Job Description:
ArkStream Capital is a private equity fund specializing in digital assets and multi-asset allocation, with assets under management exceeding $100 million. Our funding comes from top-tier Asian listed companies, family offices, and institutional investors. Our team members hail from prestigious backgrounds including MIT, Stanford, Google, and BlackRock, with strategic advisors from Tower Research. We are building data-driven, reproducible systematic research and portfolio management capabilities and seeking quantitative talents with 1–3 years of internship/full-time experience, rigorous research skills, and an entrepreneurial mindset to join us.
Key Responsibilities:
- Data & Research Support: Process trading-related data (executions, positions, prices, costs, etc.), complete cleaning, alignment, and consistency checks to ensure point-in-time correctness in research, avoiding look-ahead bias and data leakage. Build standardized research datasets and feature libraries.
- Backtesting & Performance Evaluation: Implement strategy backtesting and experiments within the existing research framework. Output standardized performance metrics: annualized returns, maximum drawdown, Sharpe/Sortino/Calmar ratios, return distributions, tail risk analysis, and rolling window stability analysis. Analyze structural characteristics such as trading frequency, holding periods, and directional exposure.
- Risk & Portfolio Support: Participate in portfolio-level risk assessment and constraint design. Analyze strategy correlations, concentration, and style drift. Support research and implementation of volatility targeting, risk budgeting, and other capital management frameworks.
Job Requirements:
- Bachelor's degree or higher with 1–3 years of quantitative research/systematic trading experience (internship/full-time).
- Proficient in Python (pandas/numpy) with clean and maintainable code structure.
- Familiar with SQL and capable of independent data processing.
- Understanding and ability to clearly explain core concepts: maximum drawdown, return distributions and skewness/kurtosis, Rolling Sharpe, overfitting and out-of-sample validation, TWR vs. IRR differences.
- Knowledge of trading mechanisms (at least familiar with cost structures, leverage, or margin requirements in one market).
Application Instructions:
To improve your application success rate, please include a one-page personal statement describing a quantitative research project you led or deeply participated in. It should cover:
- Data sources and processing methods.
- How you avoided look-ahead bias or data leakage.
- In-sample/out-of-sample partitioning methods.
- Key evaluation metrics and results.
- Analysis of strategy failures or risk points (if applicable).
Benefits:
- Salary Range: Base salary of 300,000–500,000 RMB.
- Performance Bonus: Linked to portfolio performance.
- Career Growth: Outstanding candidates may gradually take on strategy and portfolio management responsibilities.
