Data Scientist, Operations Research

2 months ago Menlo Park   2 views
Job Details
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.
In this role, your primary responsibility will be to partner with key stakeholders and lead strategic analysis to support and enable the continued growth critical to Facebook’s Data Center organization. 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 and Demand Forecasting. 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.
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
Knowledge of Statistics & Probability (e.g. Hypothesis testing, Regression, Stochastic modeling, Markov Chains and etc.)
7+ years experience in building models and developing algorithms for machine learning, statistics, mathematical programming, and simulation in industry and/or academia
5+ years experience in managing and analyzing large-scale structured and unstructured data using R or Python
7+ years experience with algorithms and optimizations using CPLEX or related tools
7+ years experience in SQL and data modeling
PhD in Operation Research or Industrial Engineering.
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.