Lead AI Governance Specialist

TIAA • Iselin, NJ

1d • $121,000 - $165,000 • Onsite

About The Position

The Lead Data Quality and Governance Analyst manages large projects and processes involving the assessment, improvement, and governance of data quality and ongoing fitness for purpose. The role ensures data quality is maintained so data can effectively support business processes. As a subject matter expert in data quality and governance, this position directs the design and implementation of master data management solutions to maintain a common, firm-wide data standard. The role coaches, reviews, and delegates work to lower-level team members and influences the team to implement new processes and methodologies as needed.

The position leads firm-wide data standards implementation and strengthens data governance capabilities across the data lifecycle. It supports master data business processes, systems, data coordination, and integration; oversees reporting and dashboards for business metrics and decision-making; monitors data quality metrics and audits; recommends improvements; and communicates the business impact of data quality issues to management.

The role requires experience designing governance frameworks in regulated industries, aligning cross-functional control and compliance stakeholders, running pilots with measured outcomes, understanding AI/ML lifecycle and model-risk concepts, and preparing auditable procedures and functional requirements. Preferred qualifications include Model Risk Management experience or certification, experience with workflow automation or GRC tools, and partnering with technical teams to translate procedures into system logic.

Requirements

• Bachelor's degree required.
• At least 5 years designing or redesigning multi-stakeholder governance frameworks in a regulated industry, with an example spanning design, pilot, and operational SOP and describing the relevant system analysis or architecture context.
• Documented experience facilitating structured working sessions with at least four distinct control or compliance functions to align on a shared framework or policy, including an example of resolving conflicting requirements.
• Experience piloting a process or framework change, measuring it against predefined metrics, and providing specific before-and-after results.
• Working knowledge of AI/ML lifecycle and model risk terminology, including tiering, materiality thresholds, and validation, and ability to explain conceptually how an AI/ML system progresses from development to deployment; coding or model-building experience is not required.
• Demonstrated ability to produce auditable procedural documentation, such as SOPs, decision-rights charts, and escalation paths, and functional requirements documents for a separate technical team.
• Related skills: business acumen, business analysis, business process understanding, change management, collaboration, communication, continuous improvement, data analysis, data-driven business intelligence, data management, data visualization, executive presence, influence, project management, and storytelling.
• Sedentary work.

Nice To Haves

• 7 or more years of work experience preferred.
• Formal certification or direct work experience in Model Risk Management, such as SR 11-7 or an equivalent regulatory framework.
• Experience writing functional requirements implemented in a workflow automation or GRC tool, with the ability to name the tool or platform.
• Experience partnering with technical implementation teams to translate SOPs into system logic or workflow automation without personally architecting the system.

Responsibilities

• Lead implementation of tools and processes to maintain firm-wide data standards.
• Strengthen data governance capabilities to maintain high data quality throughout the data lifecycle and ensure data controls support business objectives.
• Ensure business process, system support, and data quality governance for master data through data coordination and integration, supporting efficient processes and consistent data flows to business and stakeholders.
• Oversee development of reports and dashboards to identify business metrics, trends, and analytical needs, and optimize reporting for operational and management decision-making.
• Monitor data quality metrics, execute data quality audits, and advise on improvements to master data processes.
• Evaluate master data management metrics and recommend opportunities to strengthen enterprise data integrity, quality, and availability.
• Review and contribute to management reports that quantify and articulate the business impact of data quality issues.
• Coach, review, and delegate work to lower-level team members and influence the team to implement new processes and methodologies.

Benefits

• Superior retirement program.
• Competitive health, wellness, and work-life offerings supporting physical, emotional, and financial well-being.
• Compensation may include participation in an incentive program linked to performance, depending on the role.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior