Experience

Kaggle

• United States
• IT Services and IT Consulting
• 400 - 500 Employee

• Kaggle Competition Expert (Top 0.5%)

  • Jun 2019 - Present

  Kaggle : Jane Street Market Prediction Top1% (27/4245) Kaggle : Mechanisms of Action Prediction Top1% (42/4347) Kaggle : Jane Street Market Prediction Top1% (27/4245) Kaggle : Mechanisms of Action Prediction Top1% (42/4347)



Kafang Technology

• China
• Financial Services
• 1 - 100 Employee

• Quantitative Analyst

  • May 2022 - Sep 2022

  High-frequency proprietary trading (2-ticks level) High-frequency proprietary trading (2-ticks level)



QTG Capital Management

• Investment Management
• 1 - 100 Employee

• Quantitative Research Analyst

  • Jun 2021 - Nov 2021



Essence Securities Co., Ltd

• China
• Investment Banking
• 200 - 300 Employee

• Quantitative Analyst Assistant (Machine Learning)

  • Aug 2019 - Mar 2020

  • Developed Alpha factors using China stock market abnormal signals in pre-market call auction stage. • Built a strategy backtesting framework for single factor analysis and strategy performance analysis. • Designed T+0 strategy with an average annual return of 107% and an average annual maximum callback of 9.68% • Developed Alpha factors using China stock market abnormal signals in pre-market call auction stage. • Built a strategy backtesting framework for single factor analysis and strategy performance analysis. • Designed T+0 strategy with an average annual return of 107% and an average annual maximum callback of 9.68%



Point Zero One Technology Ltd.

• Hong Kong
• Financial Services

• Quantitative Researcher

  • May 2019 - Aug 2019

  • Developed machine learning models to separate top and bottom signals of tick data from trade stocks. • Transformed 72 high correlated variables into 14 uncorrelated variables by PCA for 1 million stock transactions.  Implemented and evaluated various models, including Logistic Regression, Gaussian Mixture and Quadratic Discriminant Analysis on a real-world dataset. • Implemented Semi-Supervised Learning to reinforce generalization ability, increasing win ratio from 53% to 59%. • Developed machine learning models to separate top and bottom signals of tick data from trade stocks. • Transformed 72 high correlated variables into 14 uncorrelated variables by PCA for 1 million stock transactions.  Implemented and evaluated various models, including Logistic Regression, Gaussian Mixture and Quadratic Discriminant Analysis on a real-world dataset. • Implemented Semi-Supervised Learning to reinforce generalization ability, increasing win ratio from 53% to 59%.