How I Became a Quant
Summary
The NYU-published piece chronicles a personal journey into quantitative finance, outlining the educational background, skillset, and project work that enabled the transition into a quant role. It emphasizes mathematical foundations, programming, and data-driven problem solving, offering transferable lessons for data science, automation, and AI practitioners. While not AI-specific, the content provides practical insights into modeling, tool selection, and continuous learning relevant to tech-forward businesses.