Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
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. With nearly 2,500 experts worldwide, we work with transformative, iconic brands such as Tesco, Coca-Cola, Nestlé, Unilever, and Metro.

We are seeking a dynamic Applied Data Science Manager to join the Tesco UK&I ADS team. Your goal will be to use science and data to create new commercially valuable solutions for Consumer Packaged Goods (CPGs). This exciting opportunity involves working closely with propositions teams to turn ideas into Minimum Viable Products (MVPs) and scalable solutions.

Key responsibilities include managing and leading a team of Data Scientists and Market Researchers, ensuring quality and timeliness of deliverables, and fostering a culture of quality, collaboration, and experimentation. You will shape and define the scope of new propositions in collaboration with propositions and client teams, translating commercial ideas into solution designs that leverage science, AI, and new data sources to unlock differentiated value.

You will demonstrate a solutions mindset, applying strong industry and capability knowledge to develop pragmatic programmes of work that lead to tangible results. Leading the development and delivery of MVPs, you will rapidly test ideas through prototyping, experimentation, and iteration, assessing technical feasibility, scalability, and commercial viability.

Working cross-functionally, you will bring MVPs to life, clearly articulating trade-offs to support decision making. You will drive innovation in applied data science using advanced analytics, machine learning, and new data sources, continuously exploring and introducing new techniques to create new solutions and propositions.

Collaboration across Global Data Science is key to bring the best science capabilities into CPG solutions now and in the future. You will promote a culture of re-use of dunnhumby science, modules, and code lines over re-invention, packaging new solutions for global re-use where possible.

As a leader, you will manage risk effectively, provide visible and consistent leadership on Values and Code of Business Conduct, and act proactively where issues arise. Protecting your team by ensuring they have the skills and training needed is a priority.

At dunnhumby, we offer a comprehensive rewards package, flexible working hours, your birthday off, and investment in cutting-edge technology. We foster an inclusive culture with thriving networks supporting gender equality, LGBTQ+ pride, family, disability, and wellbeing. We are committed to enabling everyone to perform at their best throughout the recruitment process and beyond.

Our approach to flexible working respects your work/life balance and we encourage discussions about agile working opportunities during the hiring process.

Experience
Proven experience managing and leading teams of Data Scientists and Market Researchers. Strong background in applied data science, advanced analytics, machine learning, and solution delivery. Experience working cross-functionally to develop and deliver MVPs and scalable solutions. Demonstrated ability to translate commercial ideas into pragmatic data science programmes.

About you
Dynamic and collaborative leader with a solutions mindset. Strong industry knowledge and capability in data science and AI. Excellent communication skills with the ability to articulate trade-offs and support decision making. Passionate about innovation and continuous improvement. Committed to fostering a culture of quality, collaboration, experimentation, and re-use of scientific assets. Values-driven with a focus on team development and ethical leadership.

Qualifications
A degree in a quantitative discipline such as Data Science, Computer Science, Statistics, Mathematics, or related field is preferred. Relevant experience may substitute formal qualifications. Continuous learning mindset with a commitment to staying current with emerging data science techniques and technologies.