Facebook Quantitative Researcher, R&D in Menlo Park, California
Facebook's mission is to give people the power to share, and make the world more open and connected. Through our growing family of apps and services, we're building a different kind of company that helps billions of people around the world connect and share what matters most to them. 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 make the world more open and accessible. Connecting the world takes every one of us—and we're just getting started.
The Marketing Science R&D team is responsible for enabling advertisers to accurately measure the impact of paid media. In service of this goal, the team develops methodologies, partners with our product and engineering teams to establish measurement systems, and prototypes new approaches to increase the efficiency of ad spend on our platform. We also form partnerships with measurement companies to advance our goals.
Facebook seeks a causal inference expert to help build world-class cross-publisher and cross-channel measurement solutions. 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.
The ideal candidate will not only have a strong technical background, but also prior cross-publisher measurement experience. This position is full-time and based in either Menlo Park, California.
Drive technical development and project management of cross-publisher and cross-channel measurement initiatives.
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, Engineering and Marketing Science leads to solve problems, identify opportunities for impact, and 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 with (GB/TB) datasets
Experience with causal inference, including leveraging observational data and addressing challenges from missing data
Analytical and research design skills
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