Remote

• 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

• 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

Be an Early Applicant Remote Hiring Remotely in US 174K-246K Annually Senior level Remote Hiring Remotely in US 174K-246K Annually Senior level Own credit risk policy optimization, limit-setting, experimentation, forecasting, and portfolio monitoring. Design A/B tests, build performance reporting and dashboards, identify emerging risks, and partner with Machine Learning, Product, Engineering, and Operations to improve risk models and customer outcomes. Monitor deployed model performance and translate analytical findings into actionable policy and product changes. The summary above was generated by AI About EarnIn

As one of the first pioneers of earned wage access, our passion at EarnIn is building products that deliver real-time financial flexibility for those with the unique needs of living paycheck to paycheck. Our community members access their earnings as they earn them, with options to spend, save, and grow their money without mandatory fees, interest rates, or credit checks.

We’re fortunate to have an incredibly experienced leadership team, combined with world-class funding partners like A16Z, Matrix Partners, DST, Ribbit Capital, and a very healthy core business with a tremendous runway. We’re growing fast and are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth journey., The base salary range for this full-time position is $173,928 - $245,773 plus equity and benefits. Our salary ranges are determined by role, level, and location. This is a remote role in the US, however those local to Mountain View (headquarters) will require in-office work 2 days a week.