Job Description

The role is available as hybrid with time in the office in London or Leeds.

Quantitative Analyst - Sports Focus

Are you fascinated by the intersection of data, uncertainty, and sport? Our client is looking for curious and driven individuals to join their growing analytics team, where they tackle some of the toughest challenges in the world of sports prediction. Whether you're a seasoned Quant or someone from a different industry with a passion for statistics and sport, this could be your opportunity to make a real impact. You'll contribute directly to the design, development, and deployment of models that underpin key business decisions--bringing together your statistical intuition, modelling skills, and an interest in the unpredictable world of sport.

What You'll Be Doing

You'll be engaged in the design and refinement of cutting-edge statistical models that help us interpret and forecast sporting events. Drawing from a wide array of data sources--both traditional and unconventional--you'll help uncover insights that drive key decisions. This role is about more than just the numbers; it's about creative problem solving, exploring new methods, and pushing boundaries in a field where uncertainty reigns.

Develop sophisticated probabilistic and statistical models

, including Bayesian approaches, to better understand and forecast sporting events

Own the research process

--from hypothesis generation to data wrangling to model validation

Work with rich and diverse datasets

, including match stats, player tracking, and market signals

Contribute to production codebases

, ensuring your work is robust, reproducible, and scalable

Continuously improve model performance

, calibration, and feature design using both technical experimentation and domain insight

About You

You don't need a background in sports--but you do need an analytical mind and a strong desire to dig into complex data. You should be:



Comfortable working with probabilities and uncertainty Thoughtful and methodical in how you approach problems Willing to question assumptions and explore alternative viewpoints Enthusiastic about working collaboratively with colleagues across different areas of the business

Essentials

Experience in a data science, quant, or statistical modelling role Strong coding ability in Python and fluency in its data science ecosystem (e.g. numpy, pandas, matplotlib, seaborn) Practical knowledge of probability theory and statistical inference, particularly Bayesian methods Ability to independently manage and structure a modelling project--from early-stage analysis to deployment Experience working with real-world datasets: cleaning, transforming, visualising, and modelling Clear communicator who can articulate complex findings to technical and non-technical audiences

Nice to Have

Experience with probabilistic programming tools (e.g. PyMC, Stan, NumPyro) Familiarity with version control (git), testing, and production-quality code practices Exposure to sports analytics, betting markets, or similar high-noise, high-variance environments Background in working with time series or structured data in complex domains

What You'll Gain

High-impact Work

- Your models will directly influence business strategy and performance

Autonomy and Growth

- They'll trust you to lead projects, make key decisions, and deepen your technical expertise

Access to Experts

- You'll collaborate with a team of experienced quants, data engineers, and domain specialists

A Supportive Culture

- Flat structure, knowledge-sharing, and a focus on continual improvement

Room to Explore

- Encouragement to try new techniques, learn new tools, and stay up to date with the latest in probabilistic modelling and sports analytics

A Note on Backgrounds

You don't need to have worked in sport or betting before--what matters is your ability to model uncertainty, think critically about data, and write clean, functional code. We welcome applicants from academia, finance, research, tech, or any analytical field. If you've got a solid track record of using stats and code to solve difficult problems--and you're intrigued by sport as a domain--we'd love to chat.



The role is available as hybrid with time in the office in London or Leeds.