Manager Data Science

About the role

Lead and develop high-performing teams of data scientists, machine learning engineers, researchers, and technical contributors.
Define and execute data science strategies that advance scientific discovery, research intelligence, and knowledge-access products.
Drive the development of AI-powered capabilities across search, retrieval, recommendation, NLP, knowledge systems, and generative AI.
Translate complex customer, scientific, and business challenges into scalable data science solutions and measurable outcomes.
Establish high standards for experimentation, evaluation, model quality, reliability, and responsible AI practices.
Partner closely with Product, Engineering, Research, UX, Analytics, and domain experts to shape product strategy and delivery.
Mentor and coach team members while fostering a culture of scientific rigor, collaboration, innovation, and continuous learning.
Guide the adoption of emerging AI technologies, including LLMs, retrieval-augmented generation, semantic search, and knowledge-based systems.
Influence senior stakeholders and contribute to long-term AI, technology, and product strategy across the organization.
Ensure that AI systems are trustworthy, scalable, explainable, measurable, and aligned with meaningful customer and societal outcomes.

Responsibilities

• Lead and develop high-performing teams of data scientists, machine learning engineers, researchers, and technical contributors.
• Define and execute data science strategies that advance scientific discovery, research intelligence, and knowledge-access products.
• Drive the development of AI-powered capabilities across search, retrieval, recommendation, NLP, knowledge systems, and generative AI.
• Translate complex customer, scientific, and business challenges into scalable data science solutions and measurable outcomes.
• Establish high standards for experimentation, evaluation, model quality, reliability, and responsible AI practices.
• Partner closely with Product, Engineering, Research, UX, Analytics, and domain experts to shape product strategy and delivery.
• Mentor and coach team members while fostering a culture of scientific rigor, collaboration, innovation, and continuous learning.
• Guide the adoption of emerging AI technologies, including LLMs, retrieval-augmented generation, semantic search, and knowledge-based systems.
• Influence senior stakeholders and contribute to long-term AI, technology, and product strategy across the organization.
• Ensure that AI systems are trustworthy, scalable, explainable, measurable, and aligned with meaningful customer and societal outcomes.

Requirements

Significant experience leading data science, machine learning, artificial intelligence, NLP, information retrieval, or related technical teams.
Proven success building, coaching, and developing high-performing teams in complex technology or product environments.
Technical expertise across machine learning, generative AI, large language models, retrieval systems, experimentation, and model evaluation.
Experience delivering AI-powered products or platforms from concept through production deployment and measurable impact.
Deep understanding of modern AI approaches, including 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, execution plans, and business outcomes.
Exceptional communication and stakeholder-management skills with the 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 to create meaningful real-world impact.

Qualifications

U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates.

Skills

Significant experience leading data science, machine learning, artificial intelligence, NLP, information retrieval, or related technical teams.
Proven success building, coaching, and developing high-performing teams in complex technology or product environments.
Technical expertise across machine learning, generative AI, large language models, retrieval systems, experimentation, and model evaluation.
Experience delivering AI-powered products or platforms from concept through production deployment and measurable impact.
Deep understanding of modern AI approaches, including 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, execution plans, and business outcomes.
Exceptional communication and stakeholder-management skills with the 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 to create meaningful real-world impact.

Benefits

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Pay

U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates.

Schedule

N/A