Tianren Zhang is an Assistant VP in Quantitative Analytics with eight years of experience applying statistical modeling and machine learning across sell-side and buy-side institutions, currently leading QA scenario work at Barclays. He holds an MS in Financial Engineering from Columbia and a high-achieving Applied Mathematics BS from NUS, and has practical experience building production-ready backtesting and risk models at Goldman Sachs, UBS, and KPMG. His background blends rigorous academic training with hands-on model development and validation—from predictive models for offshore asset valuation to A-IRB and SACCR assessments—reflecting strong quantitative instincts and production discipline. On GitHub he signals interests in representation learning and generalization, suggesting a drive to bridge advanced ML research with quantitative finance applications.
8 years of coding experience
Master of Science - MS, Financial Engineering, 3.8/4.0, Master of Science - MS, Financial Engineering, 3.8/4.0 at Columbia University in the City of New York
Summer exchange, Applied Mathematics, A+, Summer exchange, Applied Mathematics, A+ at University of California, Los Angeles
Bachelor of Science - BS, Applied Mathematics, 4.74/5.0, Bachelor of Science - BS, Applied Mathematics, 4.74/5.0 at National University of Singapore
Contributions:10 commits, 9 pushes, 3 branches in 9 months
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Tianren Zhang - Assistant VP In Quantitative Analytics