Quantitative Analytics Lead

Affirm Affirm · Fintech · Canada, United States · Remote · Internal Audit

This role focuses on the Model Risk Management (MRM) team within Affirm's Enterprise Risk & Internal Audit department. The primary responsibility is to perform independent challenges and ongoing monitoring of machine learning models used for credit underwriting, credit risk, and fraud detection. This involves identifying model weaknesses, collaborating with model owners for remediation, and partnering cross-functionally to maintain the MRM framework. The role also involves ensuring timely resolution of audit and regulatory requests.

What you'd actually do

  1. Perform independent challenges of machine learning models used for credit underwriting, credit risk, and/or fraud detection through thorough validation and ongoing monitoring
  2. Identify model weaknesses and opportunities for improvement
  3. Collaborate with model owners to remediate model validation findings
  4. Partner cross-functionally to implement and maintain the company’s MRM framework
  5. Partner with Internal Audit, Internal Controls, and Compliance to ensure timely resolution of audit and regulatory requests

Skills

Required

  • 4-6 years of professional experience in related technical areas such as model development, model validation, data science
  • Deep and broad knowledge and experience in machine learning modeling, credit underwriting, credit risk management, and/or fraud detection and fraud risk management
  • Proven ability to work with script languages(e.g., Python) and large-scale dataset (e.g., SQL)
  • Extensive experience with machine learning platforms and frameworks (e.g., scikit-learn, pyspark) and cloud-based coding environments and databases
  • BS, MS, or PhD in a quantitative field such as Math, Data Science, Computer Science
  • Oriented toward detail, curious about data/models/algorithms, skilled at critical thinking and problem solving
  • Extraordinary interpersonal and verbal/written communication skills

What the JD emphasized

  • independent challenges
  • model validation
  • ongoing monitoring
  • machine learning models
  • credit underwriting
  • credit risk
  • fraud detection
  • model risk management
  • MRM framework
  • audit and regulatory requests

Other signals

  • model risk management
  • model validation
  • machine learning models
  • fraud detection
  • credit underwriting