Analytics & AI Specialist

Requirements

• Technical fluency Comfortable working in data environments - can write or interpret SQL, work with HRIS/HCM systems at a configuration level, and has enough familiarity with data pipelines to partner credibly with engineers. Doesn't need to build everything themselves, but can't be a passenger in technical conversations
• AI tool judgment Has worked with or evaluated AI tools in a workflow context - not just theoretical familiarity. Can assess fit, scope a use case, and distinguish between "this saves time" and "this creates risk." Knows when to pilot and when to wait
• Cross‑functional translation Can move fluently between a People Team conversation and an IT/engineering conversation - translating needs, priorities, and constraints in both directions without losing either audience
• Structured problem‑solving Brings rigor to ambiguous situations. Can take a messy data or process problem and create a workable structure - clear scope, defined output, realistic timeline
• Influence without authority This role doesn't own a team or a budget. Gets things done by building trust, setting clear expectations, and making the case for prioritization. Comfortable being the person who moves things forward without having formal control over them
• (Desirable) People function knowledge Understands how HR data flows - hiring, onboarding, performance, comp, exits - and what questions leaders and HRBPs are actually trying to answer. Knows where the gaps between system data and operational reality typically live

• We're looking for someone who brings both technical fluency and people‑function context - someone who can own how People Team data is structured, governed, and used, and who can serve as the bridge between People and IT to unlock AI‑enabled work
• This isn't a pure analytics role or a pure systems role. It's someone who understands the full data‑to‑decision chain and can make it faster and more reliable - while actively building toward a more AI‑augmented People function
• Ensure People Team data is clean, documented, and accessible - with clear ownership, defined governance, and a shared understanding of how we can apply it to different use cases
• Business leaders and key members of the People org have reliable, self‑service access to the metrics that matter most (headcount, attrition, talent pipeline, org health) - without routing every request through a single person
• Build towards a working model for how People and IT collaborate on data and AI projects - clear intake, prioritization, and delivery norms that didn't exist before
• Establish and maintain People data governance standards - including data definitions, audit processes, and documentation - so the org has a clear, trusted source of truth
• Monitor integration runs, troubleshooting data syncs, and UAT for HRIS changes
• Based on input from People leaders, develop a clear AI roadmap, including a prioritized backlog grounded in actual workflow analysis
• Support and partner with People team leaders to drive towards an end state of meaningfully augmented by AI tooling by scoping, building, and developing comprehensive roll out plans