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. 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 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. Core Competencies 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. Highest-signal resume keywords Data Science Team Leadership Machine Learning Solution Design Econometric Modeling Expertise Advanced Python Proficiency Cloud Platform Experience (Azure, Databricks) ATS Optimization Keywords Hard Skills 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 Soft Skills Coaching and Mentoring Collaboration Problem-Solving Communication Continuous Improvement Industry Keywords Customer Development Commercial Priorities Data-Driven Decision-Making Agile Methodologies CPG/Retail Tools & Technologies Azure Databricks Spark Modern Analytics Stacks #J-18808-Ljbffr Jobtailor