What do robotics and quantitative finance have in common? Both demand precise decision-making, structured creativity, and real-time optimization skills I developed over a decade in competitive robotics and now apply to financial markets.
I earned a B.S. in Quantitative Finance with Highest Honors from Stevens Institute of Technology, where I led fixed income research for the student-managed investment fund. At SumRidge Partners, I engineered momentum and ETF-based signals for bond alpha prediction and integrated them into an XGBoost-powered RFQ bidding algorithm. At Ernst & Young, I valued complex securities using option pricing and stochastic interest rate models.
I've also built and deployed a fully automated intraday trading system driven by machine learning forecasts of return and volatility. Other projects include a statistical arbitrage framework for Kalshi event contracts and a first-place finish in the Stevens high-frequency trading competition.
I aim to join a fast-paced quantitative research or trading team where I can design, test, and scale alpha-generating strategies. I bring experience working with large datasets, deploying ML models in live trading environments, and solving technical problems under pressure.
If you're looking for someone who pairs hands-on trading experience with strong coding and modeling skills, I'd love to connect. I'm available to connect via Zoom to discuss how I can contribute to your team's research and performance.
