Product Data Scientist

What You'll Do

• Build and own core product and growth metrics: activation, retention, engagement, and conversion — with particular depth on the nuances of a cross-platform, PLG consumer product
• Proactively surface insights — patterns in usage cohorts, feature adoption signals, product funnel drop-offs, engagement inflection points
• Partner with product managers and engineers across our core product surface areas to define and answer the questions that drive decisions
• Analyze A/B experiments end-to-end — from hypothesis formation through to causal interpretation and recommendations
• Collaborate closely with analytics engineers on our dbt + ClickHouse stack to ensure metric definitions and data models are clean, consistent, and align with business and product processes

What We're Looking For

• 5+ years of experience in data science or quantitative analytics, with meaningful time spent at a consumer SaaS or consumer tech company
• Experience with experimentation — from hypothesis design through analysis, with the ability to build frameworks that let the product team run and learn from tests at scale
• Strong SQL skills and fluency working within a modern data stack (dbt, ClickHouse, Snowflake, or similar); Python proficiency for analysis and modeling
• Experience embedded with product teams, using sound judgment in ambiguous situations to shape priorities and deliver actionable analysis
• Clear communicator who can make complex analysis legible to non-technical stakeholders