Data Scientist, Analytics - Sharing/Stories
(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 the heart of connecting people together is building a platform that fosters sharing between you and family, friends, and community. Industry wide, we've seen Stories as a new sharing/consumption format rise. One of the top priorities for Facebook this year will be leaning into this trend and making sure that Facebook is a Stories first product. With this change means disrupting the existing ecosystem within Facebook; it means shifting people's sharing behaviors to be more visual and less text-heavy; it means changing the way people consume content from their friends and family and moving away from a News Feed format; it'll mean learning how to monetize this new format to mitigate expected revenue cannibalization from News Feed, etc. We need a Data Scientist who is capable of tackling all aspects of this problem. As Data Scientist on the team, you'll be expected to stretch across growth, engagement, and monetization of Stories, and work with data scientists to help the company execute this major shift.
- Use existing insights, and develop an understanding agenda to unearth new ones, to drive the product strategy
- Own all communications of insights to 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
- 10+ years experience doing quantitative analysis or statistical modeling
- Knowledge of at least one modeling framework (e.g., SciKit Learn, TensorFlow, SAS, R, MATLAB)
- Experience influencing product strategy through data-centric presentations (to product, business, and other stakeholders)
- Knowledge in at least one of the following areas: predictive modeling, machine learning, experimentation methods
- Experience extracting and manipulating large datasets
- Development experience in any scripting language (PHP, Python, Perl, etc.)
- 5+ years experience leading technical teams
- Experience with distributed computing (Hive/Hadoop)
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