Staff Credit Risk Analyst

Overview

Staff Risk Analyst on EarnIn's Risk team, turning data into insights through analytics, data science and experimentation to drive credit risk management, with a focus on limit/max policy, member retention and forecasting.

What you'll do

• 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 and 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.

What you'll need

• 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.

Details

• Full-time position with a base salary range of $173,928 – $245,773, plus equity and benefits.
• Remote role in the US.
• Those local to Mountain View (headquarters) will require in-office work 2 days a week.