Data Science Manager

• 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.
• Champion agile ways of working, enabling fast-paced experimentation and iterative delivery.

• 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
• Strong background in data science modelling, with deep expertise in several of the following:
• o Econometric modelling (Regression, Bayesian approaches) especially in the context of pricing and promotions in the CPG/Retail space
• o Time series forecasting
• o 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.

Demonstrates expertise in leading data science teams and developing robust analytics solutions, with a strong focus on machine learning, econometric modeling, and cloud platforms. Capable of translating complex data insights into actionable strategies while fostering a culture of continuous improvement and agile methodologies.

• Data Science Team Leadership
• Machine Learning Solution Design
• Econometric Modeling Expertise
• Advanced Python Proficiency
• Cloud Platform Experience (Azure, Databricks)

• Data Science Modeling
• Econometric Modeling
• Time Series Forecasting
• Simulation and Optimization Tools
• Predictive Analytics
• Prescriptive Analytics
• Statistical Methods
• Generative AI
• Agentic AI
• MLOps Best Practices

• Coaching and Mentoring
• Collaboration
• Problem-Solving
• Communication
• Continuous Improvement

• Customer Development
• Commercial Priorities
• Data-Driven Decision-Making
• Agile Methodologies
• CPG/Retail

• Azure
• Databricks
• Spark
• Modern Analytics Stacks