Note: The job is a remote job and is open to candidates in USA. Forbes Advisor is hiring a Data Science Manager to turn commercial problems into scalable Data Science products and measurable business outcomes. The role leads and develops a team of Data Scientists, partners with business and marketing stakeholders, and guides predictive models from experimentation into production and adoption.

Responsibilities

• 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
• 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
• Work closely with Engineering and ML Ops to turn successful modelling work into reliable production products. You'll ensure models have appropriate experimentation, monitoring, retraining and feedback loops, while partnering with technical teams on the infrastructure needed to operate them at scale
• Build trusted relationships across Marketing, Commercial, Analytics, Product and Engineering. You'll translate business needs into Data Science opportunities and complex modelling into clear recommendations, ensuring the team goes beyond producing predictions to explain what they mean, what we can learn from them and what the business should do next
• Lead and develop a growing team of Data Scientists while remaining technically close to the work. You'll coach the global team, review modelling approaches and technical outputs, establish consistent standards and contribute hands-on where it adds value. You'll create an environment where technical rigour, curiosity and commercial thinking reinforce one another

Skills

• 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
• 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
• 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
• Ideally including LTV, propensity, customer value or acquisition optimisation
• With experience in incrementality or causal inference particularly valuable
• Experience in any of the following would be valuable, but we don't expect every candidate to bring all of them:
• 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
• Affiliate marketing, lead generation or digital publishing
• Financial services, insurance, health or other regulated industries
• Attribution and marketing measurement
• Forecasting commercial or marketing performance
• DSP or advertising optimisation algorithms
• Modern MLOps tooling and platforms such as Vertex AI
• Applied AI techniques that complement traditional predictive modelling and decision science

Benefits

• Remote work arrangement

Company Overview