Analytics Lead, Full Stack (Credit Analytics)

The Role

The Risk & Analytics team makes crucial decisions that direct Affirm’s business strategy. Our team designs and runs experiments to decide which product features to launch and which marketing campaigns to fund. We analyze performance not just to report on it, but to determine where to invest resources for maximum impact through building tools and analytical frameworks. We take ownership of the entire analytical lifecycle, from initial question to final business decision, ensuring Affirm grows efficiently and intelligently.

What You’ll Do

• 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.
• Monitor portfolio performance and macroeconomic trends that impact loan outcomes; proactively adjust underwriting and marketing strategies to mitigate risk.
• 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.
• Engage and coordinate with external stakeholders — including merchants, vendors, and regulatory bodies — to align credit risk practices, ensure compliance, and strengthen strategic partnerships.
• Oversee the development and execution of credit underwriting frameworks that balance growth, compliance, and risk mitigation goals.
• Drive cross-functional discussions to ensure new product launches and market entries are aligned with risk appetite, operational capabilities, and local regulations.

What We Look For

• Degree in Data Science, Computer Science, Engineering, Economics, or a related field, and 4+ years of experience (or equivalent senior-level experience)
• 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
• 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