Research Data Scientist

dunnhumby is the global leader in Customer Data Science, empowering businesses everywhere to compete and thrive in the modern data-driven economy. We always put the Customer First. Our mission is to enable businesses to grow and reimagine themselves by becoming advocates and champions for their Customers. With deep heritage and expertise in retail, one of the world’s most competitive markets, dunnhumby today enables businesses across industries to be Customer First. 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, Meijer, Procter & Gamble and Metro.

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. You 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 how we ensure better decisions are made as part of category management, ensuring the right product is in the hands of the customer, by enhancing our data-led understanding of products and categories, optimising across space and range and increasing automation of category decision making.

• Apply machine learning and statistical techniques to business problems.
• Contribute to the research and implementation of new approaches and perform data analysis and model validation.
• Present results to internal stakeholders.
• Develop dunnhumby science solutions that can be delivered across clients and engineered into science modules.
• Focus on improving decision making in category management by enhancing data-led understanding of products and categories, optimizing across space and range, and increasing automation of category decisions.

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field.
• 3-5 years of experience.
• 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 handle large data volumes with modern data processing tools (e.g., Hadoop / Spark / SQL).
• Experience with or ability to learn open-source software including machine learning packages (e.g., Pandas, scikit-learn) and data visualization technologies.
• Experience in the retail sector would be an added advantage.

We’ll defy expectations with a comprehensive rewards package, flexible working options, and thoughtful perks such as flexible working hours and your birthday off. You’ll benefit from investment in cutting-edge technology and a nimble, small-business feel that gives you freedom to play, experiment and learn.

We value and respect difference and are committed to building an inclusive culture where you can balance a successful career with your commitments outside of work. Some roles lend themselves to flexible options more than others, so please discuss agile working opportunities with your recruiter during the hiring process.

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At dunnhumby, we utilise diversity of thought as our competitive edge. We are proud of our diversity and committed to making dunnhumby an even more inclusive place to work. Our diversity and inclusion work is designed to cultivate a culture of belonging where everyone feels safe to bring their whole self to work. We have a full D&I strategy and five employee-led networks to support colleagues in gender, sexual orientation, multiculturalism, mental health and wellbeing, and family.