Overview As Data Science Leader, you will build and mentor high-performing teams delivering AI-powered search, NLP, and knowledge systems to accelerate scientific discovery. You'll shape strategy, elevate technical excellence, and guide AI-enabled products used by researchers and healthcare professionals worldwide. You'll lead efforts across data, models, and evaluation to ensure trustworthy, scalable solutions with measurable impact. This is leadership with purpose, applying AI to advance science and knowledge access.
Compensation / Benefits- annual incentive bonus
- country-specific benefits
Responsibilities- Lead and develop teams of data scientists, ML engineers, researchers, and contributors
- Define and execute data science strategies for 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
- Collaborate with Product, Engineering, Research, UX, Analytics, and domain experts to shape strategy
- Mentor and coach team members, fostering scientific rigor and continuous learning
- Guide adoption of emerging AI tech (LLMs, RAG, semantic search, knowledge-based systems)
- Influence senior stakeholders on long-term AI/technology/product strategy
- Ensure AI systems are trustworthy, explainable, and aligned with meaningful outcomes
Key requirements- Significant experience leading data science, ML, AI, NLP, information retrieval, or related teams
- Proven success building and developing high-performing teams in complex environments
- Technical expertise in ML, generative AI, LLMs, retrieval systems, experimentation, and evaluation
- Experience delivering AI-powered products from concept to production with measurable impact
- Deep understanding of LLMs, RAG, semantic search, embeddings, and knowledge systems
- Experience establishing evaluation frameworks and performance metrics for AI
- Ability to translate ambiguous challenges into clear strategy and execution plans
- Exceptional communication and stakeholder-management skills with executives
- Experience with large-scale structured, semi-structured, and unstructured data in production
- Passion for advancing science and expanding access to knowledge
- Strategic thinking
- Mentorship and leadership
- Cross-functional collaboration
- Machine learning
- Generative AI
- Large language models (LLMs)
