Job Description
As a Quantitative Researcher, you will play a key role in our data-driven investment strategies. You will work closely with our research team to develop, test, and implement quantitative models that drive our trading decisions.
Key Responsibilities
- Data and Research Support: Interface with and maintain data sources/APIs, complete archiving, incremental updates, and consistency checks. Clean and align trading data (executions/positions/prices/costs) using SQL for EDA. Verify key metrics (equity, unrealized P&L) to ensure point-in-time accuracy and prevent data leakage. Maintain standardized datasets/feature libraries and promote metric unification and version control.
- Factor and Label Research: Design labels and return metrics (holding period, forward return alignment) to ensure reproducibility. Calculate and maintain cross-sectional factors (missing value treatment, winsorization/standardization/neutralization/orthogonalization) with proper documentation and versioning. Evaluate factors through IC/RankIC/ICIR, group backtesting, turnover decay, and correlation/multicollinearity checks.
- Backtesting and Performance Evaluation: Maintain backtesting and experimentation workflows to support research framework iteration. Conduct in-sample/out-of-sample and robustness tests, verifying key parameters and results. Output metrics including annualized returns, drawdowns, Sharpe/Sortino/Calmar ratios, return distributions and rolling stability; identify structural issues.
- Risk and Portfolio Support: Participate in risk constraint design (position/leverage/concentration/drawdown circuit breakers) with focus on tail risks. Analyze correlations and style drift to support weighting and capital management (volatility targeting/risk budgeting). Contribute to attribution and iteration from backtesting to live trading, producing materials as needed.
Job Requirements
- Bachelor's degree or higher
- 1+ years of quantitative research/systematic trading experience (including internships)
- Proficient in Python (pandas/numpy) and SQL with clean, maintainable code
- Familiar with Git and collaborative development; able to work within unified research frameworks
- Experience with data ingestion and processing, emphasizing data quality, metric consistency and reproducibility
- Ability to explain: maximum drawdown, return distributions, rolling Sharpe; overfitting and out-of-sample validation/Walk-forward; factor calculation and evaluation; label alignment and lookahead bias prevention; TWR and risk-adjusted returns
- Understanding of cost structures and leverage/margin mechanisms in at least one market
Preferred Qualifications
- Research or live trading experience in any market (equities/futures/CTA/commodities/crypto)
- Multi-factor research experience (discovery, evaluation, synthesis and portfolio construction)
- End-to-end experience from "data → factors/models → portfolio → risk → live trading"
- Risk management/portfolio management project experience; understanding of common backtest biases
Benefits
At ArkStream, we've maintained our entrepreneurial spirit through 8 years of growth. We're looking for individuals who are excited by new markets, genuine opportunities, and complex problem-solving.
Our address-level behavioral factor strategy represents a fundamentally new approach to on-chain trading, requiring us to rebuild the entire quantitative pipeline from data to signals to portfolio construction, execution and risk management.
We seek team members who want to do more than complete isolated tasks - we want people who will work alongside smart, professional, execution-focused colleagues to build, launch, iterate and scale this system together.
Core team members won't just be system builders - they'll share in the system's long-term success through performance-based strategy profit sharing.
If you're looking for more than just a stable job - if you want to build something truly new with capable partners - we'd love to meet you.
Please send your resume and personal statement to [email protected].
