Analytics Lead, Full Stack (Credit Analytics)

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. 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. The Credit team works cross-functionally with Machine Learning, Product, Engineering, Capital Markets, and Commercial teams to responsibly manage the risk profile of the business. We’re looking for a thoughtful, driven individual who wants to learn, grow, and solve hard problems. The team’s mandate is to enable sustainable growth while closely managing the profitability and resilience of our portfolio. As Affirm continues on an exciting growth trajectory; thinking through credit policies for new initiatives and products, shaping ongoing testing and experimentation, and being ready for navigating through any exogenous changes will be important problems to tackle. The ideal candidate brings exceptional analytical rigor, deep credit domain expertise, and the ability to influence stakeholders across both technical and non-technical teams. You thrive in ambiguity, can translate complex regulatory and economic insights into actionable credit strategies, and are comfortable operating at both strategic and execution levels. Come join us in our mission to change consumer finance through better data and technology, lower costs, and increased transparency while providing the best customer experience! 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. Pay Grade - M Equity Grade - 8 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and

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 visualization, 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.