VP, People Analytics & Data Strategy

UnitedHealth Group•Eden Prairie, MN

1d•$200,400 - $343,500•Remote

About The Position

The VP, People Analytics & Data Strategy will lead the People function’s enterprise analytics, workforce data semantics, and AI data readiness agenda. This leader will be accountable for ensuring People data is trusted, well-governed, business-relevant, and fit for use across analytics, decision support, AI, and intelligent workflows. This is a strategic leadership role at the intersection of workforce analytics, data stewardship, AI readiness, and business decision support. The VP will own the business meaning of People data, the semantic consistency of metrics and KPIs, the readiness of data for priority AI use cases, and the translation of data into decision support and measurable business value. The role will work in close partnership with Tech partners, COEs, Shared Services, AI Enablement, and other key partners. People-side ownership of data meaning and stewardship will sit here; technical architecture, engineering, and runtime sits with Tech.

Requirements

12+ years of leadership experience in enterprise analytics, data and analytics, people analytics, data governance, digital transformation, or adjacent strategy roles
Proven experience leading analytics and/or business data strategy in a complex enterprise environment
Solid experience owning business data definitions, governance, metrics, and cross-functional stakeholder alignment
Experience enabling AI, advanced analytics, or intelligent automation through improved data readiness and stewardship
Solid executive communication skills and ability to translate complex data topics into business decisions and strategic narratives
Experience working in close partnership with engineering, architecture, product, and technology leaders
Demonstrated success building teams and operating models across analytics, governance, and decision support

Nice To Haves

Experience in HR, HRIS, workforce analytics, talent analytics, payroll analytics, or adjacent People domains
Experience with enterprise platforms such as Oracle HCM, ServiceNow, Salesforce, Power BI, and cloud data platforms
Experience in regulated or audit-sensitive environments where data quality, lineage, and governance matter materially
Familiarity with AI-ready data concepts such as metadata, observability, lineage, stewardship, and data product management
Sees data as a strategic business asset, not a reporting output
Can bridge semantics, analytics, AI, and executive decision-making
Brings rigor to definitions, governance, and measurement
Can partner effectively with senior Technology leaders without ceding business ownership of the data
Is comfortable operating at executive altitude while building real capability below
Understands that in an AI-first organization, trusted data is the foundation of trust, speed, and scale

Responsibilities

Lead the People analytics and workforce insights agenda in support of enterprise, functional, and executive decision-making
Deliver high-impact workforce reporting, dashboards, scorecards, and insights that inform strategic decisions across talent, workforce, payroll, productivity, and organizational effectiveness
Shape executive and board-ready workforce narratives, including trend analysis, scenario support, and strategic storytelling
Establish clear standards for insight quality, metric consistency, and business interpretation
Own the business meaning, stewardship, and source-of-truth logic for People data across major domains including Core HR, Talent Acquisition, Talent, Learning, Payroll, Time, and Employee Support
Define and govern metric logic, KPI definitions, business rules, and semantic consistency across the People ecosystem
Establish a People data stewardship model, including domain accountability, issue resolution, and governance mechanisms
Partner with COEs and Shared Services to ensure critical business rules and source data requirements are clearly defined and maintained
Lead the People-side AI data strategy, ensuring data is fit for purpose for priority AI use cases, agent workflows, and intelligent automation
Assess and prioritize AI data-readiness needs for key use cases, including structured and unstructured data, enrichment, metadata, lineage, and observability requirements
Define the backlog of People data products and improvements required to enable AI-first HR capabilities
Partner with AI Enablement and People Tech to align data priorities to product roadmap and AI use-case strategy
Establish and enforce business-facing governance for People data quality, stewardship, privacy, and appropriate use
Define business quality thresholds and monitor data issues that impact trust, analytics, or AI deployment
Partner with Tech, Privacy, Compliance, and Security teams to ensure People data governance aligns with enterprise controls and AI governance requirements
Help shape the People function’s role in AI governance, especially where workforce data supports sensitive decisions or employee-facing experiences
Partner with Optum Tech on enterprise data engineering, platform architecture, metadata tooling, lineage, observability, pipeline delivery, and BI engineering
Serve as the business owner for People data requirements while Tech owns technical build and runtime
Translate business semantics and use-case needs into technical requirements for data pipelines, models, and platform capabilities
Ensure solid alignment between People data priorities and enterprise platform investments
Define and monitor value metrics for People analytics, AI-enabled workflows, and digital products
Establish KPI frameworks to track adoption, business outcomes, efficiency gains, and decision quality
Ensure analytics and AI investments are tied to measurable business value, not just technical activity
Provide leadership on how data and AI should be measured, governed, and continuously improved
Build and lead a high-performing team across workforce analytics, data semantics, stewardship, AI data readiness, and value measurement
Develop talent and capabilities in analytics, business data ownership, stewardship, and AI-ready data practices
Establish a modern operating model that connects analytics, product, AI, and technology teams with clear accountability and decision rights
Serve as a senior leader across the People transformation agenda, bringing clarity, rigor, and enterprise perspective