Quantitative Analyst

We build bespoke statistical models and probabilistic frameworks that predict horse racing outcomes and trade them optimally. What to back, when, and how much.

We're hiring a researcher to join our quant team. Your work will have a direct, measurable impact on whether we make money. You'll have real ownership over what you build, how you build it, and whether it actually works.

If you've made a real impact on a hard technical problem and want more of that - or you've outgrown the technical depth of your current role and want somewhere you can solve problems through science, with real stakes - we'd love to hear from you.

You'll build and improve our quantitative models. We work mostly with custom developed state space models, probabilistic frameworks and neural architectures, but we're not tied to that - if something else works better, we'll use it. Modelling is only part of it. You'll spend just as much time with the data: understanding its traps, and what we haven't made use of yet.

You'll own your modelling choices, and we'll expect you to be able to explain them clearly. Equally, we'll challenge your thinking and we'd want you to do the same to ours.

We're a small team building something ambitious. As you develop an understanding of the product and domain, you will be expected to shape the direction of the research and the business decisions that follow from it. We're looking for someone who wants to identify problems, shape solutions and push through to outcomes, not just deliver pre-defined work.

Requirements

You've made a tangible difference on a difficult problem in a previous role. You can talk us through what you did, why it was hard, and what changed because of your work.

You understand statistical models at an implementation level. Not just using libraries - you understand what's happening underneath, you tailor your solutions to the problem at hand and you've formed your own views on what works and when. You could probably do a PhD in a technical field, but decided to go to industry instead.

You're comfortable with ambiguity. When there's no clear path forward, you make progress - and you know when to push through on your own versus when to bring others in.

You work at a good pace. You'd rather get something out, see if it works, and learn from it than spend weeks on the perfect approach. You have also developed a research taste - you tend to ask the right questions before diving in.

You've built something end-to-end that was genuinely yours - and you pushed it to be as good as it could be, not just technically interesting or good enough.

Good python knowledge is required. We'll teach you the Horse Racing domain knowledge.

Benefits