Why this role stands out
This role offers an exciting opportunity to leverage your quantitative expertise within a leading, technology-driven trading firm, contributing to the refinement of cutting-edge systematic strategies and driving innovation across diverse asset classes. You'll thrive here if you are a proactive individual eager to take ownership of live risk management and develop new trading opportunities, collaborating closely with a talented team in a hybrid work environment. Apply now to advance your career in a dynamic and rewarding setting.
Quick overview
Job description
The Firm
A well-capitalised, technology-driven trading firm operating at significant scale across digital assets, derivatives and emerging prediction markets. The firm runs proprietary systematic strategies across multiple asset classes with institutional-grade infrastructure and deep liquidity. The London quant trading desk is a core part of the global operation and is currently expanding its senior trading capability.
The Role
A senior front office quant trading position combining live risk management, systematic strategy research and execution. You will work directly within the firm’s automated trading infrastructure, taking ownership of both the refinement of existing models and the identification and development of new trading opportunities across asset classes and market structures.
Responsibilities
- Monitor and actively manage real-time risk across live books, including local time zone coverage and weekend shift rotation
- Conduct pricing and execution research to facilitate systematic hedging strategies using the firm’s automated trading infrastructure
- Design, implement and backtest new trading signals and execution strategies across spot, derivatives and event-driven markets
- Develop and improve models for market microstructure analysis, signal generation, position sizing and execution optimisation
- Identify structural mispricings, liquidity patterns and inefficiencies across new and existing markets
- Perform rigorous post-trade analysis including PnL attribution, slippage analysis and signal decay diagnostics
- Collaborate directly with quant developers and engineers to translate research into production-grade trading systems
- Contribute to the ongoing development of the firm’s risk framework, including real-time monitoring and drawdown management tools
Requirements
- Master’s or PhD in Mathematics, Statistics, Engineering, Computer Science or a related quantitative discipline from a top-tier institution
- 5+ years of profitable trading experience at a bank, proprietary trading firm or market making desk in any asset class
- Deep understanding of market microstructure, order flow dynamics and execution mechanics
- Hands-on experience developing and deploying systematic trading strategies in live production environments
- Strong proficiency in Python; experience with C++ or low-latency execution environments is a plus
- Solid grounding in statistical modelling, time-series analysis, signal research and backtesting methodology
- Experience with derivatives pricing, options microstructure or volatility modelling is advantageous
- Proven ability to manage live risk independently and make sound, fast decisions under pressure
- Highly analytical, detail-oriented, and intellectually curious with a drive for continuous improvement
What’s on Offer
- Highly competitive base salary with a substantial performance-based compensation component — structured to reward genuine trading edge
- Direct exposure to trading across multiple asset classes — including digital assets, derivatives, equities and prediction markets — within a single, institutionally scaled operation
- A clear and meritocratic career trajectory — senior traders with a track record are given increasing autonomy, capital allocation and leadership responsibility
- A collaborative, high-performance culture built around intellectual rigour, shared knowledge and continuous improvement
- Access to cutting-edge proprietary technology, deep liquidity and a globally connected trading operation
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