Analyst , Merchant Risk

Analyst I, Merchant Risk

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.

The Merchant Risk Analytics team works cross‑functionally with Merchant Underwriting, Compliance, Engineering, and other analytics teams to establish scalable risk management for merchant acquisition and portfolio monitoring. We’re looking for an intelligent, driven individual who wants to learn, grow, and solve challenging problems.

This role requires strong analytical foundations and a willingness to operate across the full merchant risk lifecycle, from onboarding to ongoing monitoring and risk expansion. You will support the development and maintenance of scalable analytics, modeling, automation, and monitoring frameworks as our merchant footprint grows. The role emphasizes hands‑on execution, learning, and ownership of core analyses and model‑driven workflows, while collaborating closely with cross‑functional partners.

• Support merchant onboarding and ongoing portfolio monitoring through data analysis, modeling and automation workflows.
• Detect and monitor fraud across the network, responding quickly to emerging risks.
• Contribute to the development and improvement of scalable monitoring frameworks, controls, and reporting.
• Assist in identifying gaps and opportunities within existing risk processes.
• Partner cross‑functionally to translate risk requirements into data‑driven strategies.
• Leverage AI‑assisted tools to accelerate analysis, automate workflows, and support the development of scalable, agentic merchant risk solutions.

• Minimum 1 year of experience in risk management or a related field, including prior experience with analytics.
• Strong problem‑solving skills with the ability to break down ambiguous problems using data.
• Ability to think creatively and critically, thriving in a fast‑paced environment.
• Eagerness to explore new tools and methodologies to solve real‑world problems.
• Strong coding skills in Python, SQL or other scripting languages; familiarity with agentic / LLM orchestration frameworks.
• Passion for understanding how the product works and the broader context of business decisions.
• Comfortable using AI tools to enhance productivity, analysis, and workflow automation; interest in building or leveraging agentic workflows to solve risk problems.
• Bachelor’s degree in a quantitatively rigorous field such as engineering, statistics, optimization, math, finance, or economics.

Pay Grade: I
Equity Grade: 5

Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents).

USA base pay range (CA, WA, NY, NJ, CT) per year: $115,000‑155,000
USA base pay range (all other U.S. states) per year: $102,000‑142,000

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. Remote‑based employees may occasionally be required to work out of an assigned office.

• Health care coverage – all premiums are covered for you and your dependents.
• Flexible Spending Wallets – generous stipends for technology, food, lifestyle needs and family‑forming expenses.
• Time off – competitive vacation and holiday schedules to rest and recharge.
• ESPP – employee stock purchase plan enabling you to buy shares at a discount.

We believe it’s on us to provide 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, affirm will consider for employment qualified applicants with arrest and conviction records pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance.