Product Analyst, Global Product Quality

Meta•Seattle, WA

1d•$136,000 - $185,000

About The Position

The Product Analyst will support Meta’s Global Product Quality (GPQ) organization and partner with QA, internationalization teams, engineers, product managers, and designers to improve product experiences across global markets. The role applies technical skills, analytical judgment, and business intuition to identify GPQ challenges, inform strategy and investment decisions, and shape experiences for Meta’s global user and business communities. The analyst will join the Global Experience Analytics team, which has presence in Internationalization, Global Experience Platform, International Growth, Product Quality & Experience, and Local Product Experiences.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
At least 5 years of experience in product analytics, data science, or a related quantitative discipline focused on product quality, reliability, or user experience measurement.
At least 5 years of experience with SQL and at least one scripting or statistical programming language, such as Python or R, for data extraction, transformation, and analysis.
Experience designing and interpreting product experiments, including A/B testing, hypothesis testing, and causal inference methods applied to product quality.
Experience building data visualizations and self-service dashboards that communicate product health metrics to cross-functional stakeholders.
Experience translating complex quantitative analyses into clear, actionable recommendations and influencing product roadmap decisions through data-driven narratives.
Experience evaluating AI tooling or developing AI evaluations.

Nice To Haves

Experience applying forecasting or predictive modeling techniques to anticipate product quality risks or estimate improvement opportunities.
Demonstrated ongoing AI skill development, such as prompt or context engineering and agent orchestration, and staying current with emerging AI technologies.
Experience in product quality, reliability engineering, or user experience analytics at a global scale across multiple product surfaces or platforms.
Experience adhering to and implementing responsible, ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Demonstrated ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.
Experience integrating AI tools into analytics workflows to accelerate insight generation, automate monitoring, or expand analytical scope.

Responsibilities

Identify and prioritize product quality opportunities by analyzing user-facing issues, performance signals, and usability friction across Meta’s family of apps.
Design and execute end-to-end analyses, including hypothesis formulation, data collection strategy, statistical testing, and insight synthesis, to evaluate product quality initiatives.
Define, monitor, and evolve product quality metrics and health dashboards covering reliability, performance, and user experience trends across global markets.
Build scalable self-service data visualizations and reporting tools so product and engineering partners can explore quality signals and diagnose regressions independently.
Partner with product management, engineering, and design teams to turn analytical findings into prioritized roadmap recommendations that reduce user-facing defects and improve product experience.
Develop and maintain predictive models and forecasting analyses to anticipate quality degradation risks and estimate the impact of proposed product improvements.
Communicate experiment results, quality trends, and data-driven recommendations to cross-functional stakeholders, tailoring narratives for technical and non-technical audiences.
Contribute to team-level goals by identifying measurable success metrics that connect product quality outcomes to broader business objectives.
Use AI-integrated workflows to accelerate analysis, automate recurring quality monitoring, and surface insights at greater scale and speed.
Advise cross-functional partners on analytical design best practices to ensure research plans and experiment designs rigorously address product quality hypotheses.