Finance/Credit Quantitative Model Risk Manager

Remote Canada 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. We’re looking for a sharp, driven quantitative professional to join our dynamic Model Risk Management (MRM) team. This is your chance to dive deep into the models that power our most critical business decisions. 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 data science, finance, and risk, this role is for you. What You’ll Do Conduct rigorous, independent validations of sophisticated models across finance, treasury, credit, and analytics, through in‑depth review, testing and ongoing monitoring to ensure their accuracy and integrity Identify key model weaknesses and highlight opportunities for improvement, helping teams build stronger, more powerful tools Collaborate with teams across the business to drive the remediation of validation findings Partner with model owners and developers to implement and enhance our company‑wide MRM framework, ensuring it remains effective and innovative Work closely with our Accounting, Internal Controls, and Compliance teams to ensure we meet and exceed all audit and regulatory expectations What We Look For 6+ years of professional experience in a technical role like model development, model validation, or data analytics Deep knowledge of ALM, treasury, and corporate finance. Experience with credit risk is a strong plus Hands‑on ability to script in languages like Python and wrangle large‑scale datasets with SQL A BS, MS, or PhD in a quantitative field such as Quantitative Finance, Math, or Data Science A natural problem‑solver with a meticulous eye for detail, a deep curiosity for how models work, and excellent critical‑thinking skills Exceptional interpersonal and communication skills, with a proven ability to translate complex technical ideas for any audience Base Pay & Equity Base Pay Grade – O Equity Grade – 6 Employees new to Affil now come in at the start of the pay range. Affil 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 monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, you may be eligible for equity rewards offered by Affil Holdings, Inc. (parent company). CAN base pay range per year: $170,000 – $220,000 Remote Policy Affil 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. Affilers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affil office. A limited number of roles remain office‑based due to the nature of their job responsibilities. Benefits Health care coverage – Affil 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 Affil at a discount Inclusion & EEO 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, Affil will consider for employment qualified applicants with arrest and conviction records. #J-18808-Ljbffr