Research Data Scientist

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.

Joining our team, you’ll work with world class and passionate people to apply machine learning and statistical techniques to business problems. You’ll contribute to the research and implementation of new approaches to address complex problems and perform data analysis and model validation. You’ll have the opportunity to present results to a variety of internal stakeholders and will apply these techniques and algorithms to create dunnhumby science solutions that can be delivered across our clients and engineered into science modules.

This role will 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. It will also involve product attribute generation and exploring applications of generative AI to support product development and insights.

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:

• 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.