Manager Data Science

Overview As Data Science Leader, you will build and guide high-performing teams delivering AI-powered capabilities for scientific discovery and knowledge access. You’ll shape strategy, drive responsible AI practices, and collaborate with cross-functional partners to impact researchers, clinicians, and institutions worldwide. The role blends technical depth with people leadership to turn complex scientific challenges into scalable data science solutions. You will influence long-term AI strategy and ensure trustworthy, measurable outcomes that advance science. Compensation / Benefitsannual incentive bonuscountry-specific benefits ResponsibilitiesLead and develop teams of data scientists, ML engineers, researchers, and contributors.Define and execute data science strategies to advance scientific discovery and knowledge-access products.Drive AI capabilities across search, retrieval, NLP, knowledge systems, and generative AI.Translate customer/scientific/business challenges into scalable data science solutions with measurable outcomes.Establish high standards for experimentation, model quality, reliability, and responsible AI.Partner with Product, Engineering, Research, UX, Analytics, and domain experts to shape strategy and delivery.Mentor and coach team members to foster scientific rigor, collaboration, and continuous learning.Guide adoption of emerging AI technologies including LLMs, retrieval-augmented generation, and semantic search.Influence senior stakeholders and contribute to long-term AI, technology, and product strategy across the organization.Ensure AI systems are trustworthy, scalable, explainable, and aligned with customer and societal outcomes. Key requirementsSignificant experience leading data science, ML, AI, NLP, information retrieval, or related teams.Proven success in building and developing high-performing teams in complex tech or product environments.Technical expertise in ML, generative AI, large language models, retrieval systems, experimentation, and model evaluation.Experience delivering AI-powered products or platforms from concept to production with measurable impact.Deep understanding of LLMs, RAG architectures, semantic search, embeddings, and knowledge systems.Experience establishing evaluation frameworks, experimentation practices, and performance metrics for AI solutions.Ability to translate ambiguous challenges into clear strategy and execution plans.Exceptional communication and stakeholder-management skills with ability to influence technical, product, and executive audiences.Experience working with large-scale structured, semi-structured, and unstructured data in production environments.A passion for advancing science, expanding access to knowledge, developing people, and applying AI for real-world impact.strong leadership and people developmentstrategic thinking and decision makingeffective communication and stakeholder managementmachine learninggenerative AIlarge language models