The Senior Manager for Data & AI Governance position at Mercury is an enterprise-wide leadership role based in San Francisco, New York, Portland, or available remotely across the United States. This opportunity suits an experienced risk and governance professional who wants to shape the future of responsible artificial intelligence and data management in a fast-paced fintech environment.
Role Overview
Mercury is hiring a Data & AI Governance leader to build and spearhead an organization-wide program covering data and artificial intelligence. Reporting directly to the Chief Risk Officer, this professional will establish practical standards for how data and AI are owned, developed, utilized, protected, and monitored. The role bridges technical fluency with strong risk-management expertise, collaborating closely with Data, Engineering, Product, Information Security, Legal, Compliance, and business units. The mandate focuses on establishing enterprise governance and responsible-use principles, working alongside Model Risk Management and Information Security.
Key Responsibilities
Design and implement Mercury’s enterprise Data and AI Governance frameworks, operating models, policies, and standards.
Establish clear accountability for data ownership, stewardship, quality, lineage, classification, access, retention, and lifecycle management.
Build risk-based governance processes for AI use cases across their entire lifecycle, spanning intake, assessment, approval, implementation, monitoring, and retirement.
Formulate responsible-AI principles covering transparency, explainability, fairness, privacy, security, human oversight, reliability, and regulatory compliance.
Maintain a comprehensive enterprise inventory of critical data assets, AI use cases, and governance decisions alongside key stakeholders.
Define risk-based classifications depending on the sensitivity, materiality, complexity, and customer or regulatory impact of specific use cases.
Govern internally developed, vendor-provided, and embedded AI solutions, including generative artificial intelligence.
Partner with Product, Engineering, Data, and business teams to embed governance rules into development and change-management lifecycles.
Coordinate with Model Risk Management to identify AI use cases that meet model definitions and require model-risk oversight.
Partner with Information Security and Technology Risk on cybersecurity, data protection, access, architecture, resilience, and technology controls.
Collaborate with Legal and Compliance to address privacy, regulatory, contractual, and consumer-protection requirements.
Create workflows to identify, document, escalate, and remediate risks and issues related to data and AI.
Establish metrics and reporting mechanisms to provide management and Board committees with clear insights into data quality, AI adoption, governance maturity, incidents, and emerging risks.
Monitor evolving regulatory expectations and industry practices, translating them into proportionate governance measures.
Support relevant governance committees and foster a culture that treats data as an enterprise asset while encouraging responsible AI adoption.
Scale, build, and lead a high-performing Data & AI Governance team as the program matures.
Requirements
Minimum of 10 years of relevant professional experience spanning data governance, AI governance, technology risk, information governance, model risk, privacy, compliance, or related disciplines.
Demonstrated background in building or significantly enhancing a data governance, AI governance, or responsible-AI program.
Deep understanding of data ownership, stewardship, lineage, quality, metadata, classification, access, retention, and lifecycle management.
Working knowledge of machine learning and AI concepts, covering generative AI, large language models, training and inference data, bias, performance monitoring, explainability, and human oversight.
Experience designing practical, risk-based policies that function effectively within rapid technology environments.
Ability to distinguish between data governance, AI governance, model risk, information security, privacy, and compliance responsibilities.
Strong judgment enabling the successful balance of innovation, customer outcomes, regulatory expectations, and risk management.
Proven ability to influence executive leadership, technical teams, and business stakeholders without relying solely on formal authority.
Excellent written and verbal communication skills tailored for executive and Board audiences.
Experience managing cross-functional programs and leading teams.
Strong first and second line of defense judgment, understanding how enterprise risk should partner with and challenge engineering without taking direct ownership of first-line risks.
Pragmatic approach translating theoretical principles into workable, material risk-focused processes.
Technical curiosity combined with a sharp focus on business and customer outcomes.
Decisive and collaborative mindset capable of navigating ambiguity and constructive challenge.
Nice to Have
Experience working in a fintech, financial institution, technology firm, or other highly regulated industry.
Familiarity with banking regulations regarding data management, model risk, third-party risk, privacy, and information security.
Familiarity with established data and AI governance frameworks like DAMA-DMBOK, NIST AI RMF, ISO/IEC 42001, or comparable standards.
Experience governing third-party data, vendor AI solutions, and embedded AI capabilities.
Technical or analytical background in data architecture, data engineering, machine learning, analytics, or software development.
Experience operating in a company-building or bank-building environment.
Skills and Tools
Data Governance and Data Stewardship
AI Governance and Responsible AI Principles
Generative AI and Large Language Models (LLMs) Risk Management
Technology Risk and Information Governance
Regulatory Compliance and Privacy Frameworks
Model Risk Coordination
Cross-Functional Leadership and Stakeholder Influence
DAMA-DMBOK, NIST AI RMF, and ISO/IEC 42001 Frameworks
Salary and Benefits
Total rewards package includes base salary, equity through stock options or RSUs, and comprehensive benefits.
Base salary range for US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area is $225,800 to $282,300 USD.
Base salary range for US employees outside of these designated high-cost areas is $203,300 to $254,100 USD.
New hire compensation offers are determined based on candidate experience, expertise, geographic location, and internal peer pay equity.
About the Company
Mercury is a technology and financial services company built for ambitious businesses, operating as a fintech rather than an FDIC-insured bank. Banking services are provided through Choice Financial Group and Column N.A., Members FDIC. Mercury is an Equal Employment Opportunity employer committed to workplace diversity, inclusion, and providing reasonable accommodations throughout the hiring process.
How to Apply
To apply for this position, please visit the official Mercury careers page and submit your application online.
