Director, Data & AI Governance - Flex Location

UPS

2d•Hybrid

About The Position

We're hiring a Director, Data & AI Governance to lead how UPS scales AI governance, adoption, and organizational change across the enterprise. This is a transformation and adoption role first. The role helps scale responsible AI adoption across one of the world's largest logistics and supply chain enterprises. The Director owns the governance operating model and is accountable for evolving existing governance practices into a repeatable, enterprise-wide capability that enables responsible AI adoption at enterprise scale. The Director sets the direction for the operating model, builds the cross-functional coalition needed to make it stick, and drives measurable adoption and business value. The role helps the enterprise accelerate AI adoption by making governance repeatable, scalable, and trusted. Frameworks, policies, and controls matter here—but as means to an end. The real mandate is change: scaling responsible AI practices across a large, federated enterprise and building trust in how we govern data and AI.

Requirements

Bachelor's degree in Information Systems, Computer Science, Data Analytics, Business, Engineering, Risk Management, or a related field.
10+ years in Data or AI Governance, Information Security, Risk, Information/Data Management, Analytics, or Compliance.
7+ years leading teams, programs, and enterprise initiatives.
Proven record scaling an enterprise governance program and driving adoption and organizational change across a large, federated organization while influencing executive stakeholders.
Experience designing operating models and implementing automation that improves quality, consistency, and team capacity.
Direct experience working with executive leadership and governance boards.
Experience implementing or scaling AI governance platforms such as IBM watsonx.governance or comparable solutions.
Experience implementing frameworks aligned to NIST AI RMF, ISO/IEC 42001, and emerging AI regulation.
Track record building executive dashboards and reporting for governance councils, review boards, or Executive Leadership Teams.
Executive communication
Strategic planning
Organizational change management
Cross-functional leadership
Stakeholder management
Program leadership
Decision-making under ambiguity
Coaching & mentoring
Data & AI governance platforms
Data catalog & metadata tools
Analytics & reporting
Cloud (Azure, AWS, GCP)
Data architecture concepts
AI/ML concepts and lifecycle management.
Must be a U.S. Citizen or National of the U.S., an alien lawfully admitted for permanent residence, or an alien authorized to work in the U.S. for this employer.

Nice To Haves

Master's preferred.

Responsibilities

Define the long-term vision and maturity roadmap for enterprise Data & AI Governance.
Define and evolve the enterprise AI governance operating model—roles, decision rights, workflows, and the target state for how governance runs at scale.
Scale AI governance from a collection of reviews, controls, and processes into an enterprise capability embedded across the AI lifecycle.
Drive the adoption of automation and workflow orchestration to improve governance effectiveness and scalability.
Lead the adoption and evolution of enterprise AI governance platforms, including IBM watsonx.governance, to support governance, monitoring, and oversight.
Set the multi-year roadmap and OKRs for scaling governance across business units, and report progress to executive leadership.
Drive enterprise adoption of governance practices through change management, communications, education, and executive sponsorship.
Partner with business and technology leaders to accelerate AI adoption by embedding governance into delivery and removing barriers while maintaining appropriate governance, risk, and compliance standards.
Grow AI fluency and governance awareness across the organization.
Define governance approaches for emerging AI capabilities including GenAI, intelligent agents, and reusable enterprise AI assets.
Oversee AI use case intake, risk assessment, approval, monitoring, documentation, and lifecycle management at enterprise scale.
Establish controls for model governance, explainability, transparency, fairness, accountability, and human oversight.
Chair AI Review Boards and executive governance forums and bring the operating model to life through them.
Track emerging AI and data regulation and translate impact into operating-model and roadmap changes.
Partner with Legal, Privacy, Compliance, and Security to meet internal and external requirements.
Align governance controls to NIST AI RMF, ISO/IEC 42001, and the EU AI Act.
Lead enterprise data governance strategy and operating model, including stewardship, ownership, quality, metadata, lineage, lifecycle, and governance practices that support AI-ready data.
Report governance maturity and key performance indicators to leadership.
Build, mentor, and develop a high-performing governance team.
Set goals, metrics, and development plans; model accountability and continuous improvement.