Vice President, People Data Strategy & Operational Insights

UnitedHealth Group•Eden Prairie, MN

3d•$200,400 - $343,500•Remote

About The Position

UnitedHealth Group is a health care and well-being company that’s dedicated to improving the health outcomes of millions around the world. We are comprised of two distinct and complementary businesses, UnitedHealthcare and Optum, working to build a better health system for all. Here, your contributions matter as they will help transform health care for years to come. Make an impact with a team that shares your passion for helping others. Join us to start Caring. Connecting. Growing together. The Vice President, People Data Strategy & Operational Insights will lead the enterprise People data strategy for UnitedHealth Group, ensuring workforce data is trusted, governed, secure, AI-ready, and fit for use across operations, analytics, reporting, decision support, and intelligent workflows. This leader will own the People Team’s data operating model, including data governance, stewardship, data quality, business definitions, source-of-truth logic, semantic consistency, data product strategy, and AI data readiness. The role will partner closely with Tech, Operations, COEs, Finance, and business leaders to ensure People data is used responsibly and consistently at enterprise scale. A second critical focus of this role is operational insights. As UnitedHealth Group continues to reimagine the People function, this leader will build the insight and measurement discipline needed to understand how HR work is performed today, where operational friction exists, where AI and process redesign can create value, and whether transformation efforts are improving outcomes. This includes defining operational health metrics, measuring the success of People Team Reimagination initiatives, and helping leaders make fact-based decisions about service delivery, workflow design, automation, shared services, and employee / manager experience. This role is not a traditional reporting or dashboard leadership role. It is a strategic enterprise role focused on making People data trusted, usable, governed, and actionable — and using that data to help reimagine how the People function operates.

Requirements

15+ years of experience in data strategy
Demonstrated experience defining or leading enterprise data strategy, governance, stewardship, data quality, semantic standards, or data product capabilities
Experience with enterprise data platforms, BI tools, semantic layers, data catalogs, lineage, metadata, observability, and/or data quality tools
Experience partnering with senior business leaders in Technology, HR, Finance, Legal, Privacy, Security and/or Compliance
Demonstrated ability to translate complex data issues into business decisions, operating model implications, and executive-ready narratives
Experience defining metrics, measurement frameworks, scorecards, operational health indicators, or value realization methods
Track record of driving measurable business results in a large, complex, matrixed organization
Proven leadership experience building teams, developing talent, and influencing across functions

Nice To Haves

Experience defining AI data readiness requirements, governed data products, or data foundations for GenAI / intelligent workflow use cases
Experience measuring transformation value, business case realization, productivity, capacity release, cost avoidance, service quality, adoption, or experience outcomes
Experience in a regulated, highly matrixed, enterprise-scale environment
Experience working with Technology teams where business data ownership and technical engineering ownership are split
Experience leading analytics, insights, or measurement functions that support executive decision-making and operational improvement
Understanding of workforce data and HR processes across areas such as core HR, talent, recruiting, learning, payroll, benefits, time, employee support, or employee relations
HR data, workforce analytics, people analytics, enterprise analytics, data governance, data management or transformation analytics
Experience with Oracle HCM or comparable enterprise HCM platforms such as Workday, SAP SuccessFactors, or PeopleSoft
Experience supporting large-scale HR transformation, shared services transformation, AI-enabled workflow redesign, or enterprise operating model change
Experience building operational insights capabilities for HR, shared services, payroll, benefits, talent acquisition, customer operations, or other high-volume service environments

Responsibilities

Define and lead the enterprise People data strategy across workforce, talent, recruiting, learning, payroll, benefits, time, employee support, employee relations, and other People domains
Establish how People data is governed, structured, secured, maintained, and made fit for use across operations, analytics, AI, reporting, decision support, and enterprise workflows
Build a practical roadmap to improve trust, consistency, usability, and readiness of People data at enterprise scale
Partner with People Technology and Optum Tech to ensure People data requirements are reflected in data platforms, integrations, pipelines, metadata, lineage, observability, reporting architecture, and AI-enabled capabilities
Create clarity on People-side data ownership, including the principle that People own the business meaning, stewardship, readiness, and value of workforce data, while Technology owns architecture, engineering, integration, security, and runtime
Mature the People data governance model, including ownership, stewardship roles, decision rights, issue escalation, and domain accountability
Lead the modernization of common People data definitions, business rules, metric logic, source-of-truth standards, and semantic consistency across People domains
Ensure critical workforce metrics are consistently defined, calculated, interpreted, and used across COEs, HR Operations, PBPs, Finance, business leaders, and executive reporting
Partner across the enterprise to resolve conflicting metric definitions, source-of-truth disputes, and inconsistent data usage
Build practical stewardship routines that improve data trust, not just governance documentation
Upgrade the People data quality framework, including standards, validation rules, thresholds, scorecards, audit routines, defect tracking, root-cause analysis, and remediation governance
Oversee operational data disciplines that support trusted People data, including data corrections, mass data loads, M&A data conversion, recurring audits, cyclical cleanup, and security / access controls
Partner with HR Operations, Payroll, Benefits, Talent, Recruiting, People Technology, and Tech teams to reduce recurring data defects and strengthen upstream data quality
Ensure People data used for payroll, benefits, compliance, reporting, analytics, operational insights, and AI is reliable and appropriately controlled
Create transparency into data health and ensure leaders understand where data quality issues create operational, compliance, experience, or AI-readiness risk
Lead the People data readiness agenda for AI and intelligent workflows
Define what makes People data fit for AI use, including quality, permissions, lineage, metadata, source-of-truth logic, structured and unstructured content readiness, privacy constraints, and risk controls
Partner with appropriate internal groups to assess AI use cases for data readiness, risk, scalability, and value
Ensure AI use cases are grounded in trusted, permissioned, governed People data and content
Help the People Team avoid scaling AI use cases where the underlying data, definitions, content, controls, or operating model are not ready
Build the operational insights capability required to support the People Team Reimagination agenda.
Establish the measurement framework to understand how HR work is performed today, where friction exists, where manual work persists, where defects originate, and where workflow redesign or AI can create value
Partner with HR Operations, Payroll, Benefits Administration, Leave / Absence, Talent Acquisition, People Technology, AI Enablement, and COEs to define operational health metrics across the People function
Create insight routines that help leaders understand volume, quality, cycle time, cost, capacity, case trends, employee experience, manager experience, service performance, and risk
Translate operational data into actionable recommendations that inform process redesign, service tiering, automation, shared services strategy, AI use-case prioritization, and investment decisions
Ensure operational insights are used to support decisions, not just report activity
Define the People data product strategy, including reusable workforce data assets that support analytics, operational insights, reporting, AI, decision support, and enterprise workflows
Own People-side business requirements for data products, semantic layers, AI-ready data assets, reporting datasets, workforce intelligence capabilities, and operational insight products
Partner with Optum Tech on data architecture, engineering, integration, metadata, lineage, observability, BI platforms, and production delivery
Ensure People data products are designed around business meaning, usability, security, quality, scalability, and measurable value
Improve the partnership model between People, Technology, Analytics, AI Enablement, and operational owners
Lead Enterprise People Analytics and Workforce Intelligence, converting trusted workforce data into actionable insights, executive narratives, operational health metrics, and decision support
Deliver insights that help leaders understand workforce trends, talent risks, labor dynamics, employee experience, operational performance, transformation progress, and emerging business needs
Elevate analytics from reporting and dashboards to decision enablement, strategic insight, operational improvement, and measurable business action
Support OCEO, board, and CHRO analytical needs
Ensure analytics products are built on governed definitions, trusted data sources, and consistent interpretation