Define and evolve metrics across adoption, engagement, retention, satisfaction, usability, usage quality, and customer value.
Analyze customer and developer journeys, segments, and feature-level behavior to identify opportunities and friction points.
Evaluate the quality, effectiveness, and adoption of new content and AI-powered product experiences.
Partner with Product, Engineering, Content, Design, and Marketing teams to define measurement plans and success criteria for new initiatives.
Drive experimentation by framing hypotheses, sizing opportunities, designing experiments, interpreting results, and recommending next steps.
Use AI agents as part of your daily analytics workflow, and analyze AI assistants/agentic workflows including usage, outcomes, cost, and usage-based pricing.
Who you are
You have 3-6 years of full-time experience in product analytics, data science, growth analytics, consumer analytics, platform analytics, or a related field.
You have advanced SQL skills and experience working with event, session, or clickstream-level product data.
You are comfortable using Python for analysis and working with large, imperfect, or text-based datasets.
You have a strong foundation in statistics, including hypothesis testing, confidence intervals, statistical significance, power analysis, sampling, regression, and causal inference.
You understand funnels, cohort analysis, segmentation, retention, experimentation, and feature adoption.
You can turn ambiguous business questions into structured analyses, clear recommendations, and measurable outcomes.
Even better if you have
Familiarity with LLM product metrics, AI quality evaluation, or agent workflow analysis.
Experience implementing or validating clickstream instrumentation; not only defining requirements for it.
Experience measuring content quality, learning outcomes, developer workflows, or community engagement.
Experience working with consumer tech, developer tools, learning platforms, marketplaces, or B2B SaaS products.
You will thrive if you
You enjoy owning analytics initiatives end to end, from problem framing through impact measurement.
You thrive in fast-paced environments where priorities evolve based on feedback and insights.
You have a strong bias for action, experimentation, and continuous improvement in ambiguous environments.
You enjoy working across product areas and building context quickly.
You are great at collaborating with multiple stakeholders.
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