Job Description & Requirements
Key Responsibilities
Conduct quantitative research on short-term inefficiencies, liquidity, and price dynamics within a single exchange
Design and evaluate arbitrage and market-making strategies, including:
Funding-rate-driven strategies Perpetual futures pricing opportunities Inventory-aware liquidity provision
- Build and maintain event-driven backtests that realistically model execution, fees, funding, latency, and partial fills.
Support live or paper-traded strategies through:
- Performance monitoring
- Post-trade analysis and P&L attribution
- Execution quality and slippage analysis
- Identification of strategy and operational failure modes Iterate on strategies using feedback from live trading behavior and changing market conditions.
Required Qualifications
- Minimum 3 years of proven, relevant experience in this role is required.
- Strong proficiency in Python with experience contributing to research or production trading codebases. Optional/beneficial but not mandatory, working knowledge of at least one systems language such as C++ or Rust (or equivalent).
- Solid understanding of crypto market mechanics, including centralized exchange structures, perpetual futures, and funding rate dynamics.
- Practical experience with execution and risk management, including slippage, fees, partial fills, and basic inventory risk.
- Strong quantitative foundation in probability, statistics, time-series analysis, and market microstructure. Prior experience working with high-frequency market data and supporting live or paper-traded strategies, including performance monitoring, post-trade analysis, and execution quality assessment.
- Ability to conduct independent quantitative research, take ownership of well-scoped projects, and collaborate closely with experienced developers and researchers.
What We Expect at This Level
- Can take a strategy from hypothesis backtest deployment support post-trade review
- Understands the gap between backtest results and live performance
- Able to diagnose underperformance using execution and market data
- Comfortable working in a lean environment with high ownership and minimal supervision
Nice to Have
- Experience supporting or operating live trading strategies
- Familiarity with order- book-based or event-driven backtesting systems
