Operations Research Scientist
(Menlo Park, CA)
Facebook's mission is to give people the power to share, and make the world more open and connected. Through our growing family of apps and services, we're building a different kind of company that helps billions of people around the world connect and share what matters most to them. 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 make the world more open and accessible. Connecting the world takes every one of us—and we're just getting started.
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 from new graduates to industry veterans, from individual contributors to seasoned managers. 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 a full-time 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, see 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.
- Contribute to R&D roadmap as a thought leader to shape next gen analytics solutions.
- Mentor others as needed on best practices for design and implementation of cutting-edge analytics solutions.
- MS 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 in industry and/or academia.
- 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.
- Familiarity with enterprise-wide application development life-cycle
- Familiarity with object-oriented programming languages (such as C++ or Java) and visualization tools (such as Tableau)
- Experience working with or in support of diverse communities.
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