Quantitative Developer (Systematic Options/Python) – Tier 1 Hedge Fund – Excellent Compensation & Benefits

Our client, a tech-first, rapidly expanding hedge fund based in London seek a python expert to join their systematic options as a Quant Developer and work along side one of the firms highest performing portfolio managers.

As the principal python quant dev sat alongside the Portfolio Manager and researcher, you will play a critical role in supporting and developing the technology platform behind a live systematic trading strategy. The role combines production engineering, quantitative tooling, trading infrastructure, and close collaboration with the investment team, offering exceptional exposure to both technology and the investment process.

This is a highly visible position within a lean team where strong engineers can have a direct impact on research, portfolio construction, and live trading outcomes. The environment offers significant ownership, broad technical challenges, and the opportunity to work on problems that directly influence investment performance.

What You Will Be Doing

• Maintaining and enhancing the research and production codebase supporting a live systematic options strategy
• Monitoring, troubleshooting, and improving the operation of approximately 200 live transforms and related analytics
• Working directly with the PM and researcher to implement quantitative research ideas into robust production systems
• Building tools and dashboards providing visibility into positions, signals, risk, and overall system health
• Improving platform reliability, observability, testing, documentation, and automation across the development lifecycle
• Debugging complex data pipelines, signal implementations, and production workflows
• Leveraging AI-assisted development tools and automated workflows to accelerate delivery and reduce operational burden
• Identifying recurring operational challenges and implementing scalable long-term solutions
• Contributing to the continued evolution of the team's research and trading infrastructure

What They Are Looking For

• Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative discipline
• 2+ years of software development experience within a trading, quantitative, or financial technology environment
• Strong Python development skills and experience building reliable production-quality systems
• Strong interest in quantitative investing and systematic strategies
• Experience supporting production or production-adjacent systems
• Strong understanding of software engineering best practices including testing, version control, code review, monitoring, and modular design
• Strong debugging and problem-solving capabilities across complex data and technology workflows
• Comfortable operating in a highly collaborative front-office environment working directly with PMs and researchers
• Strong ownership mentality with the ability to balance engineering excellence with the pace required in an investment team

Nice To Have

• Experience with options, derivatives, volatility strategies, or risk analytics
• Experience with signal pipelines, research platforms, backtesting systems, or live trading infrastructure
• Experience building monitoring tools, dashboards, or operational analytics platforms
• Familiarity with distributed computing, workflow orchestration, or large-scale data pipelines
• Experience using LLMs, coding agents, or AI tools to automate software development, testing, documentation, or data analysis
• Experience working with alternative or unstructured data sources

The ideal candidate will combine strong software engineering capability with a genuine interest in systematic investing, operational excellence, and the desire to work directly alongside investment decision-makers within a world‑class hedge fund environment.

The firm offers excellent compensation and benefits, direct exposure to a live investment strategy, significant ownership from day one, and the opportunity to help shape the next generation of AI‑enabled quantitative research and trading infrastructure.

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