Data Analyst, Credit Risk

About the Role

We are looking for a highly analytical and strategic Data Analyst of Credit Risk to support risk strategy for MyPay, Chime’s innovative product that provides members with early access to their earned wages. In this role, you will be the cornerstone of our MyPay risk function, balancing rapid product growth with responsible risk management and loss mitigation.

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 your deep technical expertise to build data-driven solutions. You will also directly manage, mentor, and grow a team of talented Data Analysts to execute on complex analyses and experimentation.

The base salary offered for this role and level of experience will begin at $109,000.00 and up to $150,000.00. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role, you can expect to

Support the end-to-end credit risk lifecycle for the MyPay product, 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 seamlessly into the member experience and align on financial targets.

Develop robust dashboards and reporting frameworks to track portfolio performance, loss metrics, and the financial health of the MyPay program.

To thrive in this role, you have

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 a 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).

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