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About the Role
We are seeking a Data Science Manager to transform commercial challenges into scalable Data Science products. This player-coach role involves leading and developing a Data Science team while remaining hands-on with technical work. Success is measured by the widespread adoption and commercial impact of the team's models.
Responsibilities
- Identify high-value opportunities for Data Science by translating commercial problems into predictive models and decision-making products.
- Focus on areas including lifetime value, propensity modelling, customer value, forecasting, and performance marketing optimisation, prioritising work based on commercial impact.
- Guide the development of reusable models and methodologies that scale across products, verticals, and use cases.
- Ensure model outputs are measurable, explainable, and designed for their intended use, taking work from experimentation through adoption.
- Collaborate with Engineering and ML Ops to deploy successful modelling work into reliable production products.
- Ensure models have appropriate experimentation, monitoring, retraining, and feedback loops.
- Partner with technical teams on the infrastructure required for scalable model operation.
- Build trusted relationships across Marketing, Commercial, Analytics, Product, and Engineering teams.
- Translate business needs into Data Science opportunities and complex modelling into clear recommendations.
- Explain the meaning and implications of predictions, and recommend next steps for the business.
- Lead and develop a growing team of Data Scientists while maintaining technical involvement.
- Coach the global team, review modelling approaches and technical outputs, and establish consistent standards.
- Contribute hands-on where it adds value and foster an environment of technical rigour, curiosity, and commercial thinking.
Requirements
- 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.
- 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.
- Experience in incrementality or causal inference is 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.
Skills
- Data Science
- Predictive Modelling
- Machine Learning
- Customer Analytics
- Python
- SQL
- Cloud-based Data Science environments
- ML Ops
- Experimentation
- Model Evaluation
- Incrementality
- Causal Inference
- Stakeholder Management
- Communication
- Product Mindset
- Commercial Judgement
- Performance Marketing
- LTV
- Propensity Modelling
- Customer Value
- Acquisition Optimisation
- Vertex AI
Location
- Remote
Work Type
- Full-time
Experience Level
- Manager
About the Company
- Forbes Advisor provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
- This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
Equal Opportunity
- Forbes Advisor provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
- This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.