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ClickUp is hiring a Principal Data Analyst to lead the product analytics agenda and drive smarter, faster product decisions across the organization. This is a highly influential individual contributor role that partners closely with Product, Engineering, Design, and Growth teams.
You will own product analytics across usage, activation, feature adoption, retention, and expansion. Key responsibilities include translating ambiguous business questions into structured analyses and clear recommendations; partnering with product teams to define success metrics early and improve instrumentation quality; building reusable analysis frameworks, semantic layers, and self-serve resources; and applying AI-first methods (LLMs, coding agents, automation) across the analytics workflow while maintaining human judgment in final recommendations.
You'll design and interpret experiments, observational analyses, and trend investigations even when data is incomplete or traditional experimentation isn't feasible. You'll surface meaningful patterns in behavioral, subscription, and product data to influence roadmap choices and executive decision-making. You'll also create monitoring and alerting approaches to reduce manual reporting and spot opportunities and risks earlier. Additionally, you'll mentor analysts and elevate team practices around analytical rigor, AI-assisted workflows, and stakeholder communication.
Required qualifications include significant experience in analytics, business intelligence, data science, or product analytics in B2B SaaS or product-led growth environments. You need advanced SQL skills and familiarity with modern cloud data tools (Snowflake, dbt, Amplitude, Segment, Hex, Tableau, Looker). Working proficiency in Python for analysis and automation is essential. You should have strong product analytics judgment including event instrumentation, funnel analysis, cohort analysis, retention, feature adoption, and experimentation. You must translate broad questions into structured analysis plans and communicate complex findings clearly to product and executive audiences. Demonstrated use of AI, automation, or agentic workflows to improve analytics speed and quality is required.
Desirable experience includes building or scaling product analytics practices, analyzing AI/LLM-powered features, applied statistics and causal reasoning, mentoring analysts, and working in fast-moving software environments where analytics directly influences product strategy.
