Meta's Global Operations Quality team is looking for Data Analysts to support operational efficiency and strategic decision-making for global teams, aiming to optimize processes, improve performance, and drive business outcomes through data-driven insights.
Requirements
- Advanced proficiency in querying and manipulating complex raw datasets for analysis using SQL
- Familiarity with statistical analysis and concepts
- Familiarity with data science and machine learning concepts and an understanding of how to apply these methods to solve real-world business problems
- Experience leveraging AI to drive operational efficiencies
Responsibilities
- 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)
- Partner with operations teams, data science, data engineering, and product teams to understand business needs and define analytical approaches to solve complex problems
Other
- 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
- 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
- Advanced degree with a quantitative focus (Economics, Computer Science, Operations Research, Math, Statistics, Analytics)
