Options Quant Researcher

Responsibilities

• Calibrate volatility surfaces using real market data, accounting for gaps, latency, and noise.
• Ensure surface smoothness, arbitrage-free conditions, and temporal stability.
• 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, particularly near expiry or around illiquid strikes.
• Tune and debug models under realistic market conditions including bid/ask spreads and incomplete markets.

Requirements

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

Preferred Qualifications

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

Benefits

• Fully remote work environment with a flexible schedule.
• Opportunity to collaborate with industry leaders from firms like Tower, DRW, and Credit Suisse.
• Compensation for health insurance, sports activities, and non-professional training.
• A modern, international work culture free from heavy bureaucracy.

About the Company

BHFT is a proprietary algorithmic trading firm managing 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.