LinkedIn Profile I am interested in using quantitative modeling and data analysis to better understand financial markets and support investment decisions. I graduated summa cum laude from Wellesley College with a B.A. in Computer Science and Economics and also studied finance and machine learning at MIT. At GIC, I developed cross-asset risk analytics, including VaR attribution, PCA-based risk decomposition, and clustering analysis to evaluate portfolio exposures and diversification. I also built data-driven frameworks to study macroeconomic regimes and extract market-implied growth and inflation signals across equities, rates, currencies, and breakevens. As a research assistant at MIT Sloan, I built an OpenAI-based pipeline to analyze SEC comment letters and used panel regressions to study the market effects of financial regulation. My earlier internships and projects also gave me experience in multi-factor modeling, tactical asset allocation, and sentiment analysis. At MSCF, I hope to deepen my skills in financial mathematics, statistics, and computing while exploring quantitative research opportunities across asset classes and strategies. My interests include systematic investing, portfolio research, and global macro. Outside finance, I enjoy language-decoding puzzles, drawing, and photography. Studying and working across US, Singapore, and China has also given me a global perspective on financial markets and collaboration. I'm available to meet virtually or in person to discuss how my analytical skills and unique background can immediately benefit your team.
