Product Analyst

Writer Writer · AI Frontier · San Francisco, CA · Engineering, product & design

Product analyst role at an enterprise generative AI company focused on understanding user behavior, feature performance, and product market fit to shape product strategy and drive growth. Responsibilities include deep-dive analyses, A/B testing, identifying user friction points, designing data models, and collaborating cross-functionally. Requires 5+ years of experience, advanced SQL and dbt skills, proficiency with product analytics tools, and strong communication skills.

What you'd actually do

  1. Drive product understanding by conducting deep-dive analyses on user adoption, engagement patterns, and feature utilization across our AI platform
  2. Shape product strategy through comprehensive A/B test design, analysis, and interpretation, influencing critical roadmap decisions with data-backed recommendations
  3. Identify friction points and opportunities in the user journey using tools like FullStory, translating observations into actionable insights for product and design teams
  4. Design and build new ELT-based data models using SQL and dbt, implementing efficient testing and validation to ensure the accuracy and integrity of the data.
  5. Collaborate cross-functionally with product managers, engineers, and designers to define success metrics, prioritize initiatives, and evangelize a data-informed culture

Skills

Required

  • 5+ years of experience in a product analyst, business analyst, or data analyst role
  • Advanced dbt and SQL skills
  • Proficiency with product analytics tools (e.g., FullStory, Amplitude, Mixpanel)
  • Strong analytical and problem-solving skills
  • Experience with data visualization tools (e.g., Tableau, Looker)
  • Exceptional communication skills

Nice to have

  • Preferably within a SaaS or enterprise software environment

What the JD emphasized

  • AI agents
  • enterprise-grade LLMs
  • generative AI
  • AI platform
  • product market fit
  • data-backed recommendations
  • user journey
  • data models
  • data-informed culture
  • SaaS or enterprise software environment
  • product analytics tools
  • actionable insights
  • data visualization tools
  • product health
  • strategic initiatives
  • uncover the "why"
  • product performance
  • technical and non-technical audiences
  • Own your impact
  • build and scale analytics from the ground up