The mission of Global Operations (GO) at Meta is to build and run world-class processes at a global scale that minimize harm to people and society, and maximize the success and well-being of Meta's ecosystem of people, communities, businesses, and partners.
Global Operations Data Analyst Responsibilities
Partner with operations teams, data science, data engineering, and product teams to understand business needs and define analytical approaches to solve complex problems
Design and execute data analyses to uncover insights that drive operational improvements and strategy decisions, under your own initiative
Create dashboards, automated reports, and self-service tools using BI platforms (e.g. Tableau) which deepen our understanding of the business and enable efficiencies for our operations teams
Build and maintain data pipelines and associated documentation
Communicate results of analyses to technical and non-technical stakeholders in a way that influences business outcomes (e.g. roadmap decisions, opportunity areas etc)
Minimum Qualifications
Minimum 5+ years professional experience working in an Operations, Analytics, Product, Engineering or equivalent team, preferably in a technology company, consulting firm, or similar fast-paced environment
B.A. or B.S. degree with a quantitative focus in Computer Science, Information Systems, Math, Statistics, Operations Research, Business Analytics, Data Science or equivalent training
Advanced proficiency in querying and manipulating complex raw datasets for analysis using SQL
Extensive professional experience with data visualization tools (e.g., Tableau - designing, building, productionising dashboards)
Professional experience building and deploying data pipelines
Familiarity with statistical analysis and concepts
Demonstrated experience of managing analytics projects end to end from concept design through to business adoption, autonomously
Business acumen is a must. You will be required to partner with business stakeholders to proactively define analytics strategy, drive execution, and communicate data insights clearly
Demonstrated experience working collaboratively, cross functionally, autonomously, and in a fluid business environment
Preferred Qualifications
Advanced degree with a quantitative focus (Economics, Computer Science, Operations Research, Math, Statistics, Analytics)
Experience leveraging AI to drive operational efficiencies
Familiarity with data science and machine learning concepts and an understanding of how to apply these methods to solve real-world business problems