Options Quant Researcher

About Us

BHFT is a proprietary algorithmic trading firm managing the full trading cycle, from software development to creating and coding strategies and algorithms. Our trading operations cover key exchanges across a broad range of asset classes, including equities, equity derivatives, options, commodity futures, and rates futures. We employ a diverse array of algorithmic trading strategies, utilizing both High-Frequency Trading (HFT) and Medium-Frequency Trading (MFT) approaches, and we are continuously expanding into new markets and products.

Our team consists of 200+ professionals with a strong emphasis on technology—70% are technical specialists in development, infrastructure, testing, and analytics. Our employees are located worldwide, from the United States to Hong Kong, and we operate as a 100% remote organization. At BHFT, clarity and transparency are at the core of our culture, with open communication and straightforward processes.

The Role

We're looking for a Quant Researcher with hands-on experience applying volatility models in live trading in TradFi markets.

Responsibilities

• Calibrate volatility surfaces on real market data, including handling gaps, latency issues, and other realistic market conditions
• Enforce smoothness, arbitrage-free conditions, and temporal stability in volatility models
• Tune and debug models under realistic market conditions—including bid/ask spreads, noise, and incomplete markets
• Design and implement logic for position-driven dynamic surface shaping, including how current portfolio Greeks (vega, gamma, skew) should influence surface parameters such as skew, curvature, and wing behavior
• Dynamically adapt surface shape based on current exposure with hands-on implementation
• Identify, model, and mitigate residual noise in implied volatility surfaces, especially near expiry, around illiquid strikes, and in event-driven conditions

Requirements

• Python (mandatory) with strong use of NumPy, pandas, matplotlib, SciPy, and relevant optimization/ML libraries
• Familiarity with standard quant libraries such as QuantLib or custom volatility tools
• Practical experience calibrating volatility surfaces on real market data
• Understanding of how to enforce smoothness, arbitrage-free conditions, and temporal stability
• Experience tuning and debugging models under realistic market conditions
• Ability to design and implement position-driven dynamic surface shaping logic
• MFT'ish research experience is required; HFT experience is a nice to have

Nice to Have

• PyTorch / TensorFlow experience (strongly preferred)
• Experience with NSE options and/or other TradFi derivatives with margin impact
• Familiarity with practical heuristics for surface management
• Working (not just academic) experience applying ML/DL models to volatility problems
• Understanding of model explainability and risk of overfitting in execution-sensitive environments
• Direct experience in spot/futures vs. options arbitrage

Benefits

• Work at a modern international technology company without the burden of bureaucracy
• Collaborate with industry-leading professionals, including former employees of Tower, DRW, Broadridge, Credit Suisse, and more
• Excellent opportunities for professional growth and self-realization
• Work remotely from anywhere in the world with a flexible schedule
• Compensation for health insurance, sports activities, and non-professional training