Model Risk Management Lead, Machine Learning

Affirm

Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$185,000–$245,000 / yr
Posted
7 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $225k
This role $215k
$171k most similar roles pay here $275k

This role pays less than 55% of similar roles. Most pay $197,925–$251,750 — the shaded band above. At the midpoint, this role pays about $215k versus about $225k for comparable roles.

Based on 240 similar postings.

Employer

About Affirm

Affirm is a buy-now, pay-later (BNPL) financial technology company that offers point-of-sale installment loans to consumers, allowing them to split purchases into fixed monthly payments with transparent terms. Industry: Financial Technology & Consumer Lending

Affirm currently has 61 open roles on FindRole.

Listed pay typically runs $195,000–$255,000 across 61 roles with salary data.

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View all roles at Affirm

At a glance

TL;DR · Model Risk Management Lead, Machine Learning

Join our Model Risk Management team as a Quantitative Analytics Lead, where you will play a critical role in establishing and maintaining an effective model risk management framework. Your daily responsibilities include independently challenging machine learning models used for credit underwriting, fraud detection, and credit risk through validation and monitoring, identifying weaknesses and opportunities for improvement, collaborating with model owners to remediate findings, and partnering cross-functionally to implement the MRM framework. You will need 4-6 years of experience in related fields, proficiency in Python and SQL, expertise with platforms like scikit-learn and PySpark, and a strong background in quantitative disciplines such as Math or Data Science. This role demands meticulous attention to detail, analytical skills, and excellent communication abilities, all while addressing significant business risks at scale.

What you'll do

  • Perform independent challenges of machine learning models used for credit underwriting and fraud detection.
  • Identify weaknesses and opportunities for improvement in existing models.
  • Collaborate with model owners to remediate validation findings effectively.
  • Implement and maintain the company’s Model Risk Management framework.
  • Partner with Internal Audit, Compliance, and other teams to ensure regulatory compliance.

What we're looking for

  • 4-6 years of experience in model development, validation, or data science.
  • Deep expertise in machine learning modeling and credit risk management.
  • Proficiency with Python, SQL, and cloud-based coding environments.
  • Experience using machine learning platforms like scikit-learn and PySpark.
  • BS, MS, or PhD in a quantitative field such as Math, Data Science, Computer Science.
  • Strong critical thinking skills and ability to communicate complex ideas clearly.

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