Data Science Manager

About the role

As a Data Science Manager within the Customer Development XOPS team in Data Foundation, you will be responsible for leading data science delivery across products and markets, shaping technical direction, and developing high-performing teams. This is a hands-on leadership role, combining technical depth with people management and strong business partnership. You will own the end-to-end data science lifecycle for key initiatives—translating business problems into scalable analytics solutions, ensuring high-quality delivery, and embedding data science into decision-making at scale.

Responsibilities

• Own and shape the data science roadmap for products within our Customer Development (CD) portfolio, aligned to commercial priorities and business outcomes.
• Lead the design, development, and deployment of diagnostic, predictive, and prescriptive analytics solutions, ensuring robustness, scalability, and interpretability.
• Set modelling and analytical standards across the team, covering classical statistical methods, machine learning, and emerging Generative and Agentic AI capabilities.
• Ensure solutions are industrialised and production-ready, leveraging cloud platforms (Azure, Databricks) and aligned with MLOps best practices.
• Lead, coach, and develop a team of data scientists, supporting both technical growth and career progression.
• Foster a culture of high ownership, continuous improvement, and learning, encouraging experimentation while maintaining delivery discipline.
• Provide technical guidance and review, acting as a mentor and escalation point for complex analytical challenges.
• Partner closely with Product, Engineering, and Business stakeholders to shape problem definitions, prioritise initiatives, and drive adoption of data science solutions.
• Translate complex analytics into clear, actionable insights for senior stakeholders, supporting data-driven decision-making.
• Balance short-term delivery with long-term capability building, ensuring alignment between local market needs and global product strategy.
• Champion agile ways of working, enabling fast-paced experimentation and iterative delivery.
• Identify opportunities to build reusable frameworks, scale solutions, and feed innovation into the global CD product pipeline.

Requirements

Degree qualified in a relevant technical discipline (Data Science, Computer Science, Engineering, Mathematics, Statistics, Econometrics, or similar). Proven experience leading data science teams working on complex analytics initiatives in a commercial or product-driven environment.

Qualifications

Strong background in data science modelling, with deep expertise in several of the following:

• Econometric modelling (Regression, Bayesian approaches) especially in the context of pricing and promotions in the CPG/Retail space
• Time series forecasting
• Simulation and optimisation tools
• Experience designing and industrialising machine learning solutions at scale; exposure to agent-based AI systems is a strong advantage.
• Advanced proficiency in Python, Spark, and modern analytics stacks; hands-on experience with Databricks and Azure.

Skills

Strong people leader with experience coaching and developing talent in multidisciplinary teams. Excellent communicator, able to influence and align senior stakeholders through clear storytelling and data-driven narratives. Strategic thinker with the ability to prioritise effectively and focus teams on what delivers the most value. Comfortable operating in a fast-paced, global, and ambiguous environment, balancing delivery with longer-term vision. High ethical standards in data usage, governance, and decision-making.

Benefits

• Health insurance (including prescription drug, dental, and vision coverage)
• Retirement savings benefits
• Life insurance and disability benefits
• Parental leave
• Sick leave
• Paid vacation and holidays
• Access to numerous