Qinwen Zhai
Quant Associate
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolQinwen Zhai is a Quantitative Associate at Goldman Sachs with eight years of experience applying mathematical, economic, and computational techniques to finance. Trained at HKUST and Carnegie Mellon (Computational Finance), Qinwen blends hands-on trading and fund-structuring experience with academic research in econometrics and database query systems. Past roles include equity derivatives trading at JPMorgan, senior fund modeling at Goldman, and research that introduced novel variables into organ-donation policy analysis—evidence of a knack for bringing unconventional data into quantitative questions. Comfortable coding and web development from early investment-analyst work to GitHub projects, Qinwen pairs rigorous model-building with practical implementation. Based in New York, they are focused on translating research-grade methods into robust trading and risk solutions.
8 years of coding experience
1 year of employment as a software developer
Exchange program, Economics, Exchange program, Economics at Columbia University in the City of New YorkMaster's degree, Computational Finance (aka. Financial Engineering/MFE), 4.03/4.3, Master's degree, Computational Finance (aka. Financial Engineering/MFE), 4.03/4.3 at Carnegie Mellon University - Tepper School of BusinessHong Kong University of Science and Technology (HKUST)
English, Chinese, Chinese
Github Skills (1)
jekyll4
Github contributions (3)
Chelsea-Zhai/CUSPEI
Jul 2017 - Mar 2020
Contributions:4 pushes, 1 branch in 2 years 8 months
Chelsea-Zhai/Chelsea-Zhai.github.io
Jul 2017 - Jul 2017
Contributions:8 pushes, 1 branch in 6 days
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