Staff People Analyst, Applied AI

Intuit

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Mountain View, CASan Diego, CANew York, NYFrisco, TX
Salary
$169,500–$229,000 / yr
Posted
6 days ago
Freshness
Confirmed live yesterday
Nearby
99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $209k
This role $199k
$153k $275k
below market most similar roles pay here above market

This role pays less than 63% of similar roles. Most pay $172,112–$246,500 — the blue band above. At the midpoint, this role pays about $199k versus about $209k for comparable roles.

Based on 240 similar postings.

Employer

About Intuit

Intuit is a financial software company known for products like TurboTax, QuickBooks, Mint, and Credit Karma, helping consumers and small businesses manage their finances and taxes. Industry: Financial Software & Technology

Intuit currently has 219 open roles on FindRole.

Listed pay typically runs $202,500–$274,000 across 198 roles with salary data.

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At a glance

TL;DR · Staff People Analyst, Applied AI

Role Posting Log in to save

Staff People Analyst - Applied AI The Staff People Analyst - Applied AI joins the People & Places Analytics, Research, and Technology team to drive applied AI experimentation across talent analytics and workforce planning. This hands-on builder role involves rapidly prototyping AI proof-of-concepts, designing agent-assisted analytics with explicit decision boundaries, and translating technical experimentation into business needs. You will build and iterate on LLM-powered tools using technologies like Claude and GPT while managing data warehouse and pipeline concepts. Key responsibilities include defining dashboard patterns for conversational analytics, establishing confidence tiers for AI outputs, and aligning local pilots with enterprise AI standards. You will solve the problem of turning AI opportunities into deployed value by encoding domain logic into a shared contextual layer and coaching others on AI-assisted project delivery.

Skills

AI LLM Data Analytics Data Warehouse Data Pipeline Data Architecture BI Conversational Analytics Claude GPT Workday HCM Avature ATS Data Governance

What you'll do

  • Design, build, and iterate rapid AI proof-of-concepts and experiments for talent analytics and workforce planning.
  • Design agent-assisted analytics with explicit decision boundaries for autonomous actions versus human escalation.
  • Define dashboard and visualization patterns for prototypes transitioning to self-serve or conversational analytics.
  • Label AI-generated outputs by confidence tiers and ensure traceable provenance for all insights.
  • Align local AI experimentation with enterprise standards and roadmap to prevent duplication of capabilities.
  • Contribute domain definitions and business logic to the HR contextual layer for shared infrastructure.
  • Define production handoff criteria and documentation for validated AI solutions to be managed by data engineering.
  • Coach senior analysts and partner teams to independently run AI-assisted projects and agents.

What we're looking for

  • Bachelor's degree in AI, Data Analytics, Computer Science, Business, Human Resources, Industrial/Organizational Psychology, or a related field.
  • 7+ years of experience in business/data analytics or applied AI/ML roles with hands-on ownership of building and shipping solutions.
  • Direct, hands-on experience building and deploying AI agents or LLM-powered tools and prototypes.
  • Working knowledge of data warehouse, data pipeline, and data architecture concepts.
  • Experience with dashboard/BI design and self-serve or conversational analytics patterns.
  • Ability to define confidence tiers for AI outputs and provide reliable estimates for ambiguous, large-scale initiatives.
  • Excellent communication skills to translate technical experimentation into actionable recommendations for senior stakeholders.
  • Experience with Workday HCM data, ATS platforms, talent analytics, or enterprise AI transformation teams (preferred).

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