Director I, Data Science, People, Purpose & Brand

Description 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. Qualifications - Strong foundation in Data Science principles (Probability, Statistics, AI/ML). - Experience with LLMs, embeddings, and generative/agentic systems. - Proficient in Python; comfortable writing production-quality code. - Strong SQL skills for querying, validation, and data exploration. - Experience with APIs and integrating external model or vendor services. - Familiarity with cloud computing concepts and services. - Experience evaluating models for fairness, bias, privacy, explainability, or responsible AI. - Comfortable with Git-based version control and collaborative code review. - Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and a minimum of 3 years of relevant experience, a Master`s degree and a minimum of 6 years of relevant experience or may be acquired through a Bachelor`s degree and a minimum of 8 years of relevant experience. What We Value - A collaborative, customer-focused mindset oriented toward pragmatic, high-impact solutions and enabling others. - Strong project management skills: building clear plans, coordinating across stakeholders, and driving accountability. - Clear communication of technical tradeoffs, evaluation results, and recommendations to both technical and non-technical audiences. - Product-minded engineering: building systems that are maintainable, scalable, and easy to a