Senior Director, Data Science

Role Overview

The Senior Director of Data Science for Europe forms a crucial part of the regional Data & Intelligence leadership team, reporting to the Senior Director II of Data & Intelligence Europe. Positioned within an integrated team encompassing Data Product Management, Governance, Engineering, Decision Intelligence, and AI, this role champions advanced analytics methodologies to drive impactful business outcomes across the European Operating Unit (EOU).

Main Responsibilities

• Identify and spearhead high-value opportunities leveraging data science, decision science, and AI to enhance business decisions, automate processes, improve planning, and unlock growth and efficiency.
• Maintain a comprehensive grasp of European data dynamics across diverse markets, bottlers, customers, channels, and sales models, ensuring regional nuances are embedded within models and deployments.
• Bridge regional needs with global frameworks by adopting scalable enterprise capabilities while tailoring them to Europe's specific context.
• Implement a disciplined methodology to discern the appropriate analytical approach—whether predictive, prescriptive, diagnostic, or simpler techniques—aligning solutions with the complexity of business questions.
• Establish and uphold frameworks, standards, and responsible AI practices covering areas such as model design, validation, deployment, monitoring, fairness, privacy, and transparency.
• Lead and develop a cohesive, high-performing Data Science team integrated with cross-functional units, ensuring clear responsibilities, growth opportunities, and shared accountability.
• Oversee demand, capacity, and resource allocation, monitoring financials and partner engagements to maximize return on investment and sustainable value delivery.
• Scale analytical solutions from proof-of-concept stages to trusted, optimized, and widely adopted business tools, continuously enhancing models based on performance and feedback.

Educational Qualifications

• Bachelor's degree in Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, Economics, Engineering, or related fields is required.
• A Master's degree or PhD is highly preferred.
• Professional development in AI, machine learning, decision science, optimisation, experimentation, cloud platforms, product management, or responsible AI is advantageous.

Required Skills and Experience

• More than 12 years of extensive experience in data science, decision science, advanced analytics, or AI, including leadership roles.
• Proven ability to deliver scalable analytical or AI-driven business solutions within complex, multi-market environments.
• Expertise in machine learning, statistical modeling, experimentation, causal inference, optimisation, and decision support.
• Judicious application of advanced versus simpler analytical methods, prioritizing value and business context.
• Strong knowledge of data engineering dependencies, modern cloud-based data platforms, MLOps, and production deployment.
• Experience collaborating within product-centric or Agile organizations encompassing business, engineering, governance, and architecture teams.
• Demonstrated skill in clearly communicating analytical techniques and uncertainties to senior, non-technical stakeholders.
• Establishing standards for model lifecycle management, responsible AI, and monitoring.
• Leadership experience in people management, resource planning, talent development, and budgeting within matrixed organizations.

Competencies Supporting Success

• Business-driven decision science focus for translating analytics into tangible European Operating Unit value.
• Deep understanding of the complex, heterogeneous European data landscape and market structures.
• Proficient leadership in data and decision science methods applied to real-world challenges.
• Experience employing recognized frameworks and maturity assessments to guide capability development.
• Product and engineering-oriented mindset connecting business needs with solution architectures.
• Ability to balance global standardization with regional customization to maximize impact.
• Skilled executive communication and partnership to facilitate clear decision-making.
• Strong people leadership fostering high performance and continuous learning.