Operations Research Scientist Intern
(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.
At Facebook, we pride ourselves on making data-informed decisions. This includes not only decisions we make about our platform, which serves over 1 billion users, but also how we develop internal business applications that enhance productivity. Facebook's Business Applications team is responsible for developing and maintaining integrated and scalable corporate applications that power the enterprise. We are seeking insightful and forward-thinking scientists soon to graduate from a PhD program. Our scientist team identifies business problems and solves them by using various numerical techniques, algorithms, and models in Operations Research, Data Science, and Data Mining. You will have the opportunity to work on a broad spectrum of areas such as Supply Chain Optimization, Inventory & Capacity Planning, Process Design & Optimization, Financial Modeling, Demand Forecasting, Growth & Product Analytics, and Marketing Science. This is an internship role based in Menlo Park, CA.
- Apply your expertise in Operations Research, Data Science, and Data Mining to develop analytics solutions
- Partner with internal stakeholders on projects to identify and articulate opportunities and look beyond the data to identify solutions that will raise the bar for decision making
- Collaborate with cross-functional data and product teams across Business Applications to access and manipulate data, explain data gathering requirements, display results, and build efficient and scalable analytics solutions
- Define, compute, track, and continuously validate business metrics with descriptive and predictive analytics
- Recommend and drive process changes based on robust analysis of operational data and user behavior to improve overall business performance
- PhD student in a quantitative field such as Operations Research, Computer Science, Quantitative Finance, Math, Physics or a related Engineering degree
- 2+ years experience in building models and developing algorithms for machine learning, statistics, mathematical programming, and simulation
- 2+ years experience in managing and analyzing large-scale structured and unstructured data using R or Python
- 2+ years experience in SQL and data modeling
- Experience working with or in support of diverse communities.
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