Affirm
Analyst
USARemotePosted Today$115,000 – $165,000
Full TimeSeniorRemoteUS
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Job Description
Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. About the Risk & Analytics
Key Highlights
- Point of Sale (POS): Optimize merchant and checkout performance to improve conversion, approvals, and unit economics across the purchase funnel.
- Direct to Consumer (DTC) / Card: Drive engagement, repeat usage, and lifecycle health across Affirm’s app, web, and card experiences.
- Fraud: Prevent and reduce fraud losses across the customer journey while maintaining a frictionless user experience.
- Core Analytics: Build the quantitative research, machine learning models, performance monitoring, and scalable data foundations that enable fast, economically sound decisions.
- Servicing: Enhance the post-origination customer experience by analyzing repayment behavior, collections strategies, and operational efficiency.
Qualifications
Required Qualifications
- 1–3 years of experience in an analytically driven role. Relevant internships or prior experience in consumer lending, fintech, or the broader financial services industry are highly valued.
- Degree in Data Science, Computer Science, Engineering, Economics, or a related quantitative field.
- Solid working knowledge of SQL, Python, or other scripting languages.
- Familiarity with data mining, data visualization, and foundational statistical modeling.
- Basic understanding of, or deep curiosity about, consumer lending regulations, fair lending principles, and how machine learning techniques apply to real-world business problems.
- Exceptional communication skills, humility, and the ability to collaborate effectively with cross-functional peers.
Skills & Technologies
Machine LearningGoSQLPython
About the Company
Affirm
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Job Details
Employment Type
Full Time
Experience Level
Senior
Salary Range
$115,000 – $165,000
Location
USA
Work Mode
Remote
Posted
Today
Country
US