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Salary: USD 152,000 - 210,000 / annual
Chime, a fintech company, is seeking an experienced Credit Risk Data Scientist to lead credit strategy for new-to-Chime applicants across the member lifecycle. You will own credit strategy starting with Instant Loans for prospects and extending to future unsecured products such as credit cards and lines of credit.
Key responsibilities include:
- Develop and evolve channel-specific credit policies (pre-approval, prescreen, direct mail, open application, referrals, 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 data (e.g., Experian), alternative data, and internal Chime data to underwrite applicants with no prior Chime relationship; build credit models and policies hands-on in partnership with the DSML team
- Lead test-and-learn initiatives: design and read out champion/challenger tests and controlled ramps, quantifying trade-offs among approvals, losses, direct deposit conversion, and lifetime value
- Partner with Finance and Strategy to size new channels, forecast approval funnels, vintage losses, and unit economics; set launch criteria, guardrails, and expansion triggers
- Collaborate with data teams to build data infrastructure, monitoring, and dashboards (first payment default, delinquency, vintage and roll rates) to 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 bank partners to document, approve, and govern credit policies
- Mentor and collaborate with other credit risk data scientists to develop strategies, share knowledge, and raise the team's analytical bar
You will operate with a high degree of ownership, be data-driven, and serve as a trusted cross-functional partner with product, growth, data engineering, machine learning, and analytics teams, interacting with business stakeholders across many departments.
REQUIREMENTS:
- Master's degree (required) in Statistics, Economics, Engineering, Math, Finance, Computer Science, or another quantitative discipline; PhD is a plus
- 7+ years of analytical or data science experience in Financial Services, preferably at a FinTech company
- 4+ years of experience building and managing risk for unsecured credit products such as installment loans, lines of credit, or credit cards; acquisition/underwriting experience strongly preferred
- Hands-on experience with credit bureau data and prescreen, pre-approval, or direct mail credit programs
- Experience with credit furnishing, bankruptcies, delinquency, and write-off policies, and working knowledge of consumer lending regulation (FCRA, ECOA/Reg B, fair lending, adverse action)
- Excellent SQL and Python skills, advanced Microsoft Excel skills, and experience working in Looker or similar business intelligence tool
- Strong grounding in statistics and machine learning for credit, including scorecards/gradient-boosted models, swap-set analysis, vintage analysis, and experiment design
- Hands-on, detail-oriented leader with exceptional communication skills who can explain trade-offs to executives and defend the math behind them
- Ability to work in a fast-paced, complex environment and meet ambitious deadlines while ensuring flawless completion
- Strong passion for Chime's mission and solving challenging analytical problems for the business
- Nice to have: subprime or near-prime lending, affiliate or marketplace lending, credit card line management, or cash-flow/alternative-data underwriting experience
