Product Analyst, Global Product Quality

By applying your technical skills, analytical mindset, and business intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will use data and analysis to identify and solve GPQ's biggest challenges. You will influence strategy and investment decisions with data, be focused on impact, and collaborate with other teams. You won’t simply present data, but tell data-driven stories.

You will join the Global Experience Analytics team with presence in Internationalization, Global Experience Platform, International Growth, Product Quality & Experience, and Local Product Experiences.

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 the impact of product quality initiatives Define, monitor, and evolve product quality metrics and health dashboards that track reliability, performance, and user experience trends across global markets Build scalable self-service data visualizations and reporting tools that enable product and engineering partners to explore quality signals and diagnose regressions independently Partner with product management, engineering, and design teams to translate 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 size the impact of proposed product improvements Communicate experiment results, quality trends, and data-driven recommendations clearly to cross-functional stakeholders, adapting the narrative for both technical and non-technical audiences Contribute to setting team-level goals by identifying measurable success metrics that connect product quality outcomes to broader business objectives Leverage AI-integrated workflows to accelerate analysis, automate recurring quality monitoring tasks, and surface insights at greater scale and speed Advise cross-functional partners on analytical design best practices, ensuring that research plans and experiment designs rigorously address product quality hypotheses

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, 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 (e.g., Python, 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 context 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 in evaluating AI tooling or developing AI evaluations Experience applying forecasting or predictive modeling techniques to anticipate product quality risks or size improvement opportunities Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience working on 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 (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience integrating AI tools into analytics workflows to accelerate insight generation, automate monitoring, or expanding the analytical scope