Summary
James Hirschorn is a consultant in data science and quantitative research with nine years of industry experience and a deep academic foundation as a former research mathematician with postdoctoral positions and publications in international journals. He blends financial engineering expertise—an MSc in Mathematics in Finance and buy- and sell-side experience—with hands-on machine learning work across biotech, edtech NLP, and volatility strategy backtesting. Comfortable in R, C#, C++ and MATLAB, he has built high-performance libraries for risk systems and rewritten core components to achieve multi× speedups. At Quantitative Technologies he continues to deliver models and tooling for production use while previously developing an NLP-driven asset recommendation engine for enterprise clients. Based in Phnom Penh and available for remote work, he pairs rigorous theoretical training with pragmatic software engineering to solve complex stochastic and econometric problems. A lesser-known strength is his track record of integrating unmanaged high-performance code into production analytics—bridging research-grade methods and production constraints.
9 years of coding experience
5 years of employment as a software developer
MSc, Mathematics in Finance, MSc, Mathematics in Finance at New York University
Bsc, Mathematics, Bsc, Mathematics at University of Toronto