The opportunity
We are looking for an experienced Credit Risk Data Scientist who is data-driven, has strong analytical and technical skills, and operates with a high degree of ownership. In this role, you will lead the credit strategy that lets Chime lend to people before they have a…
What you'll do
Own credit strategy for new-to-Chime applicants across the member lifecycle,: starting with Instant Loans for prospects (top of funnel) and extending to future unsecured products such as credit cards and/or lines of credit
Develop and evolve channel-specific credit policies (pre-approval /: prescreen, direct mail, open application, referrals, and affiliates) that support growth while balancing risk, unit economics, and member experience
Design and continuously iterate acquisition, loan amount / line assignment,: pricing, line management, repayment, and collections strategies
Leverage credit bureau (e.g., Experian), alternative, and internal Chime data: to underwrite applicants with no prior Chime relationship; build credit models and policies hands-on and in partnership with our DSML team
Lead test-and-learn: design and read out champion/challenger tests and controlled ramps, and quantify trade-offs among approvals, losses, direct deposit conversion, and lifetime value
Partner with Finance and Strategy to size new channels and forecast approval: funnels, vintage losses, and unit economics; set launch criteria, guardrails, and expansion triggers
What they're looking for
- Collaborate with data teams to build data infrastructure and early-read: monitoring and dashboards (first payment default, delinquency, vintage and roll rates) that help senior management understand credit risk trends and exposures
- Work with cross-functional teams including DSML, Product, Design,: Engineering, and Decision Platform to test and implement risk models and strategies in production, including accurate adverse action reasons
- Partner with Compliance, Legal, Fair Lending, Model Risk Management, Fraud,: and our bank partners to document, approve, and govern credit policies
- Mentor and work collaboratively with other credit risk data scientists to: develop strategies, share knowledge, and raise the team's analytical bar