Summary
Fuad Youssef is a quantitative analyst and trader with nine years of cross-disciplinary experience blending financial engineering, software development, and computational linguistics. Based in Chicago, he currently manages Emerging Markets hard currency and US Treasury relative-value strategies at Neuberger Berman, where he built portfolio replication and rates prediction models that materially cut tracking error and delivered measurable alpha. He holds an MS in Financial Engineering from Columbia and dual BS degrees in Computer Science and Chinese from Georgia Tech, reflecting a rare mix of technical rigor and language/cultural fluency. Prior roles include climate-focused quant research at Mina Analytics and mobile software engineering at NCR, where he shipped production iOS features and extensive data tooling. Fuad’s work stands out for applying machine learning and convex optimization to practical trading problems and for automating complex data extraction with generative AI to streamline ESG research.
9 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS Computer Science Applied Languages and Intercultural Studies (Chinese), Bachelor of Science - BS Computer Science Applied Languages and Intercultural Studies (Chinese) at Georgia Institute of Technology
Master of Science - MS Financial Engineering, Master of Science - MS Financial Engineering at Columbia University
High School Diploma, High School Diploma at Shady Side Academy
Arabic, French, Chinese, English