Key Responsibilities:

• Risk Modeling & Attribution Analysis: Develop structured market risk factor models and investigate correlations between trading strategies and various risk factors; perform regular, detailed performance attribution to identify sources of Alpha.
• Strategy Admission & Evaluation: Establish rigorous review mechanisms for new strategy deployment; conduct backtest validation and stress testing to analyze risk metrics, strictly preventing overfitting, survivor bias, or unrealistic transaction cost assumptions.
• Live Monitoring & Drift Analysis: Track statistical consistency between live trading and backtests; quantitatively monitor Tracking Error and Return-to-Drawdown ratios; analyze slippage and market impact; dynamically optimize risk exposure calculation models based on market feedback.
• Capital Management & Limit Optimization: Design and implement capital allocation models for multi-strategy scenarios; optimize capital efficiency and maximize overall returns while adhering to exchange/broker risk limits and compliance constraints.
• Model Iteration & Code Optimization: Continuously refine the codebase for risk calculation and backtesting frameworks to enhance computational efficiency and model accuracy.
• Cross-functional Collaboration: Bridge the gap between Alpha Research and Trading Operations; provide risk-based optimization suggestions to ensure risk logic is integrated throughout the entire strategy lifecycle.

Job Requirements:

• Master’s degree or above in Mathematics, Statistics, Financial Engineering, Computer Science, or related “hard science” disciplines.
• Minimum 1 year of experience in quantitative risk management or research; familiarity with the market microstructure and trading rules of major domestic markets (Equities, Futures, etc.).
• Solid skills of mathematical statistics; proficiency in risk measurement tools, time-series analysis, optimization theory, and common machine learning algorithms.
• Proficient in Python or C++; strong algorithm design and engineering implementation skills with the ability to handle large-scale financial datasets.
• Rigorous critical thinking skills; ability to maintain objective judgment under high pressure; high sensitivity to data anomalies.

Preferred Qualifications:

• Experience in portfolio optimization or capital allocation algorithm.
• Proven track record in building market multi-factor models or live performance attribution systems.
• CFA or FRM certification.