Quantitative Analytics Manager, Affirm Bank Model Governance
$220,000–$280,000 year
RemoteCalifornia, United States or New York, United States
Job Summary
Conduct rigorous, independent validations of sophisticated credit and fraud models, focusing on conceptual soundness, data integrity, and performance stability. Develop automated monitoring suites in Python to track KRI/KPI drift, population stability, and feature importance shifts in real-time. Partner with model developers to drive remediation of validation findings and collaborate with Internal Audit, Controls, and Compliance to resolve audit and regulatory requests. Support the build-out of the Bank Model Risk Management function by validating Bank-owned models. This role requires 7+ years of experience in Credit/Fraud/Financial Risk Modeling with expert-level Python and SQL proficiency. Base pay ranges from $195,000 to $280,000 depending on location, with no visa sponsorship available. The position is fully remote.
Required Qualifications
- 7+ years of professional experience in a highly technical capacity, such as Credit/Fraud/Financial Risk Modeling, Model Validation, or Quantitative Analytics
- 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
- A 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
- Must be able to work remotely
- Must be willing to occasionally work out of their assigned Affirm office
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