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Data Scientist, Sports

Posted Yesterday
Be an Early Applicant
Hybrid
Manchester, Greater Manchester, England
Mid level
Hybrid
Manchester, Greater Manchester, England
Mid level
The Data Scientist will develop probabilistic models for real-time betting, utilizing large datasets, statistical techniques, and machine learning to optimize sports betting products.
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Company Description

We’re one of the world’s leading online gambling companies, revolutionising the industry since 2000. Founded by Denise Coates CBE, we now employ over 10,000 people and serve over 120 million customers in 26 languages.

We empower our employees to push boundaries and explore new ideas, cultivating a culture that celebrates and rewards creativity. This offers employees a wealth of growth opportunities, giving them the opportunity to make a real impact in the world of online gambling. As a forward-thinking company, we’re breaking new ground in software innovation too, redefining what’s possible for our global worldwide.

Our focus on In-Play betting has solidified our market-leading position, featuring more than 1.38 million In-Play sporting events a year. With over 750 concurrent sporting fixtures at peak and more live sports streamed than anyone else in Europe (750,000), we handle over 6 million HTTP requests daily and process more than 1.5 million bets per hour at peak.

Job Description

As a Data Scientist, you will develop probabilistic models that power real-time betting markets.

The Quantitative Analysis department harnesses data-driven insights to enhance our betting products and services. The team is responsible for designing, developing, and maintaining sophisticated mathematical models to provide accurate pricing across our sports betting products.

In this role, you will work with extensive datasets to develop models that determine odds and power in-play betting decisions. Our fast-paced, delivery-focused environment offers significant opportunities for technical growth and innovation.

This role is eligible for inclusion in the Company's hybrid working policy.

Qualifications

  • Bachelor’s degree in Mathematics, Data Science, Computer Science, or a related quantitative field.
  • Keen interest in a wide range of sports and/or the online gambling industry.
  • Demonstrable experience building predictive models from data.
  • Expertise in statistical analysis and probability theory applied to real-world problems.
  • Strong Python/R skills with experience in ML frameworks, such as scikit-learn, TensorFlow, or PyTorch.
  • Ability to optimise models for both accuracy and computational efficiency.
  • Experience handling and analysing large datasets.
  • Familiarity with cloud computing environments.

Additional Information

  • Conducting in-depth analysis of large datasets to extract insights and inform decision-making in sports betting.
  • Utilising statistical techniques and machine learning algorithms to develop predictive models and algorithms for sports betting.
  • Devising innovative solutions for unstructured problems.
  • Assessing existing models and algorithms to identify areas for improvement.
  • Identifying and resolving data quality issues or bugs affecting models or analysis.
  • Performing rigorous statistical validation of models against historical and live data.
  • Collaborating with trading teams to incorporate domain expertise into mathematical models.
  • Optimising model performance for both accuracy and computational efficiency.
  • Researching novel approaches from academic literature and industry developments.
  • Identifying and defining new opportunities for data-driven insights.

By applying to us you are agreeing to share your Personal Data in accordance with our Recruitment Privacy Notice - https://www.bet365careers.com/privacy-policy

At bet365, we're committed to creating an environment where everyone feels welcome, respected and valued. Where all individuals can grow and develop, regardless of their background. We're Never Ordinary, and we're always striving to be better. If you need any adjustments or accommodations to the recruitment process, at either application or interview, please don’t hesitate to reach out.

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