HFT Options Quantitative Researcher in London

Join to apply for the HFT Options Quantitative Researcher role at DeepFin Research. DeepFin is a systematic proprietary trading firm combining deep learning, traditional quantitative research methods, and cutting‐edge trading technology to trade global markets. Founded by engineers and researchers, we build and deploy advanced trading systems that operate across global markets. Our team is lean, highly technical, and impact‐driven – every hire plays a direct role in shaping the firm's technology, strategy, and performance. We value curiosity, precision, and collaboration, and we're building an environment where exceptional people can do their best work at the intersection of AI and financial markets.

We are seeking a Quantitative Researcher with hands‐on HFT options and market‐making experience to join our High‐Frequency Options Volatility Trading Desk. The ideal candidate will have direct experience developing, testing, and deploying low‐latency trading models for options market making, including vol surface fitting, execution optimisation, and hedging strategy design. This is a front‐office research and development role – working closely with traders, quants, and engineers to turn research into live production strategies.

• Volatility Surface & Pricing Models: Design, implement, and calibrate ultra‐fast vol surface models for equity and index options (e.g., SVI, SABR, Vanna‐Volga). Integrate models into live trading systems for real‐time fitting and quoting. Collaborate with quant devs to optimise model performance and stability across exchanges.
• Market Making & Execution Research: Develop and refine high‐frequency quoting, hedging, and execution algorithms. Optimise order placement, queue position, and fill rates to reduce adverse selection and slippage. Analyse market microstructure and order‐book dynamics to improve execution logic.
• Realised Volatility & Signal Forecasting: Build and enhance short‐horizon real‐time volatility and spread forecasting models. Use high‐frequency tick data to identify predictive microstructure and volatility patterns.
• Risk & P&L Analytics: Design real‐time delta/gamma/vega hedging frameworks and risk dashboards. Conduct PnL decomposition, tracking contributions from alpha, execution, and carry. Backtest strategies with realistic latency and cost models.

• Mandatory: Direct experience in high‐frequency options trading – preferably market making on equity or index options.
• 3–7 years' experience in a quant research or trading role at an HFT, prop firm, or leading options market maker.
• Deep understanding of options pricing, Greeks, and market microstructure.
• Experience with vol surface modeling (SVI, SABR, stochastic vol) and real‐time model calibration.
• Proven background designing and testing execution logic and hedging systems in production.
• Strong programming ability in C++ and Python; experience with low‐latency systems is a plus.
• Advanced degree (Master's or PhD) in Mathematics, Physics, Statistics, Computer Science, or a related field.

If you're passionate about applying advanced technology to real‐world markets and want to work alongside a focused, high‐performing team, we'd love to hear from you. DeepFin offers a collaborative, research‐driven environment where ideas move quickly from concept to execution and where every contribution has visible impact. Join us in building the next generation of deep‐learning‐driven trading systems – shaping the future of finance through innovation, rigour, and technology.