Summary
Liyi Li is an equity analyst and data scientist with nine years of experience blending machine learning and traditional fundamental research to drive alpha in global public equities. She has built end-to-end data-driven investment processes at Neuberger Berman and Hwabao WP, leveraging large alternative datasets, NLP on filings and transcripts, and bespoke forecasting that delivered notable stock picks and outperformed benchmarks during downturns. Proficient across Python, R, Hadoop, AWS, and visualization tools, she pairs rigorous quantitative pipelines with hands-on sector expertise in Media, Technology, and Consumer names. Her background includes deploying production-scale KYC and marketing databases and managing live trading portfolios, reflecting a rare mix of engineering, trading, and client-facing experience. Based in New York with strong academic credentials from Zhejiang and Fordham, she actively shares reproducible work on GitHub, signaling a commitment to open-source tooling in investment research.
9 years of coding experience
4 years of employment as a software developer
Master of Science (M.S.), Business Analytics, 4.0/4.0, Master of Science (M.S.), Business Analytics, 4.0/4.0 at Fordham University
Bachelor of Economics Science in Economics, Economics, 3.8/4.0, Bachelor of Economics Science in Economics, Economics, 3.8/4.0 at Zhejiang University
Chinese, English, Russian