BS Computational Engineering + Mathematics @ UT Austin '21
MSE Data Science @ University of Pennsylvania '22
June 2019 - August 2019
At IHS Markit, I added over $3M to the company's Wall Street Office (WSO) product revenue by developing an automated loan tracking / reconciliation tool for internal purposes. The tool was built to handle several complicated client-specific enhancements and is estimated to have reduced 50+ hours of manual labor for each reconciliation cycle.
June 2020 - August 2020
At Point72 Asset Management, I conducted in-depth stock research and offered recommendations to senior analysts and portoflio managers. The analyses were a mixture of qualitative (DCF, comparables, three-statement models) and quantitative (hypothesis testing) components. I also leveraged large datasets from third-party vendors (e.g., AppAnnie) to motivate my investment theses.
February 2022 - May 2022 (joining full-time)
At Vanguard IMFS (Investment Management Fintech Services), I built an API (Python) for several common use cases that allowed the team to access and implement Refinitiv financial data at a much faster pace. I also carried out several statistical tests and backtests (Python, time series, online learning) on order flow imbalances to identify potential investment signals.
February 2022 - April 2022
Though I only worked with Starry from the contractor position, I audited and improved one of their random forests models (R, Snowflake) that was to be placed in production to identify high-reward marketing targets. The resulting model (after I had improved it and checked relevancy) could predict raw subscriber increases with an error rate of \(\pm 1\) subscriber >80% of the time.
June 2022 - December 2022
At FairPlay AI, I worked primarily on the Home Mortgage Data Act (HMDA) datasets in order to characterize the state of mortgage fairness in the country. I examined intersectional mortgage fairness as well as geographic fairness differences in lending markets and generated insights that would later be converted into thought leadership pieces for the company (the culmination of my work can be found here, though press coverage of this report can be found on Forbes, USA Today (paywall), and Yahoo Finance.). Later, I worked on creating a baseline framework with custom metrics for marketing fairness (i.e., how fairly is a lending institution marketing their services across represented and underrepresented populations?). This analysis is the first of its kind.
The only publicly available, vetted database of 200+ AI startups providing ethical services. EAIDB has received recognition from Open Data Science and the Montreal AI Ethics Institute. EAIDB's reports have received over 200 downloads.
A study investigating the relationship between the nature of a country's sports teams and that country's overall happiness.
An image recognition algorithm platform meant to process conservationists' photos and identify characteristics such as type of animal, number of animals, etc. and place bounding boxes around the subjects.
A research project conducted with IEEE and Winlab at Rutgers University. The goal was to devise a rover with a unique locomotion method that utilized a combination of linear actuators and wheels to traverse tough terrain.
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