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American Express is a New York financial services company founded in 1850 as an express freight business that became a payments network and card issuer. Unlike the four-party networks it competes with, it issues most of its own cards and operates its own network, which lets it earn merchant discount revenue as well as interest and annual fees, and supports a premium rewards proposition built on travel and lounge access. Its business spans consumer and small business cards, corporate payments, merchant acquiring and travel services, and it is a component of the Dow Jones Industrial Average.

The Global Risk & Compliance Organization (GRC) is an independent risk management function, led by the Chief Risk Officer, with the objective of ensuring that American Express operates in a safe, sound, and fully compliant manner with all applicable regulatory expectations. GRC creates and maintains the overall risk management framework, performs independent risk management assessments, and monitors applicable risks.

Colleagues at GRC are passionate about our commitment to drive the Company’s goals of growth and progress by creating a culture of risk awareness and proactivity around regulatory matters.

About the Role

The Model Risk Management Group (MRMG) is seeking a highly motivated analyst to support independent validation and governance of Credit Risk related models and Non-Model Tools. The role provides an opportunity to work closely with model developers, business partners, and senior risk leaders to ensure models and tools are conceptually sound, analytically robust, and compliant with internal governance standards and regulatory expectations. The successful candidate will contribute to strengthening model risk management practices while gaining exposure to regulatory capital planning, financial forecasting, and enterprise risk management.

  • Support independent validation of CFR models, including CCAR PD, EAD and LGD models and Non-Model Tools.

  • Review model methodology, assumptions, data, implementation, and performance to assess conceptual soundness and ongoing suitability.
  • Perform independent analytical testing, benchmarking, sensitivity analysis, and replication to effectively challenge first-line model development teams.
  • Evaluate model documentation and governance against internal standards and regulatory expectations, identifying gaps and recommending improvements where appropriate.
  • Track validation findings and support review of remediation evidence to ensure timely and sustainable closure.
  • Prepare clear, concise validation reports and communicate findings to model developers, stakeholders, and senior leadership.
  • Partner with cross-functional teams to support regulatory exams, internal audits, annual reviews, model changes, and special governance initiatives.
  • Contribute to research and continuous improvement initiatives that enhance validation methodologies, analytical techniques, and governance processes.
  • Bachelor's or Master's degree in Statistics, Mathematics, Economics, Finance, Engineering, Computer Science, Operations Research, or a related quantitative discipline.
  • Strong analytical and problem-solving skills with the ability to interpret quantitative results and communicate insights effectively.
  • Experience with Python, SQL, SAS, R, or similar analytical tools.
  • Understanding of statistical modeling, forecasting techniques, regression analysis, or machine learning fundamentals.
  • Excellent written and verbal communication skills.
  • Ability to manage multiple priorities while delivering high-quality work in a collaborative environment.
  • Should be flexible to work in 1:00 pm to 9:30 pm shift.

Preferred Qualifications

  • Experience in model development, model validation, model risk management, or quantitative analytics within financial services.
  • Familiarity with CCAR, CECL, IFRS 9, stress testing, regulatory capital planning, or financial forecasting models.
  • Knowledge of model governance, validation methodologies, and regulatory guidance (e.g., SR 11-7).
  • Experience working with large datasets and applying statistical techniques to solve business problems.
  • Demonstrated ability to exercise independent judgment while building strong partnerships across business and risk functions.
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