Research Data Scientist

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.

We’re looking for a talented Research Data Scientist who expects more from their career. It’s a chance to extend and improve dunnhumby’s world class science capabilities. It’s an opportunity to work with a market-leading business to explore new opportunities for us and influence global retailers and suppliers.

What You'll Be Doing

• Create new science-based solutions that can be captured as science modules and applied across clients, with support from senior team members.
• Pick up new machine learning approaches, such as regularised regression, clustering or tree-based ensembles, graph-based approaches, natural language processing and neural network techniques and apply them on client data.
• Perform exploratory data analysis to characterise and visualise datasets.
• Extend and develop programming skills, in languages such as Python and Spark, to develop efficient science code for science modules.
• Help identify new opportunities within the Data Science space for future dunnhumby solutions.
• Implement advice from colleagues to resolve challenges.
• Follow Quality Assurance processes, ways of working and meet coding standards.
• Ensure smooth running of your projects, working with senior team members for direction.
• Build strong relationships within the team and with internal stakeholders, ensuring clear and effective communication.

Who You’ll Get To Work With

• Within dunnhumby you’ll primarily work with
• Applied and Research Data Scientist teams
• Data Science Engineering teams
• Product and Client teams where required

What You’ll Need

• Master’s degree or equivalent in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field.
• Experience with machine learning techniques such as regularised regression, clustering or tree-based ensembles, and the ability to implement them through libraries.
• Experience with programming, ideally Python, and the ability to quickly pick up handling large data volumes with modern data processing tools, e.g. by using Hadoop / Spark / SQL.
• Experience with or ability to quickly learn open‑source software including machine learning packages, such as Pandas and scikit‑learn, along with data visualisation technologies.
• A willingness to present your work to both technical and non‑technical audience and to contribute to the wider data science community.

A Plus If You Also Have

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field.
• Experience in retail sector.

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. Plus, a degree of personal flexibility you might not expect. 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, while enjoying 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.

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.