Summary
Caleb Brody is Chief Data Scientist at an asset manager overseeing analytics and data integration for over $200M in assets, partnering closely with portfolio managers to vet investment ideas and design new products. With nine years in quantitative finance—including roles at Citigroup and MetLife—he blends rigorous statistical training (Master’s in Statistics from Berkeley, Summa Cum Laude B.S. in Applied Mathematics from Rutgers) with hands-on engineering across C#, Python and large-scale ML systems. He has experience building and operating machine learning pipelines at the 100 TB scale, and maintains responsibility for the firm’s entire data stack and cross-source integration. Prior roles teaching advanced VBA and building SQL workflows evidence a practical focus on turning complex analytics into usable business tools. Caleb’s work sits at the intersection of quant research and production engineering, ensuring models are both statistically sound and operationally deployable. Based in Toledo, he brings a rare combination of academic rigor, enterprise experience, and pragmatic coding to asset management analytics.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Science (BSc) Applied Mathematics; Economics, Bachelor of Science (BSc) Applied Mathematics; Economics at Rutgers Business School
Master's degree Statistics, Master's degree Statistics at University of California, Berkeley, Haas School of Business