Quantitative Developer (Systematic Options/Python) – Tier 1 Hedge Fund – Excellent Compensation[...]
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 decisionmakers 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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