Global Head of Data & AI Governance, SVP

State Street

. Establish and operate enterprise-wide governance, risk, and regulatory oversight for Data, AI, and Agentic AI .

Posted 10/16/2026full-timeUnited StatesLead💰 $225,000 - $337,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in establishing and operating enterprise-wide governance, risk, and regulatory oversight for Data, AI, and Agentic AI, while ensuring data quality and compliance with regulatory standards. Proficient in defining policies, standards, and control frameworks that support effective data governance and management.

Highest-signal resume keywords

Enterprise-Wide GovernanceData GovernanceAI Risk ClassificationRegulatory EngagementData Quality Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ManagementData StewardshipData LineageRoot Cause AnalysisRegulatory ComplianceAI Inventory ManagementControl FrameworksTiered Approval ProcessesData Quality StandardsModel Risk Management

Industry Keywords

Agentic AIGenAIResponsible AIBCBS 239NIST AI Risk Management FrameworkData AccountabilityData ArchitectureAI and ML Use CasesRegulatory OversightData Quality Measurement

About the role

Key responsibilities & impact

Establish and operate enterprise-wide governance, risk, and regulatory oversight for Data, AI, and Agentic AI
Define, maintain, and evolve enterprise-wide policies, standards, and control frameworks
Ensure governance applies across the full lifecycle of data and AI assets
Partner with lines of business to define and maintain the Data and AI governance target state
Translate enterprise governance principles into domain-specific actionable models
Provide governance leadership into Data & AI roadmaps without owning delivery or architecture decisions
Establish and operate the enterprise framework for authoritative data sources
Designate approved and trusted data sources and resolve conflicts between competing sources
Ensure lineage, data quality, fitness for purpose, and consistent use of authoritative sources
Institutionalize the enterprise data governance operating model and embed data accountability into business processes
Own the enterprise inventory of AI initiatives across AI, GenAI, ML, and Agentic AI
Design and operate streamlined, tiered approval processes for AI types
Monitor and improve approval processes to reduce friction and late-stage escalation
Partner with Model Risk Management and route applicable AI and ML use cases to MRM
Define data quality measurement, monitoring, and control standards
Own enterprise data issue and incident processes, including root cause analysis, remediation tracking, and escalation
Act as the single enterprise point of contact for regulators, audit, and external Data and AI inquiries
Assess emerging regulatory expectations and drive early alignment
Coordinate and participate in active regulatory efforts relating to data, technology, and AI
Lead regulatory examinations, findings, and remediation programs such as BCBS 239 and MRAs
Convert regulatory learnings into durable governance and process improvements
Partner with Data Architecture, Data & AI Platforms, enablement teams, and business leaders
Continuously evolve governance practices with regulatory and technology change

Requirements

What you’ll need

Experience establishing and operating enterprise-wide governance, risk, and regulatory oversight for Data, AI, and Agentic AI
Knowledge of data governance and data management
Knowledge of AI, GenAI, and Agentic AI
Knowledge of Responsible AI and AI risk classification
Knowledge of third-party and vendor AI usage
Experience defining enterprise policies, standards, and control frameworks
Experience managing the full lifecycle of data and AI assets
Experience partnering with lines of business to define Data and AI governance target states
Experience with authoritative data sources, data ownership, and data stewardship
Experience resolving conflicts between competing data sources
Knowledge of data lineage, data quality, and fitness for purpose
Experience operating enterprise data governance operating models
Experience managing key data elements and critical data assets
Experience with AI inventories, classifications, and definitions
Knowledge of the NIST AI Risk Management Framework
Experience designing and operating tiered AI approval processes
Experience routing AI and ML use cases to Model Risk Management
Knowledge of Model Risk Management requirements
Experience defining enterprise data quality standards and managing data incidents
Experience with root cause analysis, remediation tracking, and escalation
Experience with regulatory, audit, and supervisory engagement
Experience leading regulatory examinations, findings, and remediation programs, including BCBS 239 and MRAs
Experience partnering with Data Architecture, Data & AI Platforms, enablement teams, and business leaders
Ability to maintain independence from delivery while shaping enterprise design decisions

Benefits

Comp & perks

Retirement savings plan (401K) with company match
Basic life insurance
Medical insurance
Dental insurance
Vision insurance
Long-term disability insurance
Optional additional insurance coverages
Paid vacation leave
Paid sick leave
Short-term disability
Family care responsibilities leave
Employee Assistance Program
Incentive compensation, including eligibility for annual performance-based awards
Certain tax-advantaged savings plans
Inclusive development opportunities
Flexible work-life support
Paid volunteer days
Employee networks