Description

• 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