Financial Model Risk Management Lead

Affirm is a financial technology company that provides a clear, predictable way to pay over time, with no hidden fees or surprises. The Enterprise Risk & Internal Audit department protects Affirm's operations and long-term success by identifying, assessing, and monitoring risk across the business.

The Model Risk Management (MRM) team serves as Affirm's second line of defense, establishing and overseeing an effective model risk management framework to identify, quantify, monitor, mitigate, and report on model risk throughout the company.

• Perform independent challenges of financial and analytics quantitative models — including ALM, allowance/loss forecasting, loan transition models (LTM), corporate financial planning models, take-up and engagement models, and related decision-support analytics — through rigorous validation and ongoing monitoring.
• Lead end-to-end validation engagements on high-complexity, high-criticality models.
• Identify model weaknesses, limitations, and opportunities for improvement; articulate findings clearly to technical and non-technical stakeholders.
• Collaborate with model owners and stakeholders across Finance, Quantitative Research, and Growth Analytics to remediate validation findings and strengthen model governance.
• Partner cross-functionally to implement and maintain the company's MRM framework.
• Partner with Internal Audit, Internal Controls, Accounting, and Compliance to ensure timely resolution of audit, regulatory, and examiner requests.

• 4–6 years of professional experience in related technical areas such as model development, model validation, quantitative finance, or data analytics — with meaningful exposure to financial and/or analytics model validation.
• Deep and broad knowledge of corporate finance, treasury, ALM, and/or actuarial/statistical forecasting.
• Experience in credit underwriting, credit risk management is a plus.
• Proven ability to work with scripting languages (e.g., Python) and large-scale datasets (e.g., SQL); comfort reviewing models built in Excel, Python, Databricks, or similar environments.
• Experience with statistical modeling, time-series forecasting, simulation, and/or machine learning techniques as applied to finance and analytics use cases.
• BS, MS, or PhD in a quantitative field such as Quantitative Finance, Financial Engineering, Mathematics, Statistics, Economics, Computer Science, or Data Science.
• Detail-oriented and intellectually curious about data, models, and business context; skilled at critical thinking and structured problem-solving.
• Extraordinary interpersonal and verbal/written communication skills — able to influence model owners, present to senior stakeholders, and navigate cross-functional remediation.

CAN base pay range per year: $145,000 - $205,000. Total compensation 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. Benefits also include flexible time off, generous holiday calendars, and an employee stock purchase plan (ESPP).

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