Chao Ma is a quantitative researcher with nine years of experience melding classic time-series econometrics and modern machine learning to build tradable signals and robust trading infrastructure. His background spans Google software engineering to VP-level quantitative strategy at Goldman and hands-on quant development at hedge funds, where he delivered alpha research, backtests, and production C++ trading servers atop AWS/Linux stacks. Comfortable with TAQ/TRTH microstructure, fundamentals like Non-GAAP AFFO, and niche macro influences such as Farm Bill effects on commodities, he pairs domain intuition with rigorous stats—often preferring R for heavy inference and Python for production work. He prototypes in tmux/nano and Jupyter, uses Streamlit for dashboards, and brings practical DevOps experience (conda/ansible) to bridge research and deployment. Unusually for a quant, his PhD in computational biology and early bioinformatics training inform a probabilistic, data-centric approach to modeling and signal construction.
9 years of coding experience
17 years of employment as a software developer
High school
Ph.D. Computational Biology, Ph.D. Computational Biology at University of Pittsburgh
B.S. Bioinformatics, B.S. Bioinformatics at Zhejiang University
Contributions:20 releases, 8 PRs, 393 pushes in 5 years 1 month
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