collaborated with various Risk, Instrumentation and Data Science teams to enable production ready edge variables for building strategies -
2020 - 2021
American Express (Full time) | Gurugram, Haryana - India
Assistant Manager – Product Development, International Lending Analytics
• Developed robust automated data pipeline equipped with quality checks through Shell and Hive scripting to reduce manual efforts by 100%
• Launched innovative opportunity sizing tool for 150+ international markets to track portfolio performance and actionable growth insights
• Carried out profitability analysis for Customer Offer Bundling using KNN and A/B testing to study user behavior for similar groups
• Designed Net Credit Margin & Growth Decomposition tool to ramp-up revenue margin visibility across 50+ credit product offerings Analyst – Product Development, Credit and Fraud Risk Capabilities June 2018 – July 2020
• Delivered hybrid big data MIS reports for tracking credit and risk performance across various business verticals via Microsoft BI Stack
• Formulated a one-stop Portfolio Pandemic monitoring for analyzing & mitigating overall loss exposure across client/merchant relationships
• Leveraged inhouse Anomaly Detection Framework to get proactive data alerts & insights to minimize data quality issues by 30% annually