The Role
This is a role for someone who sees structure where others see randomness.
You will design, build, and run statistical arbitrage strategies—transforming data into signals, signals into portfolios, and portfolios into repeatable, risk-adjusted returns.
The focus is simple: identify inefficiencies, exploit them systematically, and evolve as those inefficiencies disappear.
What You’ll Do
- Develop and manage market-neutral, statistically driven trading strategies
- Extract alpha from cross-sectional relationships, mean reversion, and short-term dislocations
- Translate research into live trading with a strong focus on robustness and scalability
- Continuously refine models as market dynamics shift
- Own portfolio construction, risk allocation, and execution quality
- Work closely with researchers and engineers to improve data, tools, and infrastructure
How You Think
- In probabilities, not certainties
- In distributions, not single outcomes
- In portfolios, not isolated trades
You understand that:
- Most signals decay
- Backtests require skepticism
- Capacity matters as much as performance
- Risk emerges when assumptions break
What You Bring
- Demonstrated experience building or managing statistical arbitrage strategies
- A strong foundation in statistics, quantitative methods, or machine learning
- Ability to independently generate, test, and implement trading ideas
- Proficiency in Python or similar tools for research and development
- Deep understanding of execution, transaction costs, and market behavior
- Ownership mindset with a focus on outcomes
What You’ll Find Here
- A research-driven environment focused on results
- Access to high-quality data and reliable infrastructure
- Collaboration with experienced quantitative professionals
- The ability to focus on building and improving strategies without unnecessary complexity