Simon Yan

Simon is a graduate-level data scientist with a strong foundation in quantitative methods and real-world experience applying machine learning to financial markets. At Cornell, his coursework spans Machine Learning, Monte Carlo Simulation, Markov Chains, and Stochastic Processes — giving him a rigorous probabilistic and statistical grounding that goes well beyond typical bootcamp-style ML exposure.

His most significant AI work came during two internships at Central China Securities. As a Quantitative Investment Researcher, he used Python to optimize 10+ multi-factor alpha signals by incorporating market-regime classification models, engineered a modular backtesting framework simulating 20+ equity strategies, and architected an automated ETL pipeline processing over 100,000 daily data entries.

He led the quantitative strategy for a private-equity forecast engagement with The Riverside Company (heading a team of 7) and founded RoomExchange, a peer-to-peer university housing platform that won 2nd place at the UC Davis Big Bang! Business Competition.

Simon's stack includes Python, R, SQL, Java, Tableau, Docker, and Git. He's a strong mentor for students applying ML and AI to quantitative finance, building data pipelines, or exploring algorithmic strategy development.