Senior Manager - Data & AI Governance
$150,000–$282,300 year
On-siteSan Francisco, California, United States
Job Summary
Develop Mercury's enterprise Data and AI Governance frameworks, policies, and operating model to establish clear accountability for data ownership, stewardship, quality, and lineage. Create risk-based governance processes for AI use cases across their lifecycle, from intake to retirement, while defining responsible-AI principles addressing transparency, fairness, and regulatory compliance. Maintain an inventory of material data assets and AI capabilities, partnering with Product, Engineering, Security, and Legal teams to embed governance into development and change-management processes. Coordinate with Model Risk Management to distinguish model requirements and establish metrics for management visibility into governance maturity and emerging risks. Monitor regulatory developments and facilitate decisions for governance forums, eventually leading a high-performing team to promote responsible AI adoption aligned with Mercury's risk appetite.
Required Qualifications
- 10+ years of relevant experience in data governance, AI governance, technology risk, information governance, model risk, privacy, compliance, or a related discipline
- Demonstrated 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 that can operate effectively in a fast-moving technology environment
- Ability to distinguish among data governance, AI governance, model risk, information security, privacy, and compliance responsibilities while coordinating effectively across those functions
- Strong judgment and the ability to balance innovation, customer outcomes, regulatory expectations, and risk management
- Demonstrated ability to influence senior executives, technical teams, and business leaders without relying solely on formal authority
- Excellent written and verbal communication skills, including the ability to explain complex technical and risk concepts to executive and Board audiences
- Experience leading teams and managing cross-functional programs with multiple stakeholders
- Strong 1LOD/2LOD judgment with an understanding of how enterprise Risk should govern, challenge, and partner with Engineering without taking ownership of 1LOD risks
- Pragmatic judgment: Translates principles into workable processes and focuses on material risks over theoretical ones
- Technical curiosity: Understands technical complexity while staying focused on business and customer outcomes
- Decisive and collaborative: Makes sound decisions amid ambiguity, moves quickly, and challenges constructively across teams
Desired Qualifications
- Experience within a fintech, financial institution, technology company, or other highly regulated environment
- Familiarity with banking regulatory expectations for data management, model risk, third-party risk, privacy, consumer protection, and information security
- Experience with recognized data- and AI-governance frameworks and standards, such as 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 operating in a company-building or bank-building environment
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