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Salary: USD 195,000 - 280,000 / annual
Affirm is seeking a Quantitative Analytics Manager to join the Bank Model Risk Management (MRM) team. This role is responsible for establishing, maintaining, and overseeing an effective MRM framework to identify, quantify, monitor, mitigate, and report on model risk across the organization.
Key responsibilities include conducting full-stack model validation of sophisticated credit and fraud models—both machine learning and traditional statistical approaches—with focus on conceptual soundness, data integrity, and performance stability. You will develop and maintain automated, independent monitoring suites in Python to track KRI/KPI drift, population stability (PSI), and feature importance shifts in real-time across production models.
The role involves partnering with first-line model developers to drive remediation of validation findings, ensuring models and strategies are mathematically robust and compliant. You will also serve as a liaison with Internal Audit, Internal Controls, and Compliance to facilitate timely resolution of audit and regulatory requests. Additionally, you will support the buildout of the Bank Model Risk Management function and validate requirements for bank-owned models.
Required qualifications include 7+ years of professional experience in a highly technical capacity such as Credit/Fraud/Financial Risk Modeling, Model Validation, or Quantitative Analytics. You must have deep understanding of the consumer credit lifecycle and/or fraud detection, technical familiarity with loss forecasting, fraud prediction, and stress-testing frameworks. Expert-level proficiency in Python (pandas, scikit-learn, statsmodels) for replicative modeling and backtesting is essential, along with mastery of SQL for large-scale data wrangling and complex data lineage audits. Strong problem-solving skills, meticulous attention to detail, and exceptional interpersonal and communication abilities are critical for translating complex technical concepts to diverse audiences.
