dunnhumby is the global leader in Customer Data Science, partnering with the world’s most ambitious retailers and brands to put the customer at the heart of every decision. We combine deep insight, advanced technology, and close collaboration to help our clients grow, innovate, and deliver measurable value for their customers.

dunnhumby employs nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, Nestlé, Unilever and Metro.

Joining the AI Strategy, Research & Enablement team, you’ll help shape the future of AI across the organisation. Working at the intersection of cutting-edge research and real-world commercial application, you’ll turn innovative ideas into scalable capabilities that influence products, platforms, and long-term strategy. You’ll collaborate with senior leaders and contribute to decision-making across data science, engineering, and product, helping to prioritise and advance the right AI investments for the future.

We’re looking for a Senior Research Data Scientist to play a key role in developing dunnhumby’s next-generation models across a range of strategic AI initiatives. As part of this newly formed team, you’ll focus on advanced modelling, long-term capability building, and cross-industry collaboration. You’ll design new approaches, build and test prototypes, support engineering teams with productionisation, and contribute to partnerships with academia and external research organisations.

What you’ll be doing:

Drive the design, experimentation, and evaluation of transformer-based models on retail based challenges.
Explore innovative architectures (e.g., sequence-to-sequence models, causal transformers, hybrid retrieval + transformer approaches) to deliver step-change improvements in personalisation, recommendations, and forecasting.

Develop research-grade prototypes and collaborate with engineers to translate them into scalable, production-ready solutions.

Conduct forward-looking research on generative AI, multimodal learning, and representation learning.

Identify emerging AI/ML techniques with high potential for retail and consumer analytics, shaping conceptual prototypes and feasibility assessments.

Drive internal thought leadership by defining standards, sharing knowledge, and advising product, engineering, and data science teams on ML adoption and best practices.

Work with leading academic groups and private-sector research partners to co-develop new modelling approaches, run joint experiments, or explore cutting-edge AI applications.

Mentor other data scientists and contribute to growing organisational capability in deep learning and advanced ML.

Partner closely with internal teams to ensure research pathways are aligned with available tooling and future platform strategy.

Document best practices and contribute to reusable assets, libraries, and internal frameworks.

What we expect from you:

Expertise in transformer architectures (e.g., BERT, GPT, T5, Time‑Series Transformers).
Strong hands-on experience with modern deep learning frameworks (PyTorch preferred).
Solid grounding in machine learning fundamentals and statistical modelling.
Familiarity with distributed training and GPU acceleration.
A track record of delivering impactful models in production or research settings.
Ability to take ambiguous research ideas and shape them into structured investigations or prototypes.
Curiosity and a learning mindset — tracking state-of-the-art advancements and evaluating their relevance.
Strong data manipulation and engineering skills (e.g., PySpark, SQL, cloud-based data tooling).
Strong communication skills, capable of explaining complex ideas to technical and non-technical audiences.

Collaborative approach to working with ML engineers, product managers, academic partners, and leadership stakeholders.

A passion for turning cutting‑edge modelling ideas into practical business impact.

A mindset that blends scientific curiosity with real-world pragmatism.

Enthusiasm for shaping the next generation of AI capabilities at dunnhumby, both through hands-on modelling and strategic influence.

Nice to have

Experience in retail, CPG, recommendations, or customer behaviour modelling.
Engagement with academic research (publications, workshops, industry collaborations).
Familiarity with vector databases, embeddings, and retrieval techniques.
Experience Working on large datasets (efficient loading, batching, and streaming) and related tooling (PySpark preferred).

What you can expect from us

We won’t just meet your expectations. We’ll defy them. So you’ll enjoy the comprehensive rewards package you’d expect from a leading technology company. But also, a degree of personal flexibility you might not expect. Plus, thoughtful perks, like flexible working hours and your birthday off.

You’ll also benefit from an investment in cutting-edge technology that reflects our global ambition. But with a nimble, small-business feel that gives you the freedom to play, experiment and learn.

And we don’t just talk about diversity and inclusion. We live it every day – with thriving networks including dh Gender Equality Network, dh Proud, dh Family, dh One, dh Enabled and dh Thrive as the living proof. We want everyone to have the opportunity to shine and perform at your best throughout our recruitment process. Please let us know how we can make this process work best for you.

Our approach to Flexible Working

At dunnhumby, we value and respect difference and are committed to building an inclusive culture by creating an environment where you can balance a successful career with your commitments and interests outside of work.

We believe that you will do your best at work if you have a work / life balance. Some roles lend themselves to flexible options more than others, so if this is important to you please raise this with your recruiter, as we are open to discussing agile working opportunities during the hiring process.

For further information about how we collect and use your personal information please see our Privacy Notice which can be found (here)

Senior Research Data Scientist

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