Robert Martin
Stealth
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolRobert Martin is a trader at D. E. Shaw with nine years of experience applying physics-rooted quantitative thinking to finance, bridging statistics and software to produce practical trading strategies. He created and continues to maintain PyPortfolioOpt, a notable open-source Python library for portfolio optimization where he implemented features like market-neutral constraints, exponential covariance methods, and James-Stein shrinkage. His background spans prop trading internships and quant research roles at top firms including BlueCrest, Point72, and GIC, giving him both research rigor and practical market experience. An ex-astrophysics student and former combat medic, he pairs analytical depth with composure under pressure and a hands-on engineering approach. Comfortable as a back-end developer, he focuses on clean refactors and robust testing to make complex quantitative tools reproducible and accessible. Based in New York, he blends academic pedigree from Cambridge with entrepreneurial drive and a passion for elegant, intuitive explanations of complex systems.
9 years of coding experience
4 years of employment as a software developer
MA, Astrophysics, MA, Astrophysics at University of CambridgeIB Diploma Programme, IB Diploma Programme at St. Joseph’s Institution International
Spanish, English
Github Skills (8)
pandas10
statistical-models10
python10
optimisation10
linear-algebra10
optimization10
numpy10
financial-analysis9
Programming languages (10)
Github contributions (5)
PyPortfolio/PyPortfolioOpt
May 2018 - Dec 2022
Financial portfolio optimization in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 releases, 597 commits, 156 PRs in 4 years 7 months
Contributions summary:Robert's commits primarily focus on implementing new features and refactoring the codebase for financial portfolio optimization. They implemented a market-neutral constraint for efficient risk, tested the efficient frontier, and added new methods for exponential covariance. Further, they integrated and tested the James-Stein shrinkage estimator, while also contributing to core classes like ``BlackLittermanModel`` and refactoring existing functions.
pythonfinanceportfolio-optimizationportfolio-managementquantitative-finance
robertmartin8/RandomWalks
Jul 2017 - Jan 2022
One-off scripts/analysis, usually to accompany my blog posts.
Contributions:31 commits, 23 pushes, 1 branch in 4 years 7 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.