Head of Data Trust, Risk & Responsible AI

Global Payment Holding Company•Alpharetta, GA

4d•Onsite

About The Position

The Head of Data Trust, Risk & Responsible AI sets and enforces enterprise standards to ensure data and AI are safe, compliant, trustworthy, and audit ready. This leader owns governance frameworks, drives policy implementation, and manages lifecycle controls for models and agents, including comprehensive Model Risk Management (MRM).

Requirements

12+ years in Data Governance, Risk Management, Audit, Compliance, or Responsible AI within highly regulated industries; 5+ years in senior leadership.
Proven experience building and executing governance programs in high-stakes, regulated environments.
Working knowledge of model risk management and AI lifecycle control frameworks.
Ability to balance risk controls with innovation enablement and business agility.
Strong stakeholder management skills with experience influencing C-level executives and engineering teams.
Experience in payments, banking, or financial services regulatory environments required.
Bachelor's degree required
Candidates must be legally authorized to work for any employer in the United States on a full-time basis without the need for current or future immigration sponsorship.

Nice To Haves

JD, advanced degree in a quantitative field, or relevant certifications preferred.

Responsibilities

Own enterprise Data & AI governance, including policy implementation, operating model, and oversight forums.
Lead model risk and lifecycle controls for regulated environments: approvals, validation, monitoring, change control, and documentation.
Establish data stewardship, quality, metadata, lineage, and observability programs to ensure transparency of data and AI assets.
Enforce Responsible AI requirements: fairness, explainability, safety, privacy, human oversight, and ethical review.
Partner with Legal, Compliance, Privacy, Security, Audit, and Risk to align controls to regulations and internal standards.
Implement enterprise scorecards and reporting for data quality, governance adherence, AI control compliance, and remediation progress.
Drive cultural adoption through training, playbooks, and governance embedded into delivery and platform workflows.
Manage governance tooling strategy and implementation across metadata, catalog, lineage, policy enforcement, and monitoring.
Maintain a curated inventory of all AI implementations in production, ensuring governance and risk protocols are followed.