Xichi He is a statistics-trained data scientist with seven years of analytical experience and a Master’s from UC Berkeley, focused on turning quantitative methods into actionable business insights. He has applied Monte Carlo simulation, time series, PCA, and regression across finance settings—from option and futures modeling at China Securities to FX and equity analysis at Morgan Stanley—demonstrating both theoretical depth and practical implementation in Matlab, R, and Python. Comfortable with large-scale numerical experiments and downside-risk analysis, he also has hands-on experience in credit and cash-flow risk evaluation from banking internships. Based in the San Francisco Bay Area, Xichi pairs rigorous academic grounding and high GPA undergraduate work with a pragmatic focus on reproducible, data-driven decision making. An understated strength is his ability to bridge statistical theory (e.g., least-squares Monte Carlo) with concrete trading and investment scenarios, making complex models usable for stakeholders.
7 years of coding experience
Master of Arts - MA, Statistics, Master of Arts - MA, Statistics at University of California, Berkeley
Bachelor of Science - BS, Statistics, 3.82/4, Bachelor of Science - BS, Statistics, 3.82/4 at Zhejiang University
Contributions:31 commits, 26 pushes, 1 branch in 4 months
pythonmathematicsdiscretewatermelonlinear
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