Staff Auditor

Our Internal Audit Group is a worldwide function with 400+ team members and offices across nine countries within American Express. Our mission is to protect and enhance organizational value by providing independent, objective, risk-based assurance, advisory services and to influence the way the company manages risk. We are committed to growing our audit staff significantly as we continue to expand and enhance the Internal Audit Group. Our assurance and risk professionals have diverse backgrounds including internal controls, consumer compliance, technology, operational risk, financial accounting, data analytics, and banking operations. Our audit teams align to key risk areas and business units to ensure IAG can provide comprehensive and risk-based audit coverage. In addition, IAG has a Professional Practices group responsible for managing audit operations, quality, and standards; regulatory relations; reporting; training and professional development; and key internal capabilities and technologies. About the Role This Staff Auditor role supports the Internal Audit Group’s assurance coverage for Data Science, Model Risk, and Gen AI. The colleague will contribute to audit engagements by supporting planning and execution activities, evaluating control design and effectiveness, and providing actionable insights that strengthen model governance, model lifecycle management, validation, performance monitoring, and model risk assessment practices. About the Team Our Data Science and Model Risk/AI team plays a critical role in supporting Internal Audit by providing specialized assurance over models and AI/Gen AI solutions used across the enterprise. We deliver independent, risk-based evaluations that help auditors gain a clearer understanding of how models and AI are developed, governed, validated, and deployed within the business. By combining quantitative expertise with business and regulatory knowledge, the team helps uncover model risks, assess governance practices, and highlight opportunities to strengthen controls — ultimately enhancing the depth, rigor, and quality of Internal Audit's coverage over AI and model risk.