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Mid LevelFull-timePythonC++Git
Salary Range
$51,000 - $69,000 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are seeking a Quantitative Analyst to join our Trading Team, responsible for market making and proprietary trading across options, structured products, and delta one products.
Key Responsibilities
- →Model Implementation & Volatility Fitting: Improve volatility surface construction. Research and implement stochastic volatility models for accurate pricing and risk.
- →Strategy Backtesting & Development: Partner with traders to prototype and backtest new strategies. Analyze historical data to identify patterns and inefficiencies.
- →Project Management: Own quantitative projects end-to-end—from Python research and prototyping to productionization with developers (C++).
- →Tool Development: Build trade analysis tools, scenario simulators, and real-time risk dashboards.
- →Collaboration: Bridge the gap between traders and developers. Translate trader needs into technical specs and ensure timely delivery.
- →Post-Trade Analysis: Perform deep-dive P&L and Greek exposure analysis. Explain performance and suggest improvements.
Requirements
- ✓Master’s or PhD in a quantitative field (Mathematics, Physics, Financial Engineering, Computer Science) from a top-tier university.
- ✓Proven quant experience, preferably in an options market-making or derivatives prop trading firm.
- ✓Track record working with options theory and volatility trading.
- ✓Python is a must; Expert in data analysis, statistical modeling, and prototyping.
- ✓C++ is a strong plus; Experience with low-latency production code or close collaboration with C++ developers.
- ✓Familiarity with Git and collaborative coding.
- ✓Deep understanding of option pricing models (Black-Scholes, local vol, stochastic vol), Greeks, volatility surfaces, and common trading strategies.
- ✓Self-starter who drives projects independently. Strong communication skills to bridge traders and developers. Acute attention to detail and rigorous approach to data validation.
