Analyst

About the Position

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 Role

As an Analyst I 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.

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 such as Cursor, Claude Code, and copilots into your daily workflows to accelerate data mining and routine tasks, while carefully verifying outputs.

Requirements

• 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.

We Offer

• Competitive salary range: $101,000 - $165,000 per year (based on location and experience).
• Comprehensive benefits package including 100% subsidized medical coverage, dental and vision for you and your dependents.
• Generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses.
• Competitive vacation and holiday schedules.
• Employee Stock Purchase Plan (ESPP).

About the Company

Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. We’re extremely proud to offer competitive benefits that are anchored to our core value of people come first.

By joining our team, you will be part of a company that is committed to providing an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.

[For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records.

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