Data Scientist, Analytics - Product Navigation

Job Description

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.
Over 2 Billion people use Facebook every month, and our core products are the way we connect them to their communities. Our mission is to make core products in the app easy to find, relevant and easy to use. We are building out one of core app's top priorities for 2018 - dynamic tabs. We're looking for a Data Scientist who can tell us who we should target, what products we should offer them and how we should make tradeoffs across different products. Ideal fit is someone with machine learning/modeling experience in personalization/merchandising who can build and test a ranking model to decide which tabs to offer each user, which is a key priority for us in H1. Big opportunities: What is the best set of products for each user? How should we tradeoff between growing product usage and making the app simple and easy to use? Can we build a product ranking model will better target audiences for tabs vs. custom heuristics we're using today? How does personalizing tabs impact the broader product ecosystem? What are the tradeoffs between product incrementality and relevance? This is a very cross-functional role and you'll be working closely with Product Management, Engineering, Research and Design


  • Provide technical and thought leadership on designing, prototyping, implementing and automating complex analyses
  • Partner with cross-functional teams to identify new opportunities requiring the use of modern analytical and modeling techniques
  • Effectively communicate insights and recommendations to upper management in support of strategic decision-making
  • 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, develop, and optimize data and modeling pipelines

Minimum Qualifications

  • MS degree in a quantitative discipline (e.g., statistics, operations research, econometrics, computer science, applied mathematics, physics, electrical engineering, industrial engineering) or equivalent experience
  • 10+ 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)
  • Experience in the design and implementation of recommendations/personalization engines

Preferred Qualifications

  • 5+ years leading technical teams
  • Experience with distributed computing (Hive/Hadoop)
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