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Principal Data Analyst (Product)

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Onsite

Principal Data Analyst (Product)

ClickUp

Principal Data Analyst (Product)

Skills

SQL QueriesLookerTableauPythonProduct StrategyData ScienceTesting & QASnowflakeAmplitudeData AnalysisAIdbt

2 months ago

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Important information


Contract type:

Permanent

Salary:

$205,000 – $251,000 / year

Location:

United States

Work mode:

Onsite

Published on:

20 August 2026

What they need


  • We’re hiring a highly influential product analytics leader who can turn ambiguous questions into sharp insight, scalable measurement, and recommendations that directly shape what we build. This person will partner closely with Product, Engineering, Design, and Growth to raise the bar on decision quality and establish a more AI-native analytics operating model
  • Own the product analytics agenda across product usage, activation, feature adoption, retention, and expansion, and translate open-ended business questions into structured analyses and clear recommendations
  • Partner with Product, Engineering, and Design to define success metrics early, improve instrumentation quality, and ensure important product surfaces are measurable from launch
  • Build reusable analysis frameworks, semantic layers, metric definitions, and self-serve resources that help product teams answer routine questions faster and more consistently
  • Apply AI-first methods across the analytics workflow, using large language models, coding agents, and automation for tasks like query drafting, QA, validation, documentation, and first-pass synthesis while keeping human judgment at the center of final recommendations
  • Design and interpret experiments, observational analyses, and trend investigations, including situations where data is incomplete or traditional experimentation is not feasible
  • Surface meaningful patterns in behavioral, subscription, and product data to influence roadmap choices, prioritization, and executive decision-making
  • Create monitoring and alerting approaches that reduce manual reporting cycles and make it easier to spot product opportunities, risks, and anomalies earlier
  • Mentor analysts and elevate team practices around analytical rigor, AI-assisted workflows, insight storytelling, and stakeholder communication

Benefits

  • 16” MacBook Pro
  • Moving Expenses
  • $200/mo commuter benefits
  • Team lunches each week
  • 401(k) match up to 2%
  • Unlimited snacks, kombucha, and cold brew
  • Health insurance
  • Dental insurance
  • ClickUp swag
  • Teammate recognition rewards
  • Flexible PTO- Excellent written and verbal communication skills, with a track record of making complex findings easy for product and executive audiences to act on
  • Strong product analytics judgment, including experience with event instrumentation, funnel analysis, cohort analysis, retention, feature adoption, and experimentation
  • Clear examples of using AI, automation, or agentic workflows to improve analytics speed, scale, or quality while maintaining strong QA and decision discipline
  • Advanced SQL skills and strong familiarity with modern cloud data and analytics tooling such as Snowflake, dbt, Amplitude, Segment, Hex, Tableau, Looker, or similar platforms
  • Significant experience in analytics, business intelligence, data science, or product analytics, including strong experience partnering with Product teams in a B2B SaaS or product-led growth environment
  • Working proficiency in Python for analysis, automation, or experimentation support
  • A high-ownership working style with strong prioritization skills and a track record of independently driving high-impact work
  • Demonstrated ability to translate broad, ambiguous questions into structured analysis plans and actionable recommendations for senior stakeholders
  • Experience in fast-moving software environments where analytics directly influences roadmap tradeoffs and product strategy
  • Strong grasp of applied statistics, causal reasoning, and incremental impact measurement
  • Experience mentoring analysts or setting best practices for how analytics teams operate
  • Experience analyzing AI or LLM-powered product features and understanding how they influence activation, engagement, monetization, or retention
  • Experience building or scaling product analytics practices, self-serve measurement systems, or reusable metrics frameworks

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