Data and AI Governance Lead - Computing Services

Carnegie Mellon University (CMU) is seeking a dynamic, highly collaborative Data and AI Governance Lead to shape and operationalize the framework for how our institution manages, protects, and leverages its most critical data and AI assets. Unlike traditional management roles, this position does not oversee a direct team. Instead, you will act as the university's primary architect and facilitator of Data and AI Governance, working across academic and administrative units to drive progress through influence, partnership, and expert support.

You must be comfortable toggling between high-level strategy (policy-making and risk frameworks) and hands-on delivery (implementing metadata tools and assisting data stewards)

Key Responsibilities:

• Strategy & Framework Design
  :
  Lead the design and execution of CMU's Data and AI governance operating model. Define the policies, standards, and roadmaps that ensure data integrity, privacy, and the responsible use of AI across the university.
• Influence & Community Building
  :
  Build and enable a robust community of practice among distributed Data Stewards and AI practitioners. You will not have "command and control"; authority; success will depend on your ability to build trust, provide value to partners, and align departmental goals with university-wide standards.
• AI Governance & Risk: Design and operationalize AI governance controls, including model inventories, risk assessments, and ethical reviews. Partner with academic and administrative leads to ensure AI deployment is transparent, fair, and compliant with emerging regulations.
• AI Data Readiness: Transform our Data assets by establishing a unified metadata layer. You will act as the translator between business Data Analysts, SMEs, and our Data/Analytics Engineering teams, ensuring that business terminology is mapped accurately (e.g., ensuring an AI agent understands that a "Full-Time Student" in a financial aid context (12+ credits) is distinct from "Full-Time Equivalent (FTE)" used for state reporting or faculty workload so engineers can build accurate semantic models for varying audiences.
• Hands-on Operational Support
  : "Roll up your sleeves"; to help departments implement governance tooling. Assist in defining data lineage, improving data quality, and documenting metadata for complex institutional datasets.
• Cross-Functional Collaboration: Serve as the primary bridge between Information Technology, Information Security Office, the Office of the Provost, and various administrative and academic units. Translate complex technical governance requirements into actionable guidance for non-technical stakeholders.
• Metrics & Advocacy: Develop KPIs to track the adoption and health of governance practices. Regularly report progress to university leadership, advocating for the cultural shifts necessary to treat data as a strategic institutional asset.
• Other duties as assigned.

Flexibility, excellence, and passion are vital qualities within Computing Services. Inclusion, collaboration, and cultural sensitivity are valued competencies refore, we are in search of a team member who is able to effectively interact with a varied population of internal and external partners at a high level of integrity. We are looking for someone who shares our values and who will support the mission of the university through their work.

Required Qualifications:

• Experience
  : 5+ years of experience in data governance, data management, and experience in AI ethics/policy.
• The "Influence" Factor: Proven track record of leading large-scale initiatives in a federated or decentralized environment (e.g., Higher Ed, Healthcare, or complex R&D organizations) where progress is made through collaboration rather than direct authority.
• Strategic Communication: Ability to present complex risk and governance concepts to senior university leadership while being equally effective at coaching a departmental data coordinator on day-to-day data entry standards.
• Technical Depth: Familiarity with Data & AI lifecycle management, including experience with metadata management tools, data cataloging, and ML Ops/AI risk frameworks.
• AI Readiness: An understanding of AI data readiness, including how traditional machine learning and Agentic AI interact with structured and unstructured data.
• Technical Partnership: Experience partnering closely with Data Engineering and Analytics.

Preferred Qualifications:

• Experience specifically within a Research I university or a highly complex non-profit environment.
• Professional certification in Data Management (CDMP) or AI Governance (AIGP).
• Knowledge of global data privacy regulations (GDPR, FERPA, HIPAA) as they relate to both administrative data and academic research.

Why This Role?

This is a unique opportunity to revitalize a data governance program, incorporating AI, at one of the world's leading institutions for Artificial Intelligence. You will have the autonomy to shape the role, the platform to influence data and AI governance policies, and the satisfaction of…