Analytics Lead, Full Stack (credit Analytics)

Affirm Affirm · Fintech · United States · Remote · Point of Sale Analytics

This role focuses on leveraging advanced data analytics and machine learning techniques to optimize credit strategies and build scalable risk models within the fintech domain. The primary goal is to manage the risk profile of the business, enabling sustainable growth while closely managing profitability and resilience. The role involves collaborating with cross-functional teams, interpreting regulatory requirements, and driving data-informed decision-making.

What you'd actually do

  1. Leverage advanced data analytics to derive insights and optimize credit strategies across products and geographies.
  2. Partner with Engineering to design and build scalable risk models and credit risk capabilities.
  3. Monitor portfolio performance and macroeconomic trends that impact loan outcomes; proactively adjust underwriting and marketing strategies to mitigate risk.
  4. Collaborate closely with Product, Legal, and Compliance teams to interpret evolving regulatory and market requirements across jurisdictions, and translate them into credit policy, underwriting, and product design recommendations.
  5. Engage and coordinate with external stakeholders — including merchants, vendors, and regulatory bodies — to align credit risk practices, ensure compliance, and strengthen strategic partnerships.

Skills

Required

  • SQL, Python, or other scripting languages
  • Data mining, data visualisation, and statistical modeling
  • Applying machine learning techniques to credit risk management
  • Leveraging advanced analytics to develop and optimise credit strategies
  • Monitoring and interpreting model performance metrics across portfolios
  • Proven experience leading cross-functional initiatives that bridge Product, Legal, Compliance, and Engineering to align credit strategies with regulatory frameworks and business objectives.
  • Deep understanding of consumer lending regulations, fair lending principles, and regional market dynamics influencing credit policy and underwriting.
  • Ability to translate complex regulatory and economic insights into actionable credit and product strategies.
  • Demonstrated success mentoring high-performing analytical teams and driving data-informed decision-making at scale.
  • Exceptional communication skills with the ability to influence senior stakeholders across technical and non-technical functions.

Nice to have

  • Experience setting credit strategy for de novo products using Sandbox data, retrospective studies or archives
  • Experience in high-line unsecured lending, especially in the home improvement vertical

What the JD emphasized

  • Deep understanding of consumer lending regulations, fair lending principles, and regional market dynamics influencing credit policy and underwriting.
  • Ability to translate complex regulatory and economic insights into actionable credit and product strategies.
  • Proven experience leading cross-functional initiatives that bridge Product, Legal, Compliance, and Engineering to align credit strategies with regulatory frameworks and business objectives.

Other signals

  • Leverage advanced data analytics to derive insights and optimize credit strategies across products and geographies.
  • Partner with Engineering to design and build scalable risk models and credit risk capabilities.
  • Applying machine learning techniques to credit risk management
  • Monitoring and interpreting model performance metrics across portfolios