Data Science Lead

Capgemini is a global leader partnering with companies to transform and manage their businesses, with over 340,000 people in more than 50 countries and a 55+ year heritage. The Group delivers end-to-end services from strategy and design to engineering, powered by AI, cloud, and data capabilities. The role is within Group IT, which delivers enterprise-wide solutions by harmonizing global standards and integrating business units into a unified IT services model, driving transformative rollouts to enhance security, streamline operations, and elevate digital experiences globally.

• Bachelor’s or Master’s degree in Data Science, Computer Science, Applied Mathematics, or a related field
• 7+ years of experience in Data Science, with strong exposure to NLP, retrieval augmented systems, LLMs, or applied AI solutions
• Proven experience leading Data Science teams and defining experimentation and evaluation frameworks
• Strong knowledge of LLMs, embeddings, vector search, and model evaluation techniques
• Hands on experience with Python, notebooks, and AI experimentation tooling
• Comfortable working in cross functional environments with product, engineering, architecture, and knowledge teams

• Lead Data Science activities across multiple streams, ensuring consistent methodologies, evaluation standards, and model quality
• Define and implement experimentation frameworks, test protocols, and evaluation strategies for AI features
• Establish best practices for prompt evaluation, feasibility assessments, and iterative model improvement
• Oversee how AI models interact with Neo’s knowledge base to ensure accuracy, relevance, and controlled behaviour
• Guide Data Scientists in refining models based on feature intake requirements and platform constraints
• Collaborate closely with engineering and architecture teams to ensure models are ready for integration into production environments
• Act as the central authority on AI model quality, validation, and alignment across Neo
• Drive continuous improvement of Data Science standards and practices as the platform evolves