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 will shape the future of AI across the organisation. You’ll work at the intersection of cutting-edge research and real-world commercial impact, turning new ideas into scalable capabilities that influence products, platforms, and inform long term strategy. You will have a chance to influence decisions across data science, engineering, and product. You’ll partner with senior leaders to define priorities, guide innovation, and ensure we’re investing in the right AI capabilities for the future.

We’re looking for a Research Data Science Manager who expects more from their career. You will lead and grow a high‑calibre team advancing frontier AI, including generative, multimodal, and representation learning, while translating breakthrough research into robust capabilities for dunnhumby’s products.

You will shape the research agenda on transformer‑based approaches to retail problems, drive rigorous experimentation and evaluation, and turn concepts into robust prototypes in close partnership with Product, Engineering, Data Science and Platform teams. You will establish best‑practice methodologies, reusable libraries and internal frameworks that make scientific development faster, safer and easier to adopt.

You will develop talent, raise methodological quality, and guide ML adoption across domains. You will also strengthen external research partnerships so that new ideas move effectively from exploration into reliable solutions that deliver measurable client impact.

Key Responsibilities

Lead and grow a team of Research Data Scientists and ML Engineers focused on:
- Forward-looking research on generative AI, multimodal learning, and representation learning.
- The design, experimentation, and evaluation of transformer-based models on retail-based challenges.
- Emerging AI/ML techniques with high potential for retail and consumer analytics, shaping conceptual prototypes and feasibility assessments.
- Developing research-grade prototypes and collaborating with engineers to translate them into scalable, production-ready solutions.
- Documenting best practices and contributing to reusable assets, libraries, and internal frameworks.
Partner with Data Science, Product, Engineering and Platform teams to define and deliver frontier aligned AI research roadmaps.
Develop team members, build technical capability, and foster a culture of excellence and collaboration.
Drive internal thought leadership by defining standards, sharing knowledge, and advising product, engineering, and data science teams on ML adoption and best practices.
Drive measurable improvements in research methodologies, quality and adoption within Data Science solutions across domains.
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.
Partner closely with internal teams to ensure research pathways are aligned with available tooling and future platform strategy.

What you’ll need to succeed

Experience leading ambiguous research projects and shaping them into structured investigations or prototypes including design, integration, and collaboration efforts cross functionally.
Strong communication and stakeholder management skills, capable of explaining complex ideas to technical and non-technical audiences.
Collaborative approach to working with Data Scientists, ML engineers, product managers, academic partners, and leadership stakeholders.
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.
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).

What we expect from you

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.

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)

Research Data Science Manager

TLDR

Benefits