Credit Risk Data Scientist

About Rippling

Rippling gives businesses one place to run HR, IT, and Finance. It brings together all of the workforce systems that are normally scattered across a company, like payroll, expenses, benefits, and computers. For the first time ever, you can manage and automate every part of the employee lifecycle in a single system.

Take onboarding, for example. With Rippling, you can hire a new employee anywhere in the world and set up their payroll, corporate card, computer, benefits, and even third-party apps like Slack and Microsoft 365—all within 90 seconds.

Based in San Francisco, CA, Rippling has raised $1.2B from the world's top investors—including Kleiner Perkins, Founders Fund, Sequoia, Greenoaks, and Bedrock—and was named one of America's best startup employers by Forbes.

We prioritize candidate safety. Please be aware that all official communication will only be sent from @Rippling.com addresses.

Overview

We are looking for a highly analytical Senior Analyst to support key initiatives across risk, underwriting, and operations. This role will focus on leveraging data to identify opportunities, improve decision-making, and drive operational efficiency

.You will play a hands-on role in developing predictive models and supporting the design and deployment of AI-driven solutions, including agent-based systems, to scale workflows and enhance performance

What You'll Do

• Analyze large datasets to identify trends, root causes, and actionable insights
• Support risk, underwriting, and operational decision-making through data analysis and reporting
• Build, validate, and maintain predictive models (e.g., risk scoring, forecasting, classification)
• Partner with Product, Engineering, and Operations to implement data-driven solutions
• Help design and improve workflows to increase efficiency and reduce losses
• Contribute to the development and deployment of AI agents to automate operational processes and support decision-making
• Assist in productionizing models and tools in collaboration with engineering teams
• Monitor performance of models and systems, and support ongoing iteration and improvement

What We're Looking For

• 3–5+ years of experience in analytics, data science, or operations-focused roles
• Strong analytical and problem-solving skills with experience working with large datasets
• Experience building predictive models and applying statistical or machine learning techniques
• Proficiency in SQL and Python (or similar tools)
• Experience working cross-functionally and supporting execution of projects
• Ability to clearly communicate insights to both technical and non-technical stakeholders
• Exposure to AI/ML systems, including experience or interest in agent-based workflows or LLM-powered tools
• Experience in risk, underwriting, payments, or financial operations is a plus

Nice to Have

• Experience in high-growth or startup environments
• Familiarity with workflow automation or process optimization
• Experience working with production data systems or model deployment