People Analytics & AI Specialist

Faire•New York, NY

2d•Hybrid

About The Position

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.

Requirements

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.
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.
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.
Brings rigor to ambiguous situations. Can take a messy data or process problem and create a workable structure - clear scope, defined output, realistic timeline.
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.

Nice To Haves

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.

Responsibilities

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