BN31M1-Manager, Scientific AI Engineering & Data Science

CAS•Columbus, OH

About The Position

The Manager, Scientific AI Engineering & Data Science is a people-leadership role responsible for building, growing, and leading a team of data scientists and AI engineers. This team develops the systems for CAS's scientific discovery products, including retrieval, extraction, and reasoning that power CAS Newton℠ and CAS Connections, as well as internal platforms. The role is part of the Data Analytics & Insights (DAI) organization. The manager's primary focus is people management: hiring, coaching, developing, and retaining talent, and fostering an environment where the team can perform at its best. While technical direction, architecture, and roadmap delivery are handled by technical leads and product partners, the manager must possess sufficient technical fluency to lead, coach, and mentor credibly. This includes understanding the work, assessing the quality of contributions, and guiding growth, without being accountable for owning the technical roadmap. The role also involves contributing to team-wide and enterprise-wide initiatives as DAI scales, and effectively communicating the team's work to various audiences.

Requirements

Master's degree in a relevant technical or quantitative discipline (e.g., Computer Science, Applied Mathematics, Statistics, Data Science, Computational Chemistry, Physics, Bioinformatics), or equivalent experience.
8+ years of relevant experience.
3-5+ years developing people and leading technical teams.
Hands-on background in AI/ML engineering and data science sufficient to lead and coach credibly.
Familiarity with modern AI engineering — LLM-based, agentic, and large-scale retrieval and extraction systems.
Proven ability to hire, coach, grow, and retain technical talent.
Strong people-management, feedback, and career-development skills.
Team-wide and enterprise-wide perspective, and readiness to lead initiatives beyond one's own reporting line.
Ability to represent the team's work fluently and confidently to internal and external audiences.
Sound judgment on team health, culture, and prioritization.
Sufficient technical fluency to earn the trust of a team of data scientists and AI engineers.

Nice To Haves

A PhD and/or deep scientific domain expertise (chemistry, life sciences, materials science).
Experience in scientific, chemical, pharmaceutical, or materials-science domains.

Responsibilities

Build, grow, and lead a team of data scientists and AI engineers.
Develop systems for CAS's scientific discovery products, including retrieval, extraction, and reasoning.
Hire, coach, develop, and retain data scientists and AI engineers.
Create the conditions for the team to do its best work.
Lead and coach credibly with sufficient technical fluency in modern AI engineering.
Judge the quality of technical work and provide meaningful feedback.
Reinforce trustworthy-AI principles, including reliance on curated, provenanced scientific content.
Partner with technical leads and product on technical direction, architecture, and roadmap.
Ensure the team is well-resourced, unblocked, and set up for success.
Remove organizational and people-level obstacles.
Support healthy operating practices like delivery rhythm, review, and production health.
Bring team-wide and enterprise-wide thinking to the role.
Lead and drive cross-cutting initiatives as priorities dictate.
Speak fluently and confidently about the team's work to internal and external audiences.
Approach the role with an ownership mindset extending beyond the immediate team.
Partner across Product, Technology, Content Operations, and other teams.
Represent the team's capacity, needs, and health to stakeholders and leadership.
Connect the team's people and capabilities to CAS's broader goals.