Bank Model Risk & Quant Analytics Lead (Remote)

Affirm; Madison (WI); On-site; USD 195,000 - 255,000; Full time

Benefits offered by this job

Health care coverage

Flexible Spending Wallets

Time off

ESPP

Job summary

Affirm is seeking an experienced Bank Model Risk Management professional to lead independent validations of complex credit and fraud models, including machine learning and traditional statistics. The role emphasizes cross-functional work with developers, risk, and compliance to ensure robust, compliant models across the organization.

You will build automated monitoring in Python, focusing on drift and model performance, and drive remediation of findings in partnership with 1st-line teams,

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 (pandas, scikit-learn, statsmodels) for replicative modeling and backtesting.
• Mastery of SQL for wrangling large-scale datasets and data lineage audits.
• Natural problem-solver with meticulous attention to detail and strong critical thinking.
• Exceptional interpersonal and communication skills with the ability to translate complex ideas.

Responsibilities

• Full-Stack Model Validation of credit/fraud models—ML and traditional stats.
• Develop automated Python monitoring for KRI/KPI drift, PSI, and feature importance shifts.
• Remediate validation findings with model developers to ensure robustness and compliance.
• Coordinate with Audit, Controls, and Compliance to resolve audit/regulatory requests.
• Support the Bank Model Risk Management function and model validation requirements for bank-owned models.

Skills

Python

SQL

Model Validation

Credit/Financial Risk Modeling

Data Analysis

Communication Skills

Interpersonal Skills

Tools

Pandas

scikit-learn

statsmodels

Job description

Affirm is seeking an experienced Bank Model Risk Management professional to lead independent validations of complex credit and fraud models, including machine learning and traditional statistics. The role emphasizes cross-functional work with developers, risk, and compliance to ensure robust, compliant models across the organization.

You will build automated monitoring in Python, focusing on drift and model performance, and drive remediation of findings in partnership with 1st-line teams,