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# Data Scientist - Sports Betting

- **Company:** The Block
- **Location:** Watford, UK (Remote available)
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Big Data, Python (Programming Language), Machine Learning, SQL Databases, Information Technology
- **Published:** July 25, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/x/42047295/

## About the Role

What We're Looking ForStrong academic background in Mathematics, Statistics, Computer Science, Physics, Engineering or a related quantitative discipline.Commercial experience as a Data Scientist, Quantitative Analyst or similar analytical role.Advanced Python skills and experience working with large datasets.Strong understanding of machine learning, statistical modelling and predictive analytics.Experience with SQL and modern data analysis tools.Excellent problem-solving ability with exceptional attention to detail.A genuine passion for sport and an interest in sports betting markets.Naturally curious, highly analytical and motivated by solving complex problems.Strong communication skills with the confidence to influence stakeholders.Leadership potential and the ambition to grow with a rapidly scaling business.
Nice to HaveExperience within sports betting, gaming, trading or financial markets.Knowledge of time series analysis, optimisation or probabilistic modelling.Experience working in fast-paced, data-driven environments.

## Description

What You'll Be DoingBuild and enhance predictive models using statistical and machine learning techniques.Analyse large, complex datasets to identify trends, patterns and betting opportunities.Develop data-driven insights to improve betting performance and profitability.Work closely with engineering and trading teams to implement scalable analytical solutions.Optimise existing models through continual testing, validation and refinement.Research new approaches and technologies to maintain a competitive advantage.Help shape the future direction of the data science function as the business grows.Mentor and support junior team members over time.


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