Remote Staff Risk Analytics Lead – Credit Policy

Remote; San Francisco (CA); Remote; USD 174,000 - 246,000; Full time

Job summary

EarnIn is seeking a Staff Risk Analyst to advance credit risk analytics for our earned wage platform. You will own policy design for credit limits, run experiments, and build forecasting dashboards to inform stakeholders.

You'll partner with Machine Learning, Product, and Engineering to translate insights into risk-aware product changes, monitor model performance, and drive data-driven decisions in a fast-paced fintech environment.

Qualifications

• 7+ years of credit risk analytics or risk strategy experience, preferably fintech or consumer finance.
• Strong SQL proficiency and ability to analyze data with Python.
• Experience designing and evaluating policy experiments and A/B tests.

Responsibilities

• Own policy optimization for member credit limits balancing retention, churn, and risk exposure.
• Design, run, and evaluate policy experiments and A/B tests; translate results to policy changes.
• Own forecasting and reporting infrastructure for risk and portfolio performance insights.
• Explore data proactively to refine risk strategies and surface emerging trends.
• Define performance metrics and build dashboards to monitor policy outcomes.
• Collaborate with ML, Product, Engineering, and Operations to ship policy changes.
• Work with ML to shape risk models; be a primary consumer of outputs.
• Monitor deployed models for drift, degradation, and retraining needs.
• Align risk policy with customer experience and business goals.

Skills

SQL

Python

Fintech risk

A/B testing

Forecasting

Cross-functional

Communication

Model monitoring

Job description

EarnIn is seeking a Staff Risk Analyst to advance credit risk analytics for our earned wage platform. You will own policy design for credit limits, run experiments, and build forecasting dashboards to inform stakeholders.

You'll partner with Machine Learning, Product, and Engineering to translate insights into risk-aware product changes, monitor model performance, and drive data-driven decisions in a fast-paced fintech environment.