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.
What You Will Do
- 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.
What We Look For
- 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; relevant internships or prior experience in the consumer lending, fintech, or broader financial services industry are highly valued.
- Degree in Data Science, Computer Science, Engineering, Economics, Statistics, Math or a related quantitative field preferred.
- 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.
Pay Grade - I
Equity Grade - 5
Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.
Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company).
USA base pay (CA or NY) per year: $115,000
Please note that visa sponsorship is not available for this position.
#LI-Remote
Remote-first with flexibility built in
Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience.
Benefits designed for you
Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights:
- Health coverage at no cost: We cover 100% of premiums for employees and their dependents.
- Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you.
- Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to.
- Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount.
We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help.
For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law.
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