Quantitative Analyst (Options)

Job 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.

Job 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.