Data Scientist, Analytics - Video Machine Learning

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 â€" we're just getting started.

Facebook is the second largest online video platform in the world. Video at its heart is a social experience, as people talk about and talk through video. Users upload their own videos. They go Live and broadcast to their friends. Pages upload tens of millions of hours a day. The video team at Facebook is responsible for the entire video experience at FB, from the uploading, to the watching to the interactions around the video. This role is focused on better understanding the ecosystem of videos on Facebook. That includes better understanding the types of videos we have (classification by different content types and publisher types); better understanding the types of user interactions we have (substantive discourse versus platitudes versus shares); better understanding the impact of video watching on our users.


  • Use existing insights, and develop an understanding agenda to unearth new ones, to drive the product strategy
  • Own all communications of insights to upper management in support of strategic decision-making
  • Partner with cross-functional teams to identify new opportunities requiring the use of modern analytical and modeling techniques
  • Plan, and be able to conduct as needed, end-to-end analyses, from data requirement gathering, to data processing and modeling
  • Own ongoing deliverables and communications
  • Work with data engineers to architect data and modeling pipelines
  • MS degree in a quantitative discipline (e.g., statistics, operations research, econometrics, computer science, applied mathematics, physics, electrical engineering, industrial engineering) or equivalent experience
  • 5+ years experience doing quantitative analysis or statistical modeling
  • Experience and knowledge of at least one modeling framework (e.g., SciKit Learn, TensorFlow, SAS, R, MATLAB)
  • Experience extracting and manipulating large datasets
  • Development experience in any scripting language (PHP, Python, Perl, etc.)
  • Proven experience influencing product strategy through data-centric presentations (to product, business, and other stakeholders)
  • Communication experience
  • Knowledge of classification techniques, from data generation, to their use in learning systems
  • Advanced degrees
  • Experience with distributed computing (Hive/Hadoop)

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