Sr. Credit Risk Analyst - Remote and Hybrid Options Available

Remote, USA Full-time Posted 2026-05-04
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Job Overview:


We are seeking an experienced Sr. Credit Risk Analyst to join our team at Workwarp. As a Sr. Credit Risk Analyst, you will play a critical role in developing strategies to optimize consumer credit risk, marketing, and portfolio growth. This is a unique opportunity to work with a talented team and make a significant impact on our business.


Key Responsibilities:



  • Develop and implement underwriting strategies using statistical and data mining analyses to maximize unit economics and reduce defaults

  • Establish and maintain Key Performance Indicators (KPIs) to measure portfolio profitability and unit economics

  • Analyze and recommend optimal product parameters, such as loan amounts and interest rates, based on target economics and performance metrics

  • Collaborate with internal business teams to implement portfolio strategies and present findings to senior management and credit committee members

  • Develop testing frameworks and analyze results to inform portfolio decisions


Requirements:



  • Bachelor's degree in Statistics, Economics, Business, Operations Research, Mathematics, or a related quantitative field; Master's degree preferred

  • 2-4 years of experience in highly quantitative roles, with a focus on developing and recommending strategies using quantitative methods

  • Proficiency in SAS, R, Python, SQL, and Excel, with experience handling large datasets

  • Excellent written and verbal communication skills, with strong problem-solving and organizational abilities


What We Offer:



  • Competitive salary and benefits package

  • Opportunity to work remotely or on a hybrid schedule

  • Collaborative and dynamic work environment

  • Professional development and growth opportunities


How to Apply:


If you are a motivated and experienced credit risk professional looking for a new challenge, please submit your application. We can't wait to hear from you!


Apply Now

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