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Salary: USD 109,000 - 150,000 / annual
Chime is seeking a Data Analyst, Credit Risk to support risk strategy for MyPay, an innovative earned wage access product. You will be the cornerstone of the MyPay risk function, balancing rapid product growth with responsible risk management and loss mitigation.
In this role, you will sit at the intersection of credit risk strategy and data science. You will own the underwriting, limit assignment, and loss forecasting strategies for MyPay, leveraging deep technical expertise to build data-driven solutions. You will directly manage, mentor, and grow a team of talented Data Analysts to execute on complex analyses and experimentation.
Key responsibilities include:
- Support the end-to-end credit risk lifecycle for MyPay, including underwriting policies, dynamic limit assignments, and repayment strategies
- Design, execute, and analyze rigorous A/B tests to optimize credit limits, user experience, and risk/reward trade-offs
- Utilize advanced statistical modeling and data science techniques to identify new risk signals, improve predictive models, and automate risk decisioning
- Partner closely with Product Management, Engineering, Data Science, and Finance to integrate risk strategies into the member experience and align on financial targets
- Develop robust dashboards and reporting frameworks to track portfolio performance, loss metrics, and financial health of the MyPay program
Chime is a financial technology company (not a bank) that provides user-friendly tools and intuitive platforms to help members take control of their finances. The company operates with an owner's mindset, emphasizing bold thinking, collaboration, and integrity.
Workplace: Four days per week in office (San Francisco), Fridays from home. Full-time position with bonus, competitive equity package, and comprehensive benefits including health, financial, and wellbeing coverage, generous vacation policy, annual wellness stipend, and up to 22 weeks of paid parental leave for birthing parents.
Requirements:
- 3+ years of experience in credit risk, data science, or advanced analytics, preferably within consumer lending, fintech, or earned wage access (EWA)
- Expert-level proficiency in SQL for complex data extraction and manipulation
- Strong programming skills in Python (Pandas, NumPy, Scikit-learn) for data analysis and predictive modeling
- Deep hands-on experience designing, launching, and analyzing A/B tests and multivariate experiments with strong grasp of underlying statistical concepts
- Solid understanding of consumer credit risk principles, loss forecasting, and unit economics
- Exceptional ability to translate complex data and technical concepts into actionable, high-level strategies for executive stakeholders
Nice-to-have:
- Advanced degree (Master's or PhD) in a quantitative field (Statistics, Mathematics, Economics, Computer Science, etc.)
- Prior experience working specifically with Earned Wage Access (EWA), cash advance, or short-term liquidity products
- Familiarity with modern data stacks (e.g., Snowflake, dbt, Looker)
