Tier 1 Hedge Fund - China-A Quantitative Researcher

Design, construct, and refine predictive features from high-frequency and/or daily market data

Conduct exploratory data analysis to uncover structural inefficiencies and alpha opportunities

Implement and evaluate statistical, machine learning, or basic deep learning models for signal generation

Perform robust backtesting, validation, and out-of-sample testing to assess signal stability

Collaborate with traders and engineers to transition research models into live trading environments

Monitor live performance and iterate on models based on market regime shifts

1-3 years of experience in quantitative research, systematic trading, or related analytical roles

Practical experience in feature engineering, including data cleaning, transformation, and signal construction

Working knowledge of machine learning methods (e.g., tree-based models, linear models, ensemble methods); exposure to deep learning frameworks is a plus

Experience researching or trading China A-shares or commodities futures markets preferred

Strong programming skills in Python (experience with libraries such as pandas, NumPy, scikit-learn; familiarity with PyTorch or TensorFlow advantageous)

Solid understanding of statistics, probability, and model evaluation techniques

Degree in Mathematics, Statistics, Computer Science, Engineering, Finance, or related quantitative discipline