[Hiring] Data Science Manager @Forbes Advisor

Role Description

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.

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.
• Scalable Data Science Products: Guide the development of reusable models and methodologies that can scale across products, verticals and use cases.
• Production Data Science: Work closely with Engineering and ML Ops to turn successful modelling work into reliable production products.
• Business Partnership & Insight: Build trusted relationships across Marketing, Commercial, Analytics, Product and Engineering.
• Team Leadership & Technical Quality: Lead and develop a growing team of Data Scientists while remaining technically close to the work.

Qualifications

• Experience managing and developing Data Scientists while remaining comfortable working at a technical level.
• Strong experience in predictive modelling, machine learning and customer analytics.
• Experience applying Data Science to commercial or performance marketing problems, ideally including LTV, propensity, customer value or acquisition optimisation.
• Strong Python and SQL skills and experience working within modern cloud-based Data Science environments.
• Experience taking models beyond experimentation and working with Engineering or ML Ops teams to deploy and operate them in production.
• Strong understanding of experimentation and model evaluation, with experience in incrementality or causal inference particularly valuable.
• Excellent stakeholder management and communication skills, including the ability to translate complex technical work into clear recommendations for senior business audiences.
• A product mindset, with an interest in building reusable capabilities rather than one-off models.
• Strong commercial judgement and a focus on measuring the real-world impact of Data Science.

Nice to Have

• Experience in performance marketing and optimisation across Google, Meta or other major advertising platforms.
• Value-based bidding or conversion-value optimisation.
• Direct collaboration with advertising platform Data Science or Marketing Science teams.
• Experience in affiliate marketing, lead generation or digital publishing.
• Experience in financial services, insurance, health or other regulated industries.
• Experience in attribution and marketing measurement.
• Experience in forecasting commercial or marketing performance.
• Experience with DSP or advertising optimisation algorithms.
• Familiarity with modern MLOps tooling and platforms such as Vertex AI.
• Experience with applied AI techniques that complement traditional predictive modelling and decision science.

Why Join Us?

This is an opportunity to help build a Data Science capability where models are expected to do something. You'll work on commercially significant problems with large datasets, direct connections to marketing and customer outcomes, and a clear route from experimentation into production.

Most importantly, you'll be judged on the decisions your team improves and the value its products create, not simply the sophistication or number of models it builds.