Network Quantitative Engineer
- Menlo Park, CA
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.
Every day we strive to provide the best possible experience to our users that are now numbered in billions, and to make that possible, we have deployed an ultra-high capacity backbone network that spans the globe. We are looking for a Network Quantitative Engineer to join our Backbone Engineering team to support the expansion of our global network through application of targeted metrics and valuable analysis to ensure we maintain our high performance.
- Work with large, complex data sets around the Facebook data infrastructure and solve difficult ad-hoc analysis problems.
- Ability to develop, and deploy automated data pipelines to support prototyping and POC efforts across the team.
- Produce data visualizations for demand, capacity and performance which will enable decision making to internal partners.
- Build, test, and deploy models/simulations, understanding the key outputs and provide statistical analysis of results.
- Support end users on ad hoc data usage and be a subject matter expert for solution development across the team.
- Leverage the Facebook software and infrastructure to develop efficient analytics.
- Build cross-functional relationships with Data Scientists, Network Planners, Software Engineers and Network Engineers to understand their data needs.
- Degree in an analytical field (e.g. Computer Science, Engineering, Mathematics, Statistics, Operations Research, Management Science).
- Experience analyzing and interpreting data, drawing conclusions, defining recommended actions, and reporting results across various stakeholders.
- Experience in demand forecasting, Monte Carlo simulations, network analysis, performance metrics and operations research for demand-based networks and server fleets.
- Experience scripting with one of the following languages: Python, PHP, Perl, R.
- Hands-on experience with large datasets.
- Knowledge of statistical data analysis, queueing theory, non-stationary process analysis including knowledge in SQL, R and/or Tableau.
- Knowledge of network infrastructure and web technologies.
- Graduate work experience
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