Senior Quant Developer - Java - Digital Assets

Excellent opportunity opens for a Senior Quant Developer to join a Global Crypto Trading Firm. Sitting between Quantitative Research, Trading and production engineering, you will build and enhance quantitative pricing technology. You will take ownership of the mathematical design and Java implementation of OTC client-pricing, liquidity and hedging models.

The role

• Design and implement quantitative pricing models for institutional OTC trading
• Build high-performance production services using modern Java, including Java 21 or 22
• Develop client-specific pricing, spreads, skews and liquidity models
• Analyse client flow, execution behaviour, toxicity and price decay
• Develop pricing and hedging optimisation algorithms
• Translate quantitative research and mathematical models into robust production code
• Work closely with Quant Researchers and Traders on model design, testing and calibration
• Improve the performance, resilience and scalability of distributed pricing systems
• Use Python for quantitative analysis, model prototyping, data analysis and backtesting

• Strong commercial experience as a Quant Developer
• Advanced Java development experience, ideally using Java 21 or 22
• Experience implementing pricing, trading, hedging or optimisation models
• Direct experience of client pricing, market making or algorithmic trading
• Experience within crypto or another liquid electronic market such as FX, equities, ETFs or listed derivatives
• Knowledge of OTC markets and institutional client pricing
• Strong quantitative and mathematical foundations
• Degree-level background in Mathematics, Physics, Computer Science, Engineering, Quantitative Finance or another highly numerical discipline
• Strong understanding of object-oriented design, concurrency and distributed systems
• Ability to turn mathematical concepts and research models into reliable production software

Particularly relevant experience

• Digital assets or cryptocurrency markets
• Electronic market making
• OTC spot, forwards, futures, NDFs, CFDs or options
• Pricing skews and spread optimisation
• Client-flow analysis and toxicity modelling
• Automated hedging and inventory optimisation
• Numerical optimisation or machine learning applied to pricing or trading
• Python quantitative libraries such as NumPy, SciPy and Pandas
• Low-latency or high-throughput trading systems