Hi — I’m Yanzhong (Eric) Huang, a quantitative researcher and developer currently pursuing my Master of Quantitative Finance at Rutgers Business School (Class of 2024). My work bridges finance, data science, and software engineering, with a focus on systematic investing and quantitative research.

I’ve built models and tools across the investment lifecycle — from multi-factor signal research and backtesting engines to portfolio optimizers and performance attribution frameworks. I’ve worked at hedge funds, asset managers, and quant startups, managing live portfolios and deploying tools used by over 500 clients. My recent roles include quant developer at Quantel AI and Sincere Digits, and fund analyst at Hongchou Investment.

This site is where I document my work — including open-source projects like Bagel-factor, my blog notes on quant research, and Python tooling for China A-share data.

I’m currently looking for full-time opportunities in the U.S. starting in 2025, in quant research, systematic trading, or financial engineering. Feel free to reach out or explore my GitHub and LinkedIn.

Contact me:

Email: [email protected]
Github: https://github.com/bagelquant
Linkedin: https://www.linkedin.com/in/eric-huang-506185181/
X: https://x.com/EricYanzhongH

Education

RUTGERS, THE STATE UNIVERSITY OF NEW JERSEY

Rutgers Business School, Newark, NJ - Dec 2025
Master of Quantitative Finance
GPA: 4.0/4.0

MONASH UNIVERSITY

Melbourne, Australia - Jan 2021
Master of Banking and Finance

CAPITAL UNIVERSITY OF ECONOMICS AND BUSINESS

Beijing, China - Jun 2018
Bachelor of Business Administration with a major in Accounting

Experience

Quantel AI, Inc – New York, US

Summer Intern, June - Present

  • Researched and implemented over 100 fundamental and technical factors for U.S. equities.
  • Automated factor evaluation including IC, t-statistics, and forward returns using pandas and statsmodels.
  • Built stock scoring models with LSTM and tree-based ensemble methods to generate long-short signals.

Sincere Digits Co., Ltd- Beijing, China

Quantitative Developer, Oct 2022 - Jan 2024

  • Led a backend team of 4 to develop fund selection APIs serving over 500 clients.
  • Developed fund metrics (Sharpe, VaR, AVaR, exposure) for multi-dimensional screening.
  • Established event-driven backtesting engine for factor strategies and client performance analysis.
  • Designed mean-risk portfolio optimizer supporting variance, AVaR, and factor-constrained models.
  • Maintained and optimized MySQL-based data pipeline for cleaning and ETL.
  • Collaborated with marketing team to deliver internal seminars on multi-factor modeling.
  • Refined sales materials by aligning quant language with investment logic, improving clarity and team credibility.

HongChou Investment Co., Beijing, China

Fund Analyst, May 2021 - Sep 2022

  • Designed data mining pipeline (clustering, pattern mining) for 4,000+ Chinese private funds.
  • Built risk scoring system reducing fund universe to a curated shortlist of 300 high-quality funds.
  • Automated data ingestion and dashboard reporting in Excel VBA, streamlining weekly fund reviews.
  • Assisted investment committee in selecting a pool of 50 investment-ready funds with scenario analysis.
  • Managed 5 funds with total AUM of ¥20M CNY, achieving an average 20% return from Aug 2021 to Aug 2022.
  • Conducted due diligence on two quant private funds per week and authored comprehensive analysis reports.

Skills

  • Programming: Python (scikit-learn, TensorFlow, Keras, tkinter, PyQT), C++, R, SQL, MATLAB, VBA, Linux, Java.
  • Tools: MySQL, PostgreSQL, Git, GitHub, PyCharm, Tableau, MS PowerPoint, MS Excel, LaTeX.
  • Finance/Quant: Machine Learning, Deep Learning (RNN, LSTM), Optimization, Data Analysis, Multi-Factor Models.