Staff Risk Analyst

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.

Position Summary

Our Risk team takes a unique approach to risk management, portfolio management, and interacting with our community members. 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.

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.

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/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

• 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

What We're Looking For

• 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

#LI-Remote

At EarnIn, we believe that the best way to build a financial system that works for everyday people is by hiring a team that represents our diverse community. Our team is diverse not only in background and experience but also in perspective. We celebrate our diversity and strive to create a culture of belonging. EarnIn does not unlawfully discriminate based on race, color, religion, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, registered domestic partner status, sexual orientation, genetic information, or any other basis protected by local, state, or federal laws. EarnIn is an E-Verify participant.

EarnIn does not accept unsolicited resumes from individual recruiters or third‑party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or HR team.

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self‑identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiringprocess or thereafter. Any information that you do provide will be recorded and maintained in aconfidential file.

As set forth in EarnIn’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measurethe effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categoriesis as follows:

A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service‑connected disability.

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An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.

A Note on AI in the Hiring Process:

EarnIn may use Artificial Intelligence (AI)-powered tools during the hiring process, including tools that (i) generate summaries or notes for interviewers, (ii) review resumes, (iii) assist with scheduling interviews, (iv) help identify themes across candidate responses and profiles for a given role, and (v) assist with populating the interview scorecard.

Final hiring decisions are made by human interviewers and hiring managers.

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