Monetization Ecosystem

- Building, Maintaining and Improving the Surge Pricing Algorithm (Primetime & Offer Selection) on Rideshare.- Designed and built automated pricing framework for Lyft Rentals to improve capture of profits and collect experimental results on user price sensitivity.- Architected and implemented a cross-functional data infrastructure refresh for Lyft Fleet to enable optimization of fleet supply management.

- Implemented and optimized model fitting processes, cost-saving trade logic, and model diagnostic improvements for a $60m algorithmic portfolio product deployed for live trading, programmed in R.- Updated production code with exception handling, and automated outputs to reduce required human supervision of the portfolio.- Researched and implemented commodity shock and liquidity risk metrics to better manage portfolio risk tolerances, programmed using Groovy SQL and R. - Developed experimentation framework to measure implementation costs for a $500m forthcoming fund product.- Managed research requests by communicating cross-functionally with PMs, developers, and the CIO to specify problem statements and objectives, conduct hypothesis tests, and deliver findings.

- Managed client relationships and responded to client needs in a timely manner, including asset transfers and FX.- Improved team portfolio measurements to better track client cash flows and anticipate shortage of funds.

US & International Equities:- Supported portfolio managers with ad-hoc quantitative research and analytics for factor-based strategies deployed on a portfolio of over $2.5b.- Validated the accuracy of financial data collected for a database of more than 3000 securities globally.- Developed a packaged time series analysis app with R Shiny to simplify security analysis for portfolio managers.- Researched a machine learning-based method for forecasting Japanese stock buybacks.