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# Remote

- **Company:** Earnin
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $174,000.0 - $246,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Python (Programming Language), Machine Learning, SQL Databases
- **Published:** October 6, 2026
- **Apply:** https://www.builtincolorado.com/job/staff-risk-analyst/11512800?handler=ApplyRedirect

## About the Role

* 7+ years of experience in a credit risk analytics, decision science, or risk strategy role, ideally within fintech or consumer financial products
 * Expert in SQL; comfortable with Python for analysis and experimentation
 * Working knowledge of fintech risk fundamentals, including risk strategy development, limit/max policy, and portfolio monitoring
 * Experience designing and evaluating A/B tests or policy experiments, and translating results into recommendations
 * Comfortable working with forecasting or curve-based modeling (e.g., cash flow, loss, or usage forecasts)
 * Strong communicator who can translate analytical findings into clear, actionable business recommendations
 * Able to work cross-functionally with Machine Learning, Product, Engineering, and Operations
 * Ability to think creatively and thrive in a fast-paced, dynamic, and often ambiguous environment

## Description

* Own policy optimization for member credit limits, balancing retention, churn, and risk exposure
 * Design, run, and evaluate policy experiments and A/B tests, translating results into concrete policy changes
 * Own forecasting and reporting infrastructure that keeps risk and portfolio performance visible to stakeholders
 * Proactively explore data to identify opportunities to refine risk management strategies and surface emerging risk trends
 * Define performance metrics and build reports/dashboards to monitor policy and portfolio performance
 * Partner closely with Machine Learning, Product, Engineering, and Operations to translate analysis into shipped policy and product changes
 * Work closely with the Machine Learning team throughout the model development lifecycle, helping shape how risk models are built since you'll be a primary consumer of their outputs
 * Monitor deployed models in production, tracking performance and stability over time and flagging drift or degradation that should inform retraining or redesign
 * Partner with Product to understand customer anecdotes and pain points, and design risk policy with customer experience in mind alongside risk and business outcomes