Data Scientist

Salary:
Competitive Plus Benefits

Location:

London Store Support Centre and Home, London, EC1M 6HA

Contract type:
Permanent
Business area:
Data & Analytics
Closing date: 22 June 2026
Requisition :

At Sainsbury’s, data sits at the heart of how we operate, innovate and serve our customers. Our Data & Analytics team is building a technically advanced, commercially focused and impactful capability, powering our Next Level Strategy and helping to create a Sainsbury’s powered by industry leading AI algorithms. We use data, technology and advanced analytics to drive better decisions across the business, from forecasting and optimisation to experimentation, personalisation and machine learning.

With one of the richest retail datasets I n the UK and a portfolio spanning Sainsbury’s, Argos, Habitat and Nectar, the opportunity to innovate is huge. Here, you’ll tackle complex challenges at scale, create measurable impact and grow quickly alongside brilliant colleagues. People who thrive with us combine business understanding, technical expertise and curiosity, with a natural instinct for problem‑solving.

Join us and help shape the future of retail through data and AI.

In Customer Data Science (part of the Data Science Hub), we build the systems behind personalised customer decisioning – from customer segmentations to offer optimisation. We impact millions of customers, bringing them value and earning their loyalty.

This team already personalises all of the offers you see in the Nectar app, but now we’re growing in ambition and scale. We aim to personalise everything that matters – offers, online recommendations, digital experiences, communications. And we aim to achieve this using our incredible data asset, our rich customer understanding, and state of the art machine learning and AI.

This role will work in a team dedicated to foundational customer modelling – predicting who you are and what you need. These models serve a wide range of use cases – from personalised marketing to strategic analytics – driving value for the customer and the business.

Solve the hard problems

• Work on the technical development of machine learning solutions and pipelines that will generate value and deliver against our strategic objectives.
• Iterate our modelling and optimisation capabilities, identifying the most appropriate techniques to use for each commercial problem.
• Support the maintenance and optimisation of existing models to adapt to changing needs.

Embody and improve best practice

• Align to best practice across modelling, experimentation, deployment, and model lifecycle management.
• Collaborate with stakeholders to understand and deliver on their needs, and work with engineering teams to source data and deploy robust solutions.

Be an enthusiastic member of our community

• Bring new ideas for future approaches, including state of the art techniques where appropriate.
• Understand how our business really works, including by supporting our stores during peak trading periods.
• Actively contribute to our vibrant Data and Analytics community of over 800 colleagues, providing a view on new techniques and approaches that can drive positive change in wider teams.

We’re looking for a highly motivated self‑starter – someone who fixes problems and creates value without micromanagement. You need to thrive in a challenging role, and know how to balance our need for technical rigour against our need to deliver commercial and customer value.

• Experience in Data Science roles, with evidence of solving complex problems end‑to‑end.
• A record of building systems which run in production, and an understanding of the value these generated.
• An ability to understand commercial reality as well as technical rigour.
• A strong ability to communicate ideas to audiences of varying technical background and seniority.

• Strong grounding in statistical modelling and machine learning, such as predictive modelling at scale, unsupervised learning, causal inference, experimentation, optimisation and decisioning.
• Strong understanding of the “how” behind the algorithm; ability to select the right…