Model Risk Management Lead, Machine Learning
$185k - $245kAffirm
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 an intelligent, driven professional to join our Model Risk Management (MRM) team. This team seeks to establish, maintain and oversee an effective MRM framework to identify, quantify, monitor, mitigate and report on model risk throughout the company. You will have an outstanding opportunity to work cross-functionally to develop a profound understanding of models that drive critical business decisions, and add value to the company by mitigating risks due to ineffective model design or model misuse. What You’ll Do-
Perform independent challenges of machine learning models used for credit underwriting, credit risk, and/or fraud detection through thorough validation and ongoing monitoring
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Identify model weaknesses and opportunities for improvement
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Collaborate with model owners to remediate model validation findings
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Partner cross-functionally to implement and maintain the company’s MRM framework
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Partner with Internal Audit, Internal Controls, and Compliance to ensure timely resolution of audit and regulatory requests
What We Look For
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4-6 years of professional experience in related technical areas such as model development, model validation, data science
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Deep and broad knowledge and experience in machine learning modeling, credit underwriting, credit risk management, and/or fraud detection and fraud risk management
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Proven ability to work with script languages(e.g., Python) and large-scale dataset (e.g., SQL)
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Extensive experience with machine learning platforms and frameworks (e.g., scikit-learn, pyspark) and cloud-based coding environments and databases
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BS, MS, or PhD in a quantitative field such as Math, Data Science, Computer Science
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Oriented toward detail, curious about data/models/algorithms, skilled at critical thinking and problem solving
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Extraordinary interpersonal and verbal/written communication skills
Pay Grade - M
Equity Grade - 8
USA base pay range (all other U.S. states) per year: $164,000 - $224,000
#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.
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