Sports Tech Data Scientist: Predictive Modeling & Growth

Sportradar; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Hybrid work model

Social events & teambuilding

Career development framework

Women in Tech & Pride groups

Employee Assistance Programme

Calm and Reulay app

Job summary

Sportradar, a world‑leading sports technology company, seeks a data scientist/quant to build predictive models for pre‑match and in‑play betting markets. You will clean, visualize and analyze data and implement models in Java, while publishing and maintaining libraries.

Requires a Master’s in a quantitative field, strong R/Python, and excellent communication in English. Office‑first with hybrid work and opportunities for career development and collaboration globally.

Qualifications

• Master’s degree or equivalent in Data Science, Statistics, Mathematics, Software Engineering or closely related field.
• Experienced in predictive modelling with data analysis and modelling techniques like GLMs, Time-Series, Bayesian Statistics, MCMC, neural networks.
• Very strong skills in R or Python.
• Advanced coding and analytical skills. English fluency.

Responsibilities

• Learn how predictive models look like in a betting context and build models on your own.
• Support the team in maintaining the codebase.
• Research new methods for future applications.

Skills

Predictive modelling

R/Python

Time-series

GLMs & Bayesian

English fluency

Education

Master’s degree in data science

Tools

Gitlab

Jira/Confluence

SQL

Java

Job description

Sportradar, a world‑leading sports technology company, seeks a data scientist/quant to build predictive models for pre‑match and in‑play betting markets. You will clean, visualize and analyze data and implement models in Java, while publishing and maintaining libraries.

Requires a Master’s in a quantitative field, strong R/Python, and excellent communication in English. Office‑first with hybrid work and opportunities for career development and collaboration globally.