Head of Quant Analytics & Model Risk (Remote)

Affirm; Dallas (TX); On-site; USD 227,000 - 315,000; Full time

Benefits offered by this job

Health care coverage

Employee stock purchase plan (ESPP)

Flexible time off

Job summary

Affirm is seeking a senior quantitative leader to oversee the underwriting and credit risk validation sector within its Model Risk Management team. You will mentor a high-performing group while personally validating complex ML models and ensuring robustness across risk domains.

The ideal candidate has 9+ years in technical roles, strong ML, underwriting, and credit risk knowledge, and advanced Python/SQL skills. This remote-first role offers flexible work arrangements across the United States.

Qualifications

• 9+ years in a highly technical role such as model development, validation, or quantitative analytics.
• Deep understanding of machine learning modeling, underwriting, and credit risk management.
• Strong Python and SQL skills for handling large-scale datasets.

Responsibilities

• Oversee the underwriting and credit risk validation sector; lead and mentor a team of quantitative professionals.
• Execute rigorous, independent validations of sophisticated machine learning models in underwriting and credit risk.
• Evaluate conceptual soundness, data integrity, and performance stability through testing and monitoring.
• Identify weaknesses and drive remediation with model owners and developers.
• Partner to enhance the enterprise-wide Model Risk Management framework and ensure regulatory readiness.
• Coordinate with Accounting, Internal Controls, and Compliance to meet standards.

Skills

Python

SQL

Machine Learning

Leadership

Model Risk

Quant Analytics

Education

BS/MS/PhD in Statistics/Mathematics/Data Science

Job description

Affirm is seeking a senior quantitative leader to oversee the underwriting and credit risk validation sector within its Model Risk Management team. You will mentor a high-performing group while personally validating complex ML models and ensuring robustness across risk domains.

The ideal candidate has 9+ years in technical roles, strong ML, underwriting, and credit risk knowledge, and advanced Python/SQL skills. This remote-first role offers flexible work arrangements across the United States.