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Salary: USD 164,000 - 245,000 / annual
Affirm is seeking a Financial Model Risk Management Lead to join the Enterprise Risk & Internal Audit department. This role serves as a lead validator for Finance and Analytics models within Affirm's Model Risk Management (MRM) framework, which acts as the company's second line of defense against model risk.
Key responsibilities include performing independent challenges and rigorous validation of complex quantitative models including Asset-Liability Management (ALM), allowance/loss forecasting, loan transition models, corporate financial planning models, take-up and engagement models, and related decision-support analytics. You will lead end-to-end validation engagements on high-complexity, high-criticality models, identifying weaknesses and limitations while articulating findings clearly to both technical and non-technical stakeholders.
You'll collaborate cross-functionally with model owners and stakeholders across Finance, Quantitative Research, and Growth Analytics to remediate validation findings and strengthen model governance. The role also involves partnering with Internal Audit, Internal Controls, Accounting, and Compliance to ensure timely resolution of audit, regulatory, and examiner requests, and implementing and maintaining the company's MRM framework.
Required qualifications include 4–6 years of professional experience in model development, model validation, quantitative finance, or data analytics with meaningful exposure to financial and/or analytics model validation. You should have deep knowledge of corporate finance, treasury, ALM, and/or actuarial/statistical forecasting. Experience with credit underwriting and credit risk management is a plus.
Technical skills required: proficiency with scripting languages (Python), SQL, and large-scale datasets; comfort reviewing models built in Excel, Python, Databricks, or similar environments; and experience with statistical modeling, time-series forecasting, simulation, and/or machine learning techniques applied to finance and analytics.
Educational background should include a BS, MS, or PhD in a quantitative field such as Quantitative Finance, Financial Engineering, Mathematics, Statistics, Economics, Computer Science, or Data Science. Exceptional interpersonal and communication skills are essential, as you'll need to influence model owners, present to senior stakeholders, and navigate cross-functional remediation efforts.
