Senior Manager - Data & AI Governance

Responsibilities

• Develop and implement enterprise Data and AI Governance frameworks, policies, standards, and operating models.
• Establish accountability for data ownership, stewardship, quality, lineage, classification, access, retention, and appropriate use.
• Create risk-based governance for AI use cases across intake, assessment, approval, implementation, monitoring, and retirement.
• Develop responsible-AI principles addressing transparency, explainability, fairness, privacy, security, human oversight, reliability, and regulatory compliance.
• Maintain inventories of material data assets, AI use cases, and governance decisions.
• Define risk-based classifications and requirements based on sensitivity, complexity, materiality, and customer or regulatory impact.
• Establish governance for internally developed, vendor-provided, embedded, and generative AI capabilities.
• Embed governance requirements into product, engineering, data, business, and change-management processes.
• Coordinate with Model Risk Management on model classification and model-risk requirements.
• Partner with Information Security, Technology Risk, Legal, and Compliance on data protection, cybersecurity, privacy, consumer protection, regulatory, contractual, and technology-control considerations.
• Develop processes to identify, document, escalate, and remediate data- and AI-related risks and issues.
• Establish metrics and reporting for management and Board committees covering data quality, governance maturity, AI adoption, exceptions, incidents, and emerging risks.
• Monitor regulatory developments, industry practices, and emerging risks related to data and AI.
• Support Data and AI governance forums and committees and facilitate documented decisions.
• Build and lead a Data and AI Governance team as the program matures.
• Promote responsible, transparent, and risk-aligned use of data and AI.

Requirements

• 10+ years of relevant experience in data governance, AI governance, technology risk, information governance, model risk, privacy, compliance, or a related discipline.
• Experience building or materially enhancing a data governance, AI governance, or responsible-AI program.
• Strong understanding of data ownership, stewardship, quality, lineage, metadata, classification, access, retention, and lifecycle management.
• Working knowledge of AI and machine-learning concepts, including generative AI, large language models, training and inference data, explainability, bias, performance monitoring, and human oversight.
• Experience developing practical, risk-based policies and governance processes in a fast-moving technology environment.
• Ability to distinguish data governance, AI governance, model risk, information security, privacy, and compliance responsibilities while coordinating across functions.
• Strong judgment balancing innovation, customer outcomes, regulatory expectations, and risk management.
• Ability to influence senior executives, technical teams, and business leaders without relying solely on formal authority.
• Excellent written and verbal communication skills, including explaining technical and risk concepts to executive and Board audiences.
• Experience leading teams and managing cross-functional programs.
• Strong first-line/second-line-of-defense judgment and understanding of enterprise Risk's role in governing and challenging Engineering.
• Pragmatic, decisive, collaborative, and technically curious approach.

Preferred Qualifications

• Experience in fintech, financial services, technology, or another highly regulated environment.
• Familiarity with banking regulatory expectations for data management, model risk, third-party risk, privacy, consumer protection, and information security.
• Experience with DAMA-DMBOK, NIST AI RMF, ISO/IEC 42001, or comparable frameworks.
• Experience governing third-party data, vendor AI solutions, and embedded AI capabilities.
• Technical or analytical experience in data architecture, data engineering, machine learning, analytics, or software development.
• Experience in a company-building or bank-building environment.

Compensation and Benefits

• Total rewards include base salary, equity (stock options/RSUs), and benefits.
• US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $225,800–$282,300 USD base salary.
• US employees outside of New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $203,300–$254,100 USD base salary.
• Offers are based on experience, expertise, geographic location, and internal pay equity.