Data Science Manager (Remote)

About this role

Overview We're looking for a Data Science Manager who can turn commercial problems into scalable Data Science products. You'll work closely with business and marketing teams to identify high-value opportunities, lead the development of reusable predictive models, and ensure those models become embedded in how the business makes decisions. This is a player-coach role. You'll lead and develop a growing team of Data Scientists while remaining close enough to the work to shape methodology, review technical outputs and contribute hands-on where needed.

Your success won't be measured by how many models the team builds, but by how widely they're used and the commercial impact they create. The Opportunity You'll work closely with the Director of Data Science to turn our Data Science strategy into scalable products and measurable business outcomes. You'll manage the day-to-day work of a growing team while partnering directly with stakeholders across the business to understand the decisions they're trying to make and identify where Data Science can materially improve the outcome.

Our Data Science team works at the intersection of customer intelligence, performance marketing and commercial decision making. Initial areas of focus include lifetime value, propensity modelling, customer value, forecasting and marketing optimisation, including how predictive models can improve bidding and acquisition across platforms such as Google and Meta. This is not a research-focused role. We want someone who enjoys solving difficult modelling problems but is equally interested in what happens afterwards: how a model gets into production, how people use it, what we learn from it and whether it actually improves performance.

What You'll Do Commercial & Decision Science Work with the Director of Data Science and business and marketing teams to identify high-value opportunities for Data Science, translating commercial problems into predictive models and decision-making products. You'll focus on areas including lifetime value, propensity modelling, customer value, forecasting and performance marketing optimisation, with commercial impact at the centre of how work is prioritised.

Scalable Data Science Products Guide the development of reusable models and methodologies that can scale across products, verticals and use cases rather than repeatedly solving the same problems. You'll take work from experimentation through adoption, ensuring outputs are measurable, explainable and designed around how they'll ultimately be used. Production Data Science Work closely with Engineering and ML Ops to turn successful modelling work into reliable production products.