Quant Developer

ETrading Companies edge in energy derivatives is built on the quality of our pricing, volatility models, and risk management. As Staff Vol Options Quant Engineer you will sit at the boundary between rigorous financial research and production engineering - writing models that run live on the trading floor, priced in real time, monitored in production, and generating PnL. You will work directly with traders and risk managers in a true front office environment where the feedback loop between your research and market outcomes is immediate. This is not a research lab role.

Requirements

• 10-15 years combined quant research and software engineering; minimum 5 years embedded in a front office (any asset class)
• Options pricing across the full surface - vanilla, spreads, and structured products in commodity or energy markets
• Vol surface calibration: smile fitting, SABR, SVI, Heston, or equivalent; arbitrage constraints and numerical stability in production
• Greeks and second-order risk: delta, gamma, vega, volga, vanna, theta; PnL attribution and daily risk reconciliation
• VaR, stressed VaR, and scenario analysis implementation; working knowledge of regulatory capital frameworks
• Commodity modelling: term structure, forward curve construction, seasonality, convenience yield, and basis risk
• Real-time pricing and risk system design - latency-aware implementation, incremental recalculation, and feed-driven revaluation
• Backtesting framework design: walk-forward validation, statistical significance testing, and performance attribution
• Production-quality Python and/or C++ - code an engineer can review, a CI pipeline can test, and an ops team can support
• kdb+/q, DB, or TimescaleDB for high-frequency time-series market data storage and analysis
• Ability to set a research agenda independently and communicate risk and findings clearly to senior traders and management
• Cloud infrastructure - Azure preferred, AWS considered; IAM, managed services, automated and auditable deployment pipelines, secrets management

Nice to Have

• Market making, systematic execution, or electronic trading in energy or commodity derivatives
• Asian options, barrier structures, or path-dependent exotics common in commodity markets
• Machine learning applied to vol forecasting, regime detection, or execution cost optimisation
• Open-source quant library contributions, published research, or CQF/MFE/PhD in a quantitative discipline

To find out more about Huxley, please visit www.huxley.com

Huxley, a trading division of SThree Partnership LLP is acting as an Employment Business in relation to this vacancy | Registered office | 8 Bishopsgate, London, EC2N 4BQ, United Kingdom | Partnership Number | OC387148 England and Wales