Research Data Scientist

Salary: £48,000 - 88,000 per year

Requirements:

• We require a Masters degree or equivalent in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology, or a related field.
• We require experience with machine learning techniques such as regularised regression, clustering, or tree-based ensembles, and the ability to implement them through libraries.
• We require experience with programming, ideally Python, and the ability to quickly pick up handling large data volumes with modern data processing tools, such as Hadoop, Spark, or SQL.
• We require experience with, or the ability to quickly learn, open-source software including machine learning packages such as Pandas and scikit-learn, along with data visualisation technologies.
• We require a willingness to present work to both technical and non-technical audiences and to contribute to the wider data science community.
• A PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology, or a related field is a plus.
• Experience in the retail sector is a plus.

Responsibilities:

• We create new science-based solutions that can be captured as science modules and applied across clients, with support from senior team members.
• We pick up new machine learning approaches, such as regularised regression, clustering, tree-based ensembles, graph-based approaches, natural language processing, and neural network techniques, and apply them to client data.
• We perform exploratory data analysis to characterise and visualise datasets.
• We extend and develop programming skills in languages such as Python and Spark to develop efficient science code for science modules.
• We help identify new opportunities within the Data Science space for future dunnhumby solutions.
• We implement advice from colleagues to resolve challenges.
• We follow quality assurance processes, ways of working, and coding standards.
• We ensure smooth running of projects, working with senior team members for direction.
• We build strong relationships within the team and with internal stakeholders, ensuring clear and effective communication.
• We contribute to research and implementation of new approaches to address complex problems and perform data analysis and model validation.
• We present results to a variety of internal stakeholders.
• We apply techniques and algorithms to create science solutions that can be delivered across clients and engineered into science modules.
• We focus on insight automation and product assortment, leveraging data science to identify emerging and evolving product needs, optimise product mix, and predict the impact of potential changes.
• We also work on product attribute generation and explore applications of generative AI to support product development and insights.

Technologies:

• AI
• Hadoop
• Support
• Machine Learning
• Network
• Python
• SQL
• Spark
• pandas

More:

We are dunnhumby, the global leader in Customer Data Science, partnering with 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. We employ nearly 2,500 experts across Europe, Asia, Africa, and the Americas, and work for transformative brands such as Tesco, Coca-Cola, Nestlé, Unilever, and Metro. We offer a comprehensive rewards package, flexible working hours, your birthday off, investment in cutting-edge technology, and a culture that values inclusion, flexible working, and opportunities to experiment and learn.

last updated 36 week of 2026