Facebook App

Data Analyst, Global Operations Central Analytics

Job description

To give people the power to build community on our platforms, we need to make sure they have the best and most secure experiences possible. People on Central Analytics empower Facebook’s Global Operations organization to be self-sufficient in tactical decision-making and drive operations strategy through analytics, data infra, and reporting. Our key partners are embedded data teams and core functions on the business side within Global Operations, as well as Data Engineering, Data Science, Product, and Engineering partners outside of Global Operations. We are responsible for providing accurate, reliable and accessible business metrics as well as contextualizing them in operational performance with research and advanced analysis. We are looking for Analysts who share our passion for helping make Facebook a safe place for people and businesses to connect across the world. The right candidate will be comfortable in a fast-moving organization, excited to collaborate and focused on positively impacting the experience of a large scale global workforce and the entire Facebook Community. They possess strong quantitative analytical skills, statistical knowledge, data visualization skills, and the ability to build strong partnerships to drive impact across the organizationThis position will be based in our Dublin office supporting a global team.

  • Define vision for a specific value proposition within Central Analytics and mentor junior colleagues in achieving this vision through performing analytics to measure effectiveness of Operations
  • Apply quantitative skills and incorporate qualitative insights to inform and influence strategy for Global Operations
  • Analyze data, conduct research and synthesize feedback into plans, processes and playbooks
  • Partner with Operations, Data Science, Data Engineering, Product and Engineering teams to solve problems and identify trends and opportunities
  • Build/maintain data infrastructure (data pipelines, aggregated data sets, reports, dashboards) to monitor the performance of our operations and drive business understanding.

  • B.A. or B.S. degree with a quantitative focus in Computer Science, Information Systems, Statistics, Math, Physics, Operations Research, or equivalent training
  • 5+ years of experience performing data analysis and dealing with multiple stakeholders.
  • Proficiency in querying and manipulating complex raw datasets for analysis using SQL & Python
  • Experience thinking strategically, structurally solving product problems, and driving execution
  • Experience with statistical analysis (e.g., hypothesis testing, probability, prevalence measurement, regressions, experimentation logic and biases, data modeling techniques, time series analysis)
  • Experience with data visualization tools (e.g., Tableau, Power BI, Looker)
  • Professional experience with reporting systems, data pipeline architecture and data modeling
  • Experience explaining technical concepts and analysis implications clearly to varied audiences and be able to translate business objectives into actionable analyses

  • MSc/PhD with a quantitative focus (Computer Science, Statistics, Operations Research, Math)
  • Experience developing data pipelines via SQL and Python-based ETL framework
  • Experience releasing code into production

Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities - we're just getting started.

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