Meta
Product Analyst, Global Product Quality
$136K–$185K
Menlo Park, CA +1 · Full-time · Posted Oct 25, 2026
- Location
- Menlo Park, CA
Seattle, WA - Experience
- 5+ years in product analytics, data science, or a related quantitative discipline focused on product quality, reliability, or user experience measurement; 5+ years with SQL and at least one scripting or statistical programming language.
- Education
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
About the job
Analyzes global product quality data to identify user-facing issues, guide product improvements, and help Meta deliver localized experiences across its apps.
What you'll do
- Analyze quality signals and user issues; define and monitor product health metrics and dashboards.
- Design experiments and predictive analyses, then translate findings into roadmap recommendations.
- Use AI-integrated workflows to accelerate analysis and automate quality monitoring; communicate insights to stakeholders.
What they ask for
- Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
- 5+ years of experience in product analytics, data science, or a related quantitative discipline focused on product quality, reliability, or user experience measurement.
- 5+ years of experience with SQL and at least one scripting or statistical programming language, such as Python or R.
- Experience designing and interpreting product experiments, building self-service dashboards, and translating quantitative analysis into actionable product recommendations.
Nice to have
- Experience evaluating AI tooling or developing AI evaluations, and applying forecasting or predictive modeling.
- Experience with global-scale product quality, reliability engineering, or user experience analytics, and responsible AI practices.
Pay
$136,000/year to $185,000/year USD base salary; bonus and equity also stated, amounts unspecified
Tools
SQL, Python, R
AI focus
Integrate AI tools into analytics workflows to accelerate insights, automate quality monitoring, and expand analytical scope; evaluate AI tooling or develop AI evaluations; apply responsible AI practices.
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