Quantitative Analytics Manager, Affirm Bank Model Governance

What You'll Do

What We Look For

• 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.
• Base Pay Grade - O
• Equity Grade - USA 12
• Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.