Data & AI Governance leader

Job Description

Senior Manager – Data & AI Governance | Mercury

The Tone:
This is a full-time role at Mercury, with location flexibility for US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area, as well as remote options across the US and Canada. Mercury is a fintech company that provides banking services through partner banks. This leader will build and spearhead an enterprise-wide governance program for data and artificial intelligence, establishing practical standards to ensure responsible innovation and management of these critical assets across the organization.

The TL;DR
• Role: Full Time
• Location: Remote (US & Canada), New York City, Los Angeles, Seattle, San Francisco Bay Area
• Pay: $203300–$282300 USD yearly
• Team: Reports to the Chief Risk Officer
• Mission: Establish practical standards for how data and AI are owned, developed, used, protected, and monitored across the organization.
• Tech Stack: DAMA-DMBOK, NIST AI RMF, ISO/IEC 42001

What You’ll Actually Do
• Develop and implement Mercury’s enterprise Data and AI Governance frameworks, policies, standards, and operating model.
• Establish clear accountability for data ownership, stewardship, quality, lineage, classification, access, retention, and appropriate use.
• Create a risk-based governance process for AI use cases across their lifecycle, including intake, assessment, approval, implementation, monitoring, and retirement.
• Develop responsible-AI principles and standards addressing transparency, explainability, fairness, privacy, security, human oversight, reliability, and regulatory compliance.
• Partner with Product, Engineering, Data, and business teams to embed governance requirements into development and change-management processes.

The Must-Haves
• Background: 10+ years of leadership experience in data governance, AI governance, technology risk, information governance, model risk, privacy, or compliance.
• Experience: Demonstrated success building or materially enhancing an enterprise data governance, AI governance, or responsible-AI program, including leading teams and managing cross-functional initiatives.
• Skills: Strong understanding of data ownership, quality, lineage, metadata, classification, access, and lifecycle management; working knowledge of AI/ML concepts including generative AI, explainability, and bias; ability to distinguish and coordinate across data governance, AI governance, model risk, information security, and privacy responsibilities; excellent written and verbal communication for executive and Board audiences; pragmatic judgment to balance innovation, customer outcomes, regulatory expectations, and risk management.
• Bonus: Experience within a fintech, financial institution, technology company, or other highly regulated environment; familiarity with banking regulatory expectations; experience with DAMA-DMBOK, NIST AI RMF, ISO/IEC 42001, or comparable frameworks; experience governing third-party data or vendor AI solutions; technical or analytical experience in data architecture, data engineering, machine learning, or software development.