Jane Street Quant: From Math Competitions to AI-Driven Trading

In Young Cho, a quantitative trader at Jane Street, shares her unconventional career path from pre-med to quantitative trading. She recounts her experiences interning and working at Jane Street, including using programming languages like OCaml and VBA for trading and development, and humorous anecdotes about interacting with brokers. The episode delves into Jane Street's trading research, from simple linear models to complex deep neural networks, and how they leverage machine learning in low-data, high-noise environments subject to frequent regime changes. In Young Cho details the four stages of her research process: exploration, data collection, modeling, and productionization, and discusses the tension between flexible research tools and robust production systems. Finally, she offers a glimpse into the future directions of Jane Street's machine learning research, including expanding into more asset classes and data modalities, and leveraging AI to enhance trader efficiency.