A systematic futures researcher to turn a well-built CME trading platform into a reliably profitable trading business. The engineering is done: around 30 microseconds of internal latency and a first strategy already taken live. What the team is missing is someone who has designed strategies inside a trading firm, run them live and can explain what worked, what did not and why.
The work
The research and technology company inside a privately funded investment group has built a live trading platform from scratch in under two years. It trades NQ futures on CME today, with ES, gold and oil next once the research supports them. Its first live strategy performed well in the conditions it was designed for and showed its limits when the market changed. That lesson is why this hire exists. We are looking for trading experience, someone who knows which model structures, indicators and signals hold up in live markets.
What you'll own
You are the bridge between the platform and a profitable trading business. The first goal is trading that reliably makes money on average within six months, with drawdowns understood and accepted, then scaling the capital traded as performance and risk controls prove out.
- Find and prove signals that work in live markets, not only in backtests
- Specify a full order book simulator with the engineering team, then use it as the gate for every strategy release
- Set the rules for scaling capital: risk limits, drawdown thresholds and kill-switch criteria
- Take day-to-day trading decisions off the Head of AI within agreed limits, and report on them
- Raise the team's trading knowledge and, in time, help hire and lead the next trading hire
What you'll need
The language is your choice. Python, C++, OCaml or anything else: what matters is that you wrote and tested your own strategies. The platform has C++ and Python interfaces, so C++ is a plus, not a requirement. Researchers from OCaml and functional-programming trading firms are as welcome as more conventional Python and C++ backgrounds. You should be able to walk through one strategy in detail, including a failure you were responsible for and how you resolved it.
- Systematic strategies you designed, implemented and tested yourself in code, ideally on futures inside a trading firm, with some run live
- Real futures experience, ideally CME: contract specifications, margin, notional exposure, rolls and P&L
- Strong statistics, and the judgement to tell a real signal from noise
- A thorough understanding of why backtests flatter strategies: look-ahead bias, data leakage, overfitting, survivorship bias, unrealistic fills and regime change
- Comfort owning your work from idea to live in a team of around ten, without close supervision
The package
- Base up to £150,000 depending on experience
- plus a discretionary profit-based bonus shared by everyone in the group. Individual awards range from nothing to 100% of base and are paid over three years
- 31 days' holiday plus bank holidays and your birthday
- healthcare
- pension
Hybrid and London-based, so you need to live in or within easy reach of London. The dealing policy lets you keep your own personal and systematic trading without trade-by-trade pre-approval, provided company information and IP stay separate.
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Quantitative Researcher, Systematic Futures employer: Ocean Red
As a Senior Software Engineer at our London office, you'll be part of a dynamic team that values innovation and collaboration, working on technology that powers global financial markets. We offer a supportive work culture where your ideas are valued, and you have the opportunity to influence software development practices while mentoring less experienced developers. With flexible working arrangements and a focus on employee growth, this role provides a unique chance to make a significant impact in a high-stakes environment.
