Analyst, Early Career (Full Stack)

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most.

In our hybrid early career program, you’ll be paired with a tenured Affirmer and have an opportunity to collaborate in-person 3 days a week out of our New York City, or San Francisco offices. You'll experience the best of both worlds: the in-office experience and remote work. After the one-year, you can remain hybrid, go remote, or stay in an office. Opportunities are available across different tech stacks and teams so that you can find a perfect fit to launch your career with Affirm!

About the Risk & Analytics Team: The Risk & Analytics (R&A) team makes crucial decisions that direct Affirm’s business strategy. We partner with Machine Learning, Product, Engineering, Capital Markets, and Commercial teams to grow Affirm responsibly by optimizing approval, conversion, losses, and profitability.

Operating across the entire customer and merchant lifecycle, we tackle a diverse array of challenges from optimizing checkout conversion and mitigating fraud risk, to building scalable data foundations and enabling international growth. We analyze performance not just to report on it, but to determine where to invest resources for maximum impact through building tools, scalable data infrastructure, and analytical frameworks. We improve the analytics experience across Affirm by streamlining workflows and fostering a culture of learning and documentation. By taking ownership of the entire analytical lifecycle, from initial question to final business decision, we turn complex data and systems into clear, actionable signals that ensure Affirm grows efficiently and intelligently.

Our Teams (Where You Might Sit): We are hiring multiple Early Career Analyst roles across Affirm's Risk & Analytics organization through this single job posting. Rather than interviewing for one specific team, candidates will go through a shared interview process designed to assess the core skills we look for across R&A.

If selected, we will work with you to determine the best team match based on your interests, experience, strengths, and current business needs. You will have the opportunity to learn more about our teams and share your preferences as you move through the process.

Potential team placements include:

• 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 and Payments: Enhance the post-origination customer experience by analyzing repayment behavior, collections strategies, and operational efficiency.

• International Expansion: Build the measurement and decision foundations needed to sustainably launch and scale Affirm in new global markets.

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.

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