Director I, Data Science, People, Purpose & Brand

The Data Science and Assessments (DS&A) team within People, Purpose, & Brand (PP&B) is hiring a Director I, Data Scientist (STP) to serve as a hands-on technical leader for GenAI evaluation, enablement, and responsible AI adoption. PP&B develops programs across talent acquisition, workforce planning, performance & rewards, employer branding, and wellbeing to build a diverse, future-ready workforce.

In this role, you will shape how DS&A generates, evaluates, and scales ML and GenAI-based programs and tooling to improve productivity, decision-making, and employee experience across PP&B. Core responsibilities span three areas:

• GenAI Enablement: Design, build, and maintain evaluation frameworks and pipelines that accelerate the creation, iteration, and safe expansion of GenAI capabilities, including agentic workflows, data readiness, and post-deployment monitoring.
• Vendor & AI/ML Risk Management: Define and execute a vendor-AI evaluation vision enabling repeatable vendor selection, value validation, quality monitoring, and responsible model risk management.
• Broader Data Science: Support classic ML, automation, and technical consulting to empower PP&B colleagues and drive enterprise-wide outcomes.

This individual contributor role reports through the Office of Data & Data Science. The ideal candidate is proactive, highly technical, and collaborative; able to translate complex tradeoffs into clear, actionable recommendations that drive meaningful impact.

Key Responsibilities

• Architect, develop, and maintain tooling and pipelines to support GenAI model development, evaluation, deployment, and monitoring across PP&B programs.
• Design and operationalize scalable evaluation frameworks and metrics for GenAI systems (including automated and human-in-the-loop evaluations) to ensure quality, safety, and organizational alignment.
• Lead the vendor AI evaluation program: define criteria, run benchmarks and pilots, synthesize results, and provide clear recommendations for vendor selection and integration.
• Build reusable components leveraging APIs and templates that enable rapid iteration and reliable deployment of GenAI features.
• Partner with stakeholders across PP&B to translate business needs into technical designs, evaluation plans, and implementation roadmaps.
• Promote strong engineering hygiene across projects (CI/CD, version control, testing, documentation, reproducible pipelines).
• Provide informal mentorship for data science and analytics colleagues on tools and evaluation processes.