Analyst, Early Career (Full Stack)

About the Role

As an Early Career Analyst in Affirm's Risk & Analytics organization, you will join one of several analytical teams working across the customer and merchant lifecycle. While the specific problems you tackle will depend on your eventual team placement, all Analyst I roles share a common foundation: using data to understand business performance, identify opportunities, and help Affirm make better decisions. You will learn the fundamentals of consumer lending while executing scoped analytical work under the guidance of senior analysts and managers. You will leverage SQL, Python, and modern analytical tools to help optimize business strategies, monitor performance, and turn complex data into actionable insights. You are a thoughtful, driven individual eager to build a strong technical foundation, learn how to navigate exogenous market changes, and integrate modern AI tooling to solve hard problems efficiently.

Key Responsibilities

• Derive Insights & Support Strategy: Leverage data analytics to uncover insights that help optimize product, risk, or growth strategies across geographies.
• Monitor Portfolio Health: Assist in tracking performance metrics, user behavior, and macroeconomic trends that impact business outcomes, flagging risks and anomalies to senior team members.
• Technical Execution: Write clean, working SQL and Python to build scalable reporting and partner with Engineering to support the deployment of machine learning and risk models.
• Cross-Functional Collaboration: Work closely with Product, Legal, and Compliance to understand evolving consumer lending regulations and market requirements, assisting in translating them into foundational data models and operational policies.
• Drive Launch Alignment: Support cross-functional discussions to ensure new product launches and market entries align with our operational capabilities and risk appetite.
• AI Fluency & Efficiency: Integrate AI tools (Cursor, Claude Code, copilots) into your daily workflows to accelerate data mining and routine tasks, holding the line on verifying outputs.

Requirements & Tech Stack

• Currently pursuing a Bachelor’s degree or higher with an expectation that you will complete your most recent full-time degree program by August 2027 or earlier.
• Working knowledge of SQL, Python, or other scripting languages.
• Familiarity with data mining, data visualization, and foundational statistical modeling.
• Basic understanding 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.

Qualifications

• Degree in Data Science, Computer Science, Engineering, Economics, Statistics, Math or a related quantitative field preferred.
• Relevant internships or prior experience in the consumer lending, fintech, or broader financial services industry are highly valued.

Potential team placements include: Point of Sale (POS), Direct to Consumer (DTC) / Card, Fraud, Core Analytics, Servicing and Payments, International Expansion.

Hybrid early career program with in-person collaboration 3 days a week.

USA base pay range (CA or NY) per year: $115,000.

Benefits include 100% subsidized medical coverage, dental and vision, spending stipends, flexible time off, and ESPP.