Senior Manager - Data & AI Governance

Mercury is seeking a Data & AI Governance leader to build and spearhead an enterprise-wide governance program for data and artificial intelligence. Reporting to the Chief Risk Officer, this leader will establish practical standards for how data and AI are owned, developed, used, protected, and monitored across the organization.

The ideal candidate combines strong governance and risk-management experience with sufficient technical fluency to work effectively with Data, Engineering, Product, Information Security, Legal, Compliance, and business teams.

Key Responsibilities:

• 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.
• Maintain an enterprise inventory of material data assets, AI use cases, and related governance decisions.
• Partner with Product, Engineering, Data, and business teams to embed governance requirements into development and change-management processes.
• Coordinate with Model Risk Management to determine when an AI use case meets the definition of a model.
• Partner with Information Security, Technology Risk, Legal, and Compliance on data protection, regulatory, and privacy requirements.
• Build and lead a high-performing Data & AI Governance team as the program matures.

Qualifications:

• 10+ years of relevant experience in data governance, AI governance, technology risk, information governance, model risk, privacy, or compliance.
• Demonstrated experience building or materially enhancing a data governance, AI governance, or responsible-AI program.
• Working knowledge of AI and machine-learning concepts, including generative AI, large language models, training and inference data, and explainability.
• Experience developing practical, risk-based policies and governance processes in a fast-moving technology environment.
• Strong judgment, executive presence, and excellent communication skills.