Summary
Zhihan Yang is an analytically driven Audit Staff Accountant with seven years of cross-disciplinary experience blending data science, finance, and quantitative trading. Educated at NYU (BS in Data Science & Finance) and Columbia (MA in Statistics), he pairs strong Python, SQL, and ML toolset knowledge with hands-on experience building data pipelines, alternative financial datasets, and crypto market-making strategies. At firms from EY to IndicatorLab and Union Big Data, he has translated research-grade models (LSTM and other time-series methods) into practical forecasting and diagnostic tools for finance and urban analytics. Comfortable with ambiguity and collaborative across diverse teams, he excels at turning messy, multi-source data into structured, auditable outputs that directly support investment and risk decisions. An unusual mix for an audit professional, he brings quantitative trading experience and ML research instincts to strengthen controls and analytic rigor.
7 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS, Data Science, Finance, Bachelor of Science - BS, Data Science, Finance at New York University
Bachelor of Science - BS, Data Science, Finance, Bachelor of Science - BS, Data Science, Finance at New York University Shanghai
Master of Arts - MA, Statistics, Master of Arts - MA, Statistics at Columbia University
English, Chinese