At WorldQuant Brain, I developed and optimized quantitative alphas in Fast Expression Language using cross-sectional factors, time-series operators, and fundamental datasets. I evaluated signal quality with Sharpe, turnover, fitness, and robustness measures, then refined signals through normalization, decay, and risk-exposure controls.
My projects include financial valuation and equity research, plus a financial NLP/RAG pipeline for historical Federal Reserve communications using MATLAB and PostgreSQL. I also analyzed FX markets and backtested a systematic trading framework on Lean Engine.
