Staff Credit Risk Analyst

As a Staff Risk Analyst, you'll turn information into insights through analytics, data science, and experimentation to help the company achieve tremendous growth. You'll represent risk analytics for credit risk management, with a focus on limit/max policy, member retention, and forecasting. This is a remote role in the US, however those local to Mountain View (headquarters) will require in-office work 2 days a week.

Responsibilities

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; Monitor deployed models in production, tracking performance and stability over time and flagging drift or degradation; Partner with Product to understand customer anecdotes and pain points, and design risk policy with customer experience in mind

Requirements

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

Benefits

Equity; Benefits