VP, AI Data Risk Management

MUFG•Jersey City, NJ

9d•$134,000 - $193,000•Hybrid

About The Position

The Data Office is seeking a Vice President, AI Data Risk Management to help shape and strengthen the firm's AI governance framework from a data perspective. As organizations increasingly leverage artificial intelligence to drive innovation, improve customer experiences, enhance decision-making, and automate business processes, trusted and well-governed data has become foundational to managing AI risk. This role will serve as a key partner to business, technology, risk, compliance, model risk, legal, and governance teams to ensure that data supporting AI solutions is appropriately governed, controlled, transparent, and fit for purpose. The successful candidate will combine expertise in data management, governance, controls, and risk management to help establish a scalable framework for identifying, assessing, monitoring, and mitigating AI-related data risks across the enterprise. This is a senior individual contributor and team lead role with responsibility for influencing enterprise AI governance practices, supporting strategic AI initiatives, and helping drive responsible AI adoption throughout the organization.

Requirements

8+ years of experience in Data Management, Data Risk, Risk Management, Data Governance, Compliance, Audit, Technology Governance, Model Risk, or related disciplines.
Strong understanding of data quality, data controls, governance, and risk management practices.
Experience evaluating data-related risks and control effectiveness.
Ability to influence stakeholders across business, technology, risk, and governance functions.
Strong analytical, critical thinking, and problem-solving abilities.
Excellent communication and stakeholder management skills.
Demonstrated leadership experience through people management or leadership of significant cross-functional initiatives.
Bachelor's degree in Computer Science or a closely-related discipline, or an equivalent combination of formal education and experience

Nice To Haves

Experience supporting AI, machine learning, advanced analytics, or model governance programs.
Knowledge of AI governance, responsible AI principles, or emerging AI regulatory expectations.
Experience with data catalogs, data quality platforms, workflow tools, lineage solutions, or governance technologies.
Familiarity with model risk management, privacy programs, operational risk frameworks, or technology risk management.
Experience within a banking, financial services, or highly regulated environment.

Responsibilities

Partner with AI governance, technology, business, compliance, legal, model risk, privacy, and risk management teams to identify and manage data-related risks associated with AI solutions.
Assess risks associated with AI training data, inference data, reference data, metadata, synthetic data, and external data sources.
Help establish governance processes that promote the quality, integrity, transparency, lineage, and appropriate use of data throughout the AI lifecycle.
Evaluate whether data used in AI solutions is adequately documented, understood, governed, and monitored.
Support risk assessments for AI use cases and help identify potential data-related control gaps.
Monitor emerging AI data risks and recommend enhancements to governance and control practices.
Support the firm's AI governance framework by defining data management expectations for AI use cases.
Help establish policies, standards, and operating practices related to AI data management.
Partner with stakeholders to implement controls supporting responsible AI development and usage.
Assist in defining requirements for data sourcing, data ownership, data quality, lineage, monitoring, retention, and traceability.
Promote consistent governance practices across AI inventories, workflows, and approval processes.
Drive accountability for data used within AI solutions and AI-enabled business processes.
Improve transparency into how data supporting AI solutions is collected, transformed, governed, consumed, and monitored.
Help establish ownership and stewardship models for AI-related data assets.
Support management of critical data elements, business glossaries, data lineage, data quality controls, and AI-related inventories.
Partner with business teams to improve the availability and trustworthiness of data supporting AI initiatives.
Collaborate with Risk, Compliance, Legal, Privacy, and Audit teams to support evolving regulatory and governance expectations related to AI.
Support risk assessments, issue remediation efforts, control enhancements, and regulatory inquiries involving AI data practices.
Provide expertise and challenge regarding AI-related data controls and governance processes.
Help identify opportunities to strengthen oversight and reduce AI-related operational, compliance, and reputational risks.
Act as a trusted advisor to senior leaders on AI-related data risks and governance considerations.
Facilitate discussions across business and technology stakeholders to resolve data ownership, governance, and control challenges.
Help educate stakeholders on the importance of trusted data in supporting responsible AI adoption.
Lead and mentor a small team of analysts supporting AI governance and data management activities.