Manager - Audit, Models SME

About the Internal Audit Group at American Express 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 manager role supports the Internal Audit Group’s assurance coverage for Data Science, Model Risk, and Gen AI. The colleague will support audit engagements, leading 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. Serve as Auditor in Charge (AIC) on audits, managing the audit engagement end-to-end, planning audit projects, defining objectives and scope, and coordinating with control groups, external auditors, stakeholders, and regulators to ensure effective execution; conduct L1 reviews; serve as the primary audit client contact Analyze / review audit results and documentation to evaluate effectiveness and efficiency, synthesizing audit findings Lead audit client meetings and walkthroughs Develop test steps, audit findings, and the audit report in accordance with IAG policies and procedures Guide team on how to validate and execute corrective actions / Management Action Plans (MAPs) are impactful, sustainable, and improve the control environment of the business unit Support business monitoring activities with audit leadership, tracking key metrics to identify control issues and trends; stay up to date with evolving industry trends, external news and regulatory changes, and analyze the impact to the business Delegate tasks to team members; guide auditors in assessing risks, evaluating control design, and executing audit tests; review and provide feedback on work papers Effectively coach, teach, mentor, and develop less experienced colleagues and co-sourced resources in geographically diverse locations across all aspects of their role, the audit and analytic lifecycle, audit methodology and best practices Conduct post-audit feedback discussions with audit team members to provide actionable feedback, support development, and recognize accomplishments Guide team to proactively and routinely communicate task status, roadblocks, challenges, suggesting potential solutions to the team 5+ years of audit experience or model development / validation experience Prior experience working at a Big Four / G-SIB Understanding of Model Risk Management (MRM) frameworks, including model governance, model lifecycle management, validation, performance monitoring, and model risk assessments. Understanding of model risks associated with model development, implementation, validation, monitoring, and ongoing use, including data quality, model performance, interpretability, model drift, and algorithmic bias. Demonstrates strong written and verbal communication skills to deliver deliverables with quality, and actionable value-add feedback to management on issues, opportunity areas, and deficiency solutions Effectively leads a team in a fast-paced environment to drive business results, utilizing related project management skills, employing creative thinking, and the ability to work on competing priorities Applies critical thinking to break-down complex problems into components, and solve using data analysis, process, risk control knowledge, and experience to drive risk-based conclusions and decisions Applies control theory and professional auditing practices throughout the audit lifecycle Understands regulations, regulatory risks, accounting, and financial industry best practices relevant to the business, including emerging technology and data considerations, and incorporates into the audit approach to enhance outcomes Preferred Qualifications Experience in Internal Audit, Model Risk Management, Model Validation, Quantitative Tools, Enterprise Risk Management, Data Science, Artificial Intelligence/ Machine Learning and Gen AI techniques, Data Analytics, or a related control function within the financial services industry. Knowledge of model risk regulatory frameworks and industry guidance, with the ability to assess the design and effectiveness of model governance, controls, and risk management processes. Understanding of regulatory expectations and industry guidance related to Model Risk Management, including SR 11-7, OCC model risk guidance, Basel frameworks, PRA Supervisory Statement 3/17, or comparable international regulatory frameworks. Experience or understanding of regulatory, credit risk, market risk, pricing, valuation, operational risk, stress testing (e.g., CCAR), CECL, or other enterprise risk models. Experience with data analytic tools, data visualization, key risk indicators (KRIs), key performance indicators (KPIs), information systems / technology, and scorecards / dashboards, etc. Interest in working with data, interpreting results, analytic best practices and experience with data analytics tools and data visualization Employment eligibility to work with American Express in the U.S. is required as the company will not pursue visa sponsorship for these positions.