Credit Risk Associate

About Ramp

Ramp builds smart infrastructure for finance teams, automating how over $200B in annualized spend flows through 70,000+ companies. We authorize payments, flag risk, categorize spend, and close books. The median Ramp customer saves 5% and grows revenue 16% in their first year.

We hire builders with high agency and urgency who own problems end-to-end and make consequential decisions. We care about what you've built, not where you trained.

The Role

As a Credit Risk Associate on Ramp's Risk Strategy & Operations team, you will leverage data to develop and optimize credit strategies. Credit is one of Ramp's most consequential products—every policy change affects how customers grow usage and how responsibly Ramp scales while managing risk.

You will own or help build strategy across credit risk areas including:

• Credit limits and payment speed optimization
• Collections strategy
• Credit risk model prototyping
• Policy development and implementation

What You'll Do

• Own credit risk strategy for model prototyping, credit limits, payment speed, collections, and related areas
• Use SQL, quantitative reasoning, and credit risk judgment to investigate patterns, size opportunities, and define policy changes
• Build the first useful version of workflows: tools, apps, dashboards, agents, notebooks, QA loops, monitors, and decisioning processes
• Use AI tools daily to accelerate research, analysis, coding, synthesis, writing, verification, and follow-through
• Integrate AI into credit risk workflows for feature exploration, policy monitoring, and automated decisioning
• Collaborate across Product, Engineering, Data Science, Risk Operations, Finance, Customer Experience, and Compliance

Required Skills

• AI fluency: You must already use AI tools like Claude Code, Codex, or similar to write code, explore data, prototype apps, and automate workflows. You don't need to be a software engineer, but you must ship something runnable and testable.
• SQL and quantitative analysis
• Credit risk judgment and knowledge
• High agency and bias toward prototyping over documentation