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Data Scientist

Stoke-on-Trent
Posted about 17 hours ago
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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 machine learning solutions and perform statistical analysis to inform strategic, data-driven business decisions and initiatives.

Our Data Analytics team monitors, analyses, and optimises key performance indicators across our range of Sports and Gaming products. We are looking for a talented Data Scientist to join us and help turn complex data into clear, actionable insights.

In this role, you will be instrumental in extracting valuable insights from vast datasets, developing predictive models, and contributing to data-driven decision-making across various business functions.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

Collaborating with stakeholders from areas such as Fraud, Responsible Gambling, Trading and Branding allows us to identify opportunities, solve complex problems, and build robust data solutions. This is an exciting opportunity to apply cutting-edge data science techniques in a fast-paced, high-volume, and globally recognised industry, utilising a modern and powerful tech stack.

This role is eligible for inclusion in the Company’s hybrid work from home policy.

Qualifications

  • Excellent analytical, problem-solving, and critical thinking skills.
  • PhD degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Experience using core machine learning techniques, such as regressions, classification, clustering and deep learning.
  • Strong programming skills in languages such as Python, R, SQL.
  • Familiarity with data science libraries and frameworks.
  • Detailed understanding of data mining, data warehousing, and data visualisation techniques.
  • Knowledge of Artificial Intelligence and its use within data science.
  • Strong communication skills with both technical and non-technical audiences.
  • Knowledge of cloud computing, distributed systems, and big data technologies.

Additional Information

  • Sourcing, cleaning, and validating diverse datasets from various internal and external sources.
  • Conducting in-depth exploratory data analysis to uncover hidden patterns, identify trends, and generate actionable insights that inform strategic business decisions.
  • Developing and deploying robust statistical and machine learning models to address complex business challenges and drive innovative solutions.
  • Designing, implementing, and analysing A/B tests and other controlled experiments to measure the impact of new features, strategies, or models.
  • Contributing to the development and maintenance of scalable data science infrastructure.
  • Partnering closely with stakeholders to understand key business goals and translate them into effective, data-driven solutions.
  • Communicating complex findings and insights to technical and non-technical audiences through visualisations, reports, and presentations.
  • Researching and championing innovative data science techniques, tools, and methodologies.
  • Fostering a culture of continuous learning and innovation within the wider Data Analytics team.

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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.

Workplace Type: Hybrid
Department: Data Distribution and Analytics
Full Time/Part Time: Full Time
Shift Pattern: Days
2nd Office Location: UK - Manchester
Job Type: Standard

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Skills

Machine Learning
Statistical Analysis
Python
R
SQL
Deep Learning
Data Mining
Data Warehousing
Data Visualisation
Artificial Intelligence
Cloud Computing
Distributed Systems
Big Data Technologies
A/B Testing
Exploratory Data Analysis
Predictive Modeling

Location

Stoke-on-Trent, England, United Kingdom

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