Data Scientist, Analytics - Sharing/Ecosystems
(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; the mission of the Sharing Organization at Facebook is to do just that. The Sharing Ecosystem team's job is to step back, and tackle deep, challenging questions that'll help inform our understanding of sharing on Facebook and the barriers. Questions like: what's driving the sharing decline on Facebook, how much of this is from competition, from increasing audience concerns, from politicization of Facebook and changes in sentiment and brand; how do we use our understanding of sharing drivers to make accurate, non-linear forecasts; we know women and children are most susceptible to harassment and bullying - how does this impact their propensity to share, how do we detect and mitigate this in the future? This team is unique in that it's not directly tied to a product team, which provides the team with the space to dive deep into these topics. The ideal candidate is someone who is a deep systems thinker, and is someone who is looking for a role that is more research heavy.
- 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 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
- 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 and knowledge in at least one of the following areas: predictive modeling, machine learning, experimentation methods
- 5+ years leading technical teams
- Experience with distributed computing (Hive/Hadoop)
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