Options Quant Researcher

Responsibilities

• Calibrate volatility surfaces on real market data, handling gaps, latency, and noise
• Enforce smoothness, arbitrage-free conditions, and temporal stability in models
• Tune and debug models under realistic market conditions including bid/ask spreads and incomplete markets
• Design and implement logic for position-driven dynamic surface shaping based on portfolio Greeks (vega, gamma, skew)
• Identify and mitigate residual noise in implied volatility surfaces near expiry or around illiquid strikes

Requirements

• Proficiency in Python with strong experience in NumPy, pandas, matplotlib, and SciPy
• Practical experience applying volatility models within live TradFi trading environments
• Experience with standard quant libraries such as QuantLib or custom volatility tools
• Experience with MFT (Medium-Frequency Trading) research

Preferred Qualifications

• Experience with PyTorch or TensorFlow for applying ML/DL models to volatility problems
• Experience with NSE options or other TradFi derivatives with margin impact
• Understanding of model explainability and the risk of overfitting in execution-sensitive environments
• Direct experience in spot/futures vs. options arbitrage

Benefits

• 100% remote work environment with a flexible schedule
• Opportunity to collaborate with industry-leading professionals from firms like Tower and DRW
• Compensation for health insurance, sports activities, and non-professional training
• Professional growth opportunities within a modern, low-bureaucracy international company

About the Company

BHFT is a proprietary algorithmic trading firm that manages the full trading cycle, from software development to strategy coding. We trade a broad range of asset classes, including equities, options, and commodity futures, using both HFT and MFT approaches. Our team of over 200 professionals is highly technical, with 70% specializing in development, infrastructure, and analytics.