EarnIn is hiring a

Staff Credit Risk Analyst

Palo Alto, United States

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.

This is a hybrid position; this individual should expect to be in the office (Palo Alto, CA) 2 days per week minimum. The US base salary range for this full-time position is $198,000 - $242,000 + equity + benefits. Our salary ranges are determined by role, level, and location.

Position Summary:

Our Risk team has taken a unique approach to risk management, portfolio management, and interacting with our community members. You will have the opportunity to turn information into insights through analytics, data science, experimentation and help the company achieve tremendous growth. This role would be the representative of risk analytics for credit risk management.

What You'll Do:

  • Proactively explore data and identify opportunities to refine our risk management strategies
  • Conduct pattern analysis by researching and analyzing risk trends and patterns, provide valuable information for use in building risk-prevention methods
  • Define performance metrics and develop reports to monitor risk mitigation performance
  • Integrated decision making in the business area considering broader economic P&L, brand and people impact 
  • Work closely with machine learning team to improve risk models with business insights and past experience 
  • Work cross-functionally with Machine Learning, Product, Engineering, Operations to mitigate risk
  • Evaluate innovative data sources to solve individual identity risk and transaction risk

What We're Looking For:

  • An expert with SQL and experienced with Python
  • 8+ years relevant experience in a credit risk analytics role in financial industry
  • Working knowledge of the fundamentals of fintech risk. Have an understanding of industry risk trends, including familiarity with risk strategy development
  • Communicate metrics and data clearly and able to translate analytical insights to business metrics
  • Ability to apply statistics and probability concepts to split testing or LTV estimation 
  • Strong interpersonal skills and are able to work cross-functionally in the team environments
  • Ability to think creatively and thrive in a fast-paced, dynamic, often ambiguous work environment

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 on the basis of 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.

 

 

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