Staff Business Talent Analytics Data Analyst – Applied AI

Intuit’s PART team is seeking a Staff Business Talent Analytics Data Analyst with a focus on applied AI experimentation for talent analytics and workforce planning. The role prototypes and stress-tests AI approaches for people data, then helps shape how validated work transitions into production-ready, governed outputs with traceable provenance.

This is an onsite opportunity in San Diego, CA, and the expected base pay range is USD 151,000 - 204,000 per year. The position requires 7+ years of experience and is designed for a builder who can take ideas through testing, evaluation, and handoff.

What you’ll do

• Design, build, and iterate rapid AI proof-of-concepts and experiments across talent analytics, workforce planning, talent acquisition, and related people-data use cases, using modern AI and LLM tooling to validate ideas before engineering investment.
• Create agent-assisted analytics for pilots with clear decision boundaries, specifying what an agent can decide or act on autonomously versus what must be escalated to a human, grounded in governed data.
• Continuously scan for new AI capabilities, tools, and applicable use cases in talent analytics and workforce planning, maintaining an informed point of view on what’s worth piloting next.
• Define dashboard and visualization patterns for prototypes that move toward self-serve or conversational analytics, including identifying which underlying data sources are certified for broader consumption.
• Label AI-generated outputs and prototypes by confidence tier (such as exploratory, validated, or decision-ready) to communicate how much weight stakeholders should place on an insight while ensuring provenance is traceable.
• Partner with the AI Transformation team to align local experimentation with enterprise AI standards, tooling, and roadmap so pilots are not reinvented or left without a path to adoption.
• Bring enterprise capabilities into the team’s use cases and feed learnings back to the enterprise team.
• Work with Technology and HR to contribute to and consume the HR contextual layer by encoding domain definitions and business logic so people and agents can rely on consistent shared context as the infrastructure matures.
• Provide reliable estimates and develop a shared spec-writing discipline for ambiguous, large-scope initiatives so AI-assisted work is planned with delivery rigor.
• Embed AI into the team’s analytics product roadmap by identifying where AI changes product capabilities rather than bolting AI onto existing outputs, and sequencing prototypes with a defined path forward.
• Define what moves from prototype to production, coordinating with data engineering and product to hand off validated solutions with documentation, authored evaluation criteria, and the context required to sustain them, then routing outcomes back into future prototyping.
• Evaluate technical feasibility versus speculative AI use cases and translate findings into actionable recommendations for leadership.
• Communicate technical feasibility, risk, and recommended next steps to senior stakeholders.
• Raise applied AI capability across the team and partner groups by establishing reusable patterns, tooling standards, and working practices so AI-enabled delivery becomes default rather than individual expertise.
• Coach senior analysts and partner teams to run AI-assisted projects and agents independently, focusing on building judgment.

What you’ll need

• 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 or data analytics or applied AI/ML roles, with demonstrated hands-on ownership of building and shipping solutions.
• Direct, hands-on experience building and deploying AI agents or LLM-powered tools/prototypes (for example, using Claude, GPT, or similar); this is a builder role.
• Working knowledge of data warehouse, data pipeline, and data architecture concepts and how they affect AI and analytics readiness at scale.
• Experience designing dashboards/BI and self-serve or conversational analytics patterns, including how to certify data sources for broader consumption.
• Comfort defining confidence tiers or similar governance for AI-generated outputs, along with the ability to estimate and scope ambiguous, large initiatives.
• A strong point of view on evaluating technical feasibility versus speculative AI use cases, with the judgment to make build or no-build recommendations.
• Excellent communication skills, translating experimentation into decisions for senior stakeholders and executive audiences.
• Ability to operate autonomously in ambiguous, undefined problem spaces ahead of established enterprise AI patterns.

Technologies

• Claude
• GPT
• AI agents
• LLM-powered tools
• AI/LLM tooling

Compensation and benefits

• Competitive compensation package with a pay for performance rewards approach.
• May be eligible for a cash bonus.
• May be eligible for equity rewards.
• Benefits

Preferred experience

• Experience with Workday HCM data and Avature or other ATS/recruiting platforms.
• Experience partnering with an enterprise AI/AI Transformation team, platform team, or ML engineering org on shared standards or infrastructure.
• Familiarity with talent analytics or workforce planning domains such as headcount, requisitions, planned exits, and hiring projections.
• Familiarity with People Data governance, security, and access considerations.

Additional location base pay ranges

• Mountain View, CA: $169,500 - $229,000
• New York: $159,500 - $215,500