Conduct in-depth portfolio and trend analysis to identify key performance drivers, emerging risks, and growth opportunities
Develop insights and recommendations to optimize underwriting policies, credit decisioning, and fraud risk strategies
Monitor and evaluate key credit metrics (e.g., approval rates, loss rates, delinquency trends, vintage performance) and communicate findings to stakeholders
Partner with Analytics, Data Science, and Data Engineering to build scalable data models, automated reporting, and repeatable performance monitoring frameworks
Support strategy testing and measurement efforts (e.g., champion/challenger experiments) to improve decision quality and customer outcomes
Translate complex analyses into clear, concise narratives and recommendations for leadership and cross-functional partners
Mentor team members on analytical best practices and help strengthen a data-driven culture across the organization

Requirements

Bachelor’s degree in math, economics, statistics, or other quantitative field
5+ years of experience in an analytical role
2+ years of consumer lending experience, either at a large bank or a fintech
Proficiency in SQL, R or Python
Proficiency in Data Lake, DBT or Git
Excellent written, verbal, and interpersonal communication skills
Strong sense of ownership with the ability to drive projects forward independently in a fast-paced environment

Benefits

equity
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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

portfolio analysistrend analysisunderwriting policiescredit decisioningfraud risk strategiescredit metricsdata modelsautomated reportingchampion/challenger experimentsanalytical best practices

Soft Skills

communication skillsmentoringownershipindependencecollaborationnarrative developmentproblem-solvingadaptabilityleadershipdata-driven culture