Data Scientist, Risk

About the role

As a Data Scientist supporting Risk, you will play a crucial role in leveraging experimentation, statistical inference, and causal analysis to drive strategic decision making that contributes to the overall success of our organization. The ideal candidate is a trusted data storyteller with strong statistical and coding skills, and a passion for applying these skills to help small businesses thrive.

This is a San Francisco-based role with expectations to be in office Tuesdays and Wednesdays.

Here’s what you’ll do day-to-day

• Partner and Execute: Translate ambiguous stakeholder questions into clear, testable analyses. Structure complex business problems, identify drivers of performance, and communicate actionable insights to influence product or business decisions.
• Analytical Depth: Use sound statistical reasoning and experimentation frameworks to separate signal from noise. Select appropriate analytical techniques that balance rigor and speed, and leverage AI-assisted analytics to surface drivers of product performance, separating signal from noise
• Build Models and Leverage AI: use Claude Code to enhance analytical approaches. Build risk models and present recommendations to process and project enhancements
• Experimentation & Measurement: Design and interpret experiments within your domain. Work with stakeholders to define success metrics, measure impact, and communicate trade-offs.
• Communication: Tell clear, data-driven stories that connect findings to business strategy. Adapt communication for technical and non-technical audiences.
• Execution: Own end-to-end delivery of analyses and metrics for your product area. Collaborate with cross-functional peers to scope, prioritize, and deliver insights that inform decisions.

Here’s what we’re looking for

• 7-10 years of experience in Data Science at a product-focused software company.
• Experience with Risk DS and risk modeling.
• Strong SQL skills and comfort with Python.
• Proven ability to apply statistical methods, causal inference, and experimental design to real business problems.
• Excellent communication skills, with a track record of influencing cross-functional stakeholders and leadership.
• Demonstrated experience leading technically complex projects with clear business impact.
• A proactive, resilient problem-solver who independently structures ambiguous problems into actionable insights.
• Passion for mentoring others and raising the bar for data science craft across the team.