We are looking for a Customer Data Analyst to join our founding team. This is an opportunity to work directly with the CEO and play a pivotal role in shaping both how we deliver value to customers and how we evolve the product. You will work closely with our design partners—helping them make sense of complex data, uncover patterns, and translate insights into actions that improve their GTM performance. At the same time, you’ll synthesize customer feedback into structured insights that will guide our product roadmap. This role is ideal for someone who thrives in ambiguity, sees data as a puzzle to solve, and wants to work at the intersection of customer-facing work, analytics, and product strategy.

WHY THIS ROLE EXISTS

We are looking for a Customer Data Analyst to join our founding team. This is an opportunity to work directly with the CEO and play a pivotal role in shaping both how we deliver value to customers and how we evolve the product.
You will work closely with our design partners—helping them make sense of complex data, uncover patterns, and translate insights into actions that improve their GTM performance. At the same time, you’ll synthesize customer feedback into structured insights that will guide our product roadmap.
This role is ideal for someone who thrives in ambiguity, sees data as a puzzle to solve, and wants to work at the intersection of customer-facing work, analytics, and product strategy.

WHAT YOU’LL DO

• Own design-partner outcomes: onboard, troubleshoot, and guide early customers to measurable wins and deeper adoption.
• Analyze multi-source data: wrangle CRM/RevOps, marketing touchpoints, and product signals; find patterns and attribution insights that change decisions.
• Tell the story: package findings into short narratives, dashboards, and recommendations executives will act on, help them create QBR and board slides.
• Close the loop with product: translate customer pain + data learnings into prioritized, testable product requirements.
• Build for scale: create playbooks, frameworks, and lightweight instrumentation that make future implementations faster and more reliable.
• Be the voice of reality: pressure-test assumptions, validate data quality, and call out hallucinations before customers see them.