Jan 2022 – Jun 2022 · 5 mos · Ann Arbor, Michigan, United States

• MATH 628 - Machine Learning for Finance - I (Winter'22 Semester)
• Recipient of 100% Tuition Scholarship awarded by Department of Mathematics

Aug 2021 – Dec 2021 · 4 mos · Ann Arbor, Michigan, United States

• MATH 700 - Machine Learning For Finance - II (Fall'21 Semester)
• Recipient of 100% Tuition Scholarship awarded by Department of Mathematics

Nov 2020 – Aug 2021 · 9 mos · Bengaluru, Karnataka, India

• Worked on building an end‐to‐end, fault‐tolerant time series forecasting pipeline for one of the largest FMCG companies in the world
• Executed feature selection techniques such as Mutual Information regression and Ridge regularization for implemented in multivariate models.
• Implemented a framework using Kalman filters for missing value imputation and a Hill‐Climbing Bayesian network for enhancing univariate time series forecasts. Designed a bias correction logic and used Twitter’s Anomaly Detection algorithm for outlier treatment in time series forecasting
• Forecasted key financial metrics for multiple business units using Python and PySpark replacing a manual 20 day procedure

Jan 2020 – May 2020 · 4 mos

• Applied statistical modeling techniques to price mortgage collateral in excess of $500 million notional across various jurisdictions (EMEA and APAC) for multiple portfolio types by cross collaborating with peers and trading desks scattered across New York, London and Hong Kong.
• Developed robust and scalable systems which can handle inevitable market movements and stream algorithmic prices to electronic trading platforms as well as automatically quote a subset of the incoming trade inquiries using live market data, product attributes, and manual trader inputs.
• Received an Accelerated Promotion to Associate in 1.5 years based on outstanding performance

Jul 2018 – Dec 2019 · 1 yr 5 mos

May 2016 – Jul 2016 · 2 mos · Gurgaon, Haryana, India

• Designed and implemented a strategy to increase customer spending per month in a leading e-commerce giant of UK by applying machine learning techniques on client’s customer base to identify discount responsive customers.
• Applied cluster analysis and K-means clustering algorithm to segment customers to offer more personalized targeting. Received Job Offer based on outstanding performance

May 2015 – Jul 2015 · 2 mos · Mumbai Area, India

• Performed Company Profiling to understand advantages of partnering with other companies based on parameters such as average ticket size, size of customer base, sales per day etc.
• Conceptualized cross promotional activities allying with companies across different industries, reaping maximum benefit
• Associated with Clients such as Naaptol, Starbazaar, Zopnow, Go4fresh,in & What The Fun which enriched potential TinyOwl user experience
• Executed promotional campaigns in corporate offices such as Oracle, Nielson, Red FM
• Analyzed Consumer Behaviour based on customer’s food ordering habits and offer preferences