Manager Data Science

Responsibilities

• Lead and develop high-performing teams of data scientists, machine learning engineers, and researchers.
• Define and execute data science strategies to advance scientific discovery and research intelligence.
• Drive the development of AI-powered capabilities including search, retrieval, NLP, and generative AI.
• Translate complex scientific and business challenges into scalable, production-ready AI solutions.
• Establish high standards for experimentation, model quality, reliability, and responsible AI practices.
• Partner with Product, Engineering, and Research teams to shape product strategy and delivery.
• Mentor and coach team members while fostering a culture of scientific rigor and continuous learning.
• Guide the adoption of emerging technologies such as LLMs, RAG architectures, and semantic search.

Requirements

• Significant experience leading data science, machine learning, or AI technical teams.
• Proven success in building, coaching, and developing high-performing technical teams.
• Technical expertise in machine learning, generative AI, and large language models (LLMs).
• Deep understanding of modern AI approaches, including RAG architectures, semantic search, and embeddings.
• Experience delivering AI-powered products from initial concept through to production deployment.
• Strong stakeholder management skills with the ability to influence technical and executive audiences.
• Experience working with large-scale structured and unstructured data in production environments.

About the Company

Elsevier is a global leader in advanced information and decision support for science and healthcare. We combine high-quality content with powerful analytics to transform complexity into clarity, delivering mission-critical insights that help professionals make better decisions. By connecting quality content with innovative technologies, we help researchers discover knowledge faster and accelerate scientific progress worldwide.