Underwriting/Credit Model Risk Senior Manager - Machine Learning

affirm

Remote Canada

Posted Aug 14, 2026

Other
Remote
Internal Audit

Job description

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.

About Enterprise Risk & Internal Audit

The Enterprise Risk & Internal Audit department protects Affirm’s operations and long-term success. We identify, assess, and monitor risk across the business. Our work includes internal audits, regulatory assurance, fraud prevention, and crisis planning. The team maintains strong controls, tracks key risk indicators, and ensures readiness for external reviews. We uphold accountability, transparency, and resilience to support responsible growth.

About the Team

We're looking for a sharp, driven quantitative professional to join our dynamic Model Risk Management (MRM) team. In this role, you will oversee the underwriting and credit risk validation sector - the most critical pillar of Affirm’s MRM framework. This is a unique position designed for a seasoned technical leader who can build, mentor, and manage a high-performing team while remaining deeply hands-on, personally executing validations of our most complex machine learning models.

You'll collaborate across the company to shape a best-in-class risk framework, ensuring our models are robust, reliable, and ready for the future. If you're passionate about the intersection of finance, credit risk, and data science, this role is for you.

What You'll Do:

Sector Leadership & Team Management: Oversee the underwriting and credit risk validation sector. Lead, mentor, and manage a team of talented quantitative professionals while setting the strategic direction for this critical risk domain.
Hands-On Model Validation: Execute rigorous, independent validations of sophisticated machine learning models across underwriting and credit risk management.
Technical Review: Evaluate conceptual soundness, data integrity, and performance stability through comprehensive testing, in-depth reviews, and continuous monitoring to ensure model accuracy.
Identification & Remediation: Detect critical model weaknesses and identify areas for improvement; collaborate with model owners and developers to track and resolve validation findings.
Framework Enhancement: Partner with cross-functional stakeholders to implement and refine the enterprise-wide Model Risk Management (MRM) framework, ensuring it remains robust and innovative.
Audit & Compliance: Coordinate with Accounting, Internal Controls, and Compliance teams to ensure all model activities meet or exceed internal standards and regulatory expectations.

What We Look For:

Experience: 9+ years of professional experience in a highly technical role, such as model development, model validation, or quantitative analytics.
Domain Expertise: Deep understanding of machine learning modeling, underwriting, and credit risk management.
Technical Proficiency: Advanced ability to script in Python and expertise in using SQL to manipulate and analyze large-scale, complex datasets.
Leadership & Influence: Proven track record of hiring, managing, and mentoring quantitative teams. Ability to transition seamlessly between high-level strategic oversight and detailed, hands-on technical work.
Education: A BS, MS, or PhD in a quantitative discipline such as Statistics, Quantitative Finance, Mathematics, or Data Science.
Analytical Mindset: A natural problem-solver with a meticulous eye for detail, a deep curiosity regarding model mechanics, and sharp critical-thinking skills.
Communication: Exceptional interpersonal skills with a proven ability to distill and translate complex technical concepts for diverse audiences.

Pay Grade - Q

Equity Grade - 7

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. Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)

CAN base pay range per year: $201,000 - $261,000

#LI-Remote

Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities.

We’re extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:

Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents
Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses
Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge
ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount

We believe It’s On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.

[For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records.

By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.