Summary
Pengyu Zhang is a self-taught data analyst and quantitative finance specialist with a decade of experience combining applied mathematics, statistics, and programming to solve business problems. He holds dual master’s degrees in Mathematical Finance and Applied Statistics from Illinois Institute of Technology and Fordham, and brings strong technical chops in Python (numpy, pandas, scikit-learn), C++, MATLAB, SAS, VBA, and SQL. Experienced in practical problem-solving through industry work with HAVI and personal quant finance projects, he is an FRM Level II candidate who applies both supervised and unsupervised machine learning methods to real datasets. Detail-oriented and methodical, Pengyu bridges rigorous academic training with hands-on implementation, often developing end-to-end analysis workflows showcased on his GitHub site. Based in Nanjing with international education and professional exposure, he is seeking internships or full-time roles in quantitative finance or data analytics where he can turn complex models into actionable insights.
10 years of coding experience
Master's degree, mathematical finance, GPA 3.67, Master's degree, mathematical finance, GPA 3.67 at Illinois Institute of Technology
Major: Applied Mathematics. Minor: Finance, Major: Applied Mathematics. Minor: Finance at Hong Kong Baptist University
Master of Applied Statistics and Decision-Making, GPA 3.7, Master of Applied Statistics and Decision-Making, GPA 3.7 at Fordham Gabelli School of Business
English, Chinese