Risk Data Analyst, Imprint

• 4 years of experience in an analytical role with focus on collections, risk, or recoveries
• Strong SQL skills and experience working with large datasets (Snowflake, dbt, or similar a plus)including experience with external data integrations and log consumption. (
• Experience with dashboarding and visualization tools (Looker, Tableau, etc.)
• Familiarity with collections typologies (early-stage delinquency, chronic delinquency, roll rates, re-defaults, recovery strategies, etc.)
• Strong analytical, investigative, and problem-solving skills with the ability to connect data to real-world collections/ delinquency scenarios
• Excellent communication skills — able to translate findings into clear recommendations
• Comfort in a fast-paced startup environment where priorities shift quickly
• Experience in fintech, high-growth startups, or customer-facing data products

Desirable

• We’re looking for a Risk Data Analyst to join our Collections Risk Analytics team
• In this role, you’ll drive improvements in collections performance through in-depth analysis of delinquency trends, roll rates, and recovery outcomes - helping the team to identify actionable opportunities
• You’ll partner closely with Risk, Product, and Data teams to develop collections performance monitoring tools, design and test new collections and recovery strategies and support the development of predictive models that help Imprint stay ahead of rising delinquencies
• This is a high-impact role with strong visibility across the business, where you’ll leverage data to optimize collections effectiveness while ensuring a seamless and customer-centric experience
• Design, build, and maintain portfolio performance dashboards (including the development of internal collections manual review dashboards) that track key collections metrics, alert on anomalies and communicate potential risks to leadership
• Perform deep-dive analyses on delinquency and repayment behaviors, providing actionable recommendations to strengthen collections strategies and controls
• Partner with Product and Engineering to design and test collections process automation, and tooling
• Support collections model development by preparing performance datasets, validating model outputs, and tracking predictive accuracy over time
• Forecast collections losses, delinquency rates, roll rates, and recoveries using statistical and data-driven methods. Provide insights into emerging risk trends and recommend mitigation strategies
• Assist in designing, building, and maintaining scalable data pipelines and infrastructure across batch and streaming systems, as well as supporting external data integrations and consuming logs from external third-party vendors
• Collaborate with cross-functional teams to strengthen overall collections performance and stay current on industry delinquency trends and best collections practices