Operations Data Scientist

Operations Data Scientist

Milton Keynes (Hybrid, Tuesday office day)

At Domino's, we're using data to make smarter decisions across one of the UK's most recognised brands. As our Operations Data Scientist, you'll help transform how we understand and improve performance across our stores, turning complex data into practical solutions that make a real difference.

This is an exciting opportunity to join a growing Data Science team that's focused on innovation, advanced analytics and the responsible application of AI. Working closely with operational leaders across the business, you'll build solutions that help answer challenging questions, uncover opportunities and improve decision-making at scale.

If you're someone who enjoys getting beneath the surface of a problem, challenging assumptions and using data to drive meaningful change, we'd love to hear from you.

What You'll Bring

We're looking for someone with strong technical expertise, commercial curiosity and a proactive approach to solving problems.

You'll have:

• Professional experience in a Data Scientist role, applying machine learning, statistical modelling or advanced analytics to real business challenges
• Strong Python and SQL skills, with experience building and evaluating models
• A degree in Data Science, Mathematics, Statistics, Computer Science or another quantitative discipline
• Experience working through the full data science lifecycle, from problem definition and exploratory analysis through to implementation and monitoring
• Strong analytical thinking and the ability to identify the story behind the data
• Confidence communicating findings to both technical and non-technical audiences
• The ability to work independently, challenge assumptions constructively and influence decision-making through evidence

It would be beneficial if you also have:

• Experience with Databricks, PySpark, Azure or similar cloud-based data environments
• Experience within operational, retail, logistics or customer-focused businesses
• Exposure to AI solutions or emerging machine learning technologies

Most importantly, you'll be naturally curious, tenacious when tackling difficult problems and motivated by finding better ways of doing things.

What You'll Be Doing

As our Operations Data Scientist, you'll partner with stakeholders across Operations to identify opportunities where data science can create measurable business value.

Your responsibilities will include:

• Applying machine learning, AI and advanced analytics techniques to operational challenges
• Developing predictive models, forecasting solutions and analytical tools using Python and SQL
• Investigating business performance to uncover key drivers, risks and opportunities
• Translating complex analysis into clear, actionable recommendations
• Maintaining and enhancing Power BI reporting and dashboards used across Operations
• Collaborating with Data, Technology and Operations teams to deploy and monitor solutions
• Contributing to the Data Science roadmap and helping shape future analytical capabilities
• Exploring innovative approaches and AI-powered solutions that improve operational performance

This role offers the opportunity to work on new and emerging projects, helping Domino's continue to evolve the way we use data across the business.

How We Will Support You

At Domino's, you'll have the opportunity to develop your skills while working alongside experienced data professionals and business leaders.

You'll benefit from:

• Exposure to advanced analytics, machine learning and AI initiatives
• The opportunity to work on high-impact projects with visible business outcomes
• Support from a collaborative and knowledgeable Data Science team
• The chance to influence decisions across a nationwide operation
• A hybrid working environment that balances flexibility with meaningful collaboration
• Ongoing opportunities to learn, grow and broaden your technical and commercial expertise

We're looking for people who bring fresh thinking, challenge the status quo and help us continually improve how we work.