Quantitative Analytics Manager, Affirm Bank Model Governance

About the role

Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. We're seeking a professional with 7+ years of experience in credit/fraud modeling, model validation, or quantitative analytics to join our Bank Model Risk Management (MRM) team. Your role will involve full-stack model validation, advanced quantitative monitoring, remediation, and regulatory liaison.

Responsibilities

• Conduct rigorous, independent validations of sophisticated credit/fraud models—including machine learning and traditional statistical models—focusing on conceptual soundness, data integrity, and performance stability.
• Develop automated, independent monitoring suites in Python to track Key Risk Indicators (KRIs), Key Performance Indicators (KPIs), population stability (PSI), and feature importance shifts in real-time.
• Partner with 1st-line Model Developers to drive the remediation of validation findings, ensuring models and strategies are not only compliant but mathematically robust.
• Partner with Internal Audit, Internal Controls, and Compliance to facilitate the timely resolution of audit and regulatory requests.
• Support the model validation requirements for Bank-owned models.

Requirements

• 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 (specifically pandas, scikit-learn, statsmodels) for replicative modeling and backtesting.
• Mastery of SQL for wrangling large-scale, distributed datasets and performing complex data lineage audits.
• Natural problem-solver with a meticulous eye for detail, a deep curiosity for how strategies perform, and sharp critical-thinking skills.
• Exceptional interpersonal and communication skills, with a proven ability to translate complex technical ideas for any audience.

Qualifications

• Advanced degree in Finance, Statistics, Computer Science, or a related field.
• Experience working with large-scale, distributed datasets.
• Knowledge of financial regulations and compliance standards.

Skills

• Python programming (pandas, scikit-learn, statsmodels).
• SQL for data wrangling and complex data lineage audits.
• Statistical analysis and modeling techniques.
• Model validation and risk management methodologies.
• Communication and collaboration skills.

Benefits

• Base Pay Grade - O
• Equity Grade - USA 12
• Base Pay Range: $195,000 - $255,000 (USA base pay range)
• Remote-first work environment
• Competitive benefits package including health care coverage, flexible spending wallets, time off, ESPP, and more

Pay

Base Pay Grade - O

Schedule

Remote-first work environment