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# FX Quantitative Developer

- **Company:** Bonhill Partners
- **Location:** Greater London, UK
- **Salary:** £160,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Algorithmic Trading, Amazon Web Services, Cloud Engineering, Convex Optimization, Distributed Systems, Python (Programming Language), Machine Learning, NumPy, Object-Oriented Software Development, Performance Tuning, Backtesting, SciPy, Concurrency, Pandas, Kubernetes, Low Latency, Docker
- **Published:** August 26, 2026
- **Apply:** https://www.collegerecruiter.com/job/2815050998-fx-quantitative-developer

## About the Role

* Advanced Java development. Expert knowledge of Object-Oriented (OO) design, concurrency, and building high-performance, distributed multi-region systems.
 * Python Proficiency: Expert use of the Python stack (NumPy, SciPy, Pandas) for quantitative data analysis, backtesting, and model prototyping.
 * Numerical Optimisation & ML: Proven experience applying numerical optimisation techniques (e.g., convex optimisation, gradient descent) and Machine Learning models to solve real-world pricing or trading problems.
 * Market Experience: Direct experience in client pricing or equivalent algorithmic trading roles within liquid markets (e.g., FX, ETFs, Equities, or Crypto).
 * Quantitative Foundation: Strong academic background in a numerical field (Mathematics, Physics, or Quantitative Finance)., * Infrastructure: Experience with cloud-native deployments (AWS), Docker, and Kubernetes.
 * Low-Latency: Familiarity with performance tuning (GC optimisation, LMAX Disruptor) is a plus but secondary to distributed systems expertise.
 * Derivatives Knowledge: Understanding of derivatives pricing and risk management across Futures, Forwards, NDFs, and CFDs.

## Description

Bonhill Partners are working closely with a well-established Crypto exchange to hire a Quantitative Java Developer to work on their low latency/HFQ trading platforms.

This is a Hybrid role with a requirement of 2/3 days in office.

Requirements:

 * Advanced Java development. Expert knowledge of Object-Oriented (OO) design, concurrency, and building high-performance, distributed multi-region systems.
 * Python Proficiency: Expert use of the Python stack (NumPy, SciPy, Pandas) for quantitative data analysis, backtesting, and model prototyping.
 * Numerical Optimisation & ML: Proven experience applying numerical optimisation techniques (e.g., convex optimisation, gradient descent) and Machine Learning models to solve real-world pricing or trading problems.
 * Market Experience: Direct experience in client pricing or equivalent algorithmic trading roles within liquid markets (e.g., FX, ETFs, Equities, or Crypto).
 * Quantitative Foundation: Strong academic background in a numerical field (Mathematics, Physics, or Quantitative Finance).

Preferred Qualifications:

 * Infrastructure: Experience with cloud-native deployments (AWS), Docker, and Kubernetes.
 * Low-Latency: Familiarity with performance tuning (GC optimisation, LMAX Disruptor) is a plus but secondary to distributed systems expertise.
 * Derivatives Knowledge: Understanding of derivatives pricing and risk management across Futures, Forwards, NDFs, and CFDs.

The salary available is up to £160k + X2 yearly bonus + benefits.


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