We’re looking for a driven, analytically-minded professional to join the Growth Analytics team. The team is responsible for the research, reporting and experimentation necessary to build outstanding repayment products. The ideal candidate will have strong analytical and problem solving skills, prior background in credit or financial services industry, an eagerness to work cross-functionally, curiosity to learn more every day, and patience to work through difficult and ambiguous problems.

What you'll do

• Identify and deliver analysis to influence operational and product strategy for loan repayment in compliance with regulatory requirements
• Monitor repayment metrics (collections and recoveries performance, delinquency rates, auto pay, etc) and actively influence vendor strategies to improve repayment at optimal cost
• Identify third parties, data solutions, and other innovative ways to evolve the repayment experience
• Develop and execute end-to-end analytics roadmap for repayment by partnering closely with product, credit, operations, engineering and other teams to grow the Affirm network
• Collaborate with cross-functional partners to understand their business priorities, formulate and execute end-to-end analytics workflow that includes defining critical metrics, data instrumentation and gathering, experimentation, analysis, and building meaningful dashboards and forecasts
• Translate analytical outcomes and results into compelling narratives / presentations for multiple levels of leadership
• Lead a team of analysts to be effective in the role and deliver high-impact and business-driving work

What we look for

• 5+ years of proven ability in an analytical role in consumer collections or credit / risk domain
• Previous experience in leading impactful analytics teams
• Experience conducting experiments in partnership with the product team and performing data analysis on large unstructured data sets
• Experience with simultaneously balancing multiple workstreams and prioritizing team's roadmap
• Experience pulling and joining large data sets with SQL and performing analysis using tools such as Python, Notebooks, R, or Excel
• Proficiency in communicating research and analysis to technical and non-technical audiences
• An appreciation for qualitative and quantitative analysis and an admiration for good design
• Willingness to go out of you way to help teammates
• Enough laziness to find a faster way to do your least favorite tasks