Quantitative Researcher, R&D
(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.
The Marketing Science R&D team is responsible for designing and prototyping highly-scalable solutions, and to ensure successful prototypes are expanded such that all advertisers can improve the measurement and ads delivery of their marketing efforts. In service of this goal, the team identifies and executes novel solutions, develops methodologies, and partners with our product and engineering teams.
Facebook seeks an innovator to recognize new opportunities and help build highly-scalable, scientifically rigorous measurement and ads delivery systems. These efforts are instrumental for shifting the industry and marketers to evaluate their initiatives based on true business value, and to shape Facebook's ads product strategy with insights gained from these new platforms.
This position is full-time and based in Menlo Park, California.
- Identify specific opportunities to leverage new data sources or systems to improve ads delivery or measurement for marketers.
- Assess the validity and rigor of new data sources and approaches, establishing scalable frameworks for ongoing evaluation as appropriate.
- Build cross functional relationships with Product, Analytics and Engineering to shape long-term product roadmaps with a balance of technical rigor and strategic considerations.
- Master's or PhD in a quantitative field such as Computer Science, Engineering, Statistics, Economics or Political Methodology
- 2+ years of hands-on research experience with empirical problems in the social or biomedical sciences, or in the Internet industry
- Experience using machine learning or non-parametric modeling techniques with large (GB/TB) datasets
- Experience with causal inference, including leveraging observational data and addressing challenges from missing data
- Prior experience with ads product development and established track record of innovation
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