David Zhao

David Zhao

I am a quantitative researcher at Two Sigma.

I recently graduated with a Ph.D. in Statistics and Machine Learning from Carnegie Mellon University, where my research focused on uncertainty quantification with applications to astronomy. Prior to CMU, I worked as an options trader at Optiver and a research analyst at AQR Capital. I also hold an M.Sc. in Statistics from ETH Zurich and an A.B. in Applied Mathematics from Harvard University.

Education

  • Ph.D. in Statistics and Machine Learning, 2023

    Carnegie Mellon University

  • M.Sc. in Statistics, 2017

    ETH Zurich

  • A.B. in Applied Mathematics, 2013

    Harvard University

Selected Papers

(+) denotes Equal Contribution

Biprateep Dey, David Zhao, Jeffrey A. Newman, Brett H. Andrews, Rafael Izbicki, Ann B. Lee (2022). Calibrated Predictive Distributions for Photometric Redshifts. 39th International Conference on Machine Learning (ICML 2022). Workshop on Machine Learning for Astrophysics.

PDF Poster

David Zhao, Niccolò Dalmasso, Rafael Izbicki, Ann B. Lee (2021). Diagnostics for Conditional Density Models and Bayesian Inference Algorithms. 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021). Spotlight Talk.

Preprint PDF Code

Niccolò Dalmasso (+), David Zhao (+), Rafael Izbicki, Ann B. Lee (2021). Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning in Simulation and Uncertainty Quantification. arXiv preprint.

Preprint Code

Benjamin LeRoy (+), David Zhao (+) (2021). MD-split+: Practical Local Conformal Inference in High Dimensions. 38th International Conference on Machine Learning (ICML 2021). Workshop on Distribution-Free Uncertainty Quantification.

Preprint Code

David Zhao, Alessandro Rinaldo, Christopher Brookins (2019). Cryptocurrency Price Prediction and Trading Strategies Using Support Vector Machines. arXiv preprint.

Preprint

Work Experience

 
 
 
 
 
Quantitative Researcher
Two Sigma Investments
Sep 2023 – Present New York, NY
  • Alpha research
 
 
 
 
 
Quantitative Research Intern
Two Sigma Investments
Jun 2022 – Aug 2022 New York, NY
  • Alpha research for equity feature forecasting
  • Returning full-time in Summer 2023
 
 
 
 
 
Quantitative Trading Intern
Tower Research Capital
Jan 2021 – Jun 2021 New York, NY
  • Developed technical indicators for predicting 30 min and close-to-close single stock returns. Incorporated order book history, Barra factors, GICS, and short interest information.
  • Combined indicators into tradable model using tree boosting (e.g. CatBoost, LightGBM) methods. Model added value and had low correlation to team’s existing strategies.
 
 
 
 
 
Derivatives Trader
Optiver US
Mar 2017 – Mar 2018 Chicago, IL
  • Oil options trader on a small team with shared responsibility for PnL and risk every day.
  • Made markets and trading decisions in real time, adjusted models to changing market conditions, actively monitored opportunities and risks, handled day-to-day operations.
 
 
 
 
 
Research Analyst
AQR Capital Management
Jul 2013 – May 2015 Greenwich, CT
  • Researcher on product providing country and currency strategy exposure without derivatives.
  • Researcher on optimizing account rebalance schedules to reduce turnover and market impact.
  • Researcher on tax loss harvesting strategy that realizes capital gains on a tax-favorable schedule.

Contact

  • dzhaoism AT gmail DOT com