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Summary

Facebook is seeking a Research Scientist to join the Adaptive Experimentation group as part of the Core Data Science team. The Adaptive Experimentation group's mission is to improve the way we run experiments and make decisions both within and outside of Facebook. Candidates apply expertise to develop Internet-scale statistical methods, ranging from adaptive design of experiments, to large-scale inference, to using machine learning to identify heterogeneous treatment effects, to high-dimensional causal inference with observational data.

Required Skills

• Develop new methods and work collaboratively with engineers to develop internal and open-source tools.
• Provide technical leadership in the area of experimentation and causal inference.

• PhD in statistics, political science, economics, biostatistics, or related field, and proven experience for applied problems in experimentation and causal inference. Familiarity with the potential outcomes framework.
• At least 4 years of industry research experience with Internet experiments ("A/B tests").
• Proficient in R and experience with Python, as well as query languages such as SQL, Hive, or Impala.
• At least one of the following:
  • Experience with experimental design, missing data, survey sampling, and/or panel data.
  • Experience with observational causal inference (e.g., regression adjustment, matching, propensity score stratification), or quasi-experimental methods (e.g., instrumental variables, regression discontinuity, interrupted time series).
  • Experience with bandit optimization, adaptive experimentation.
  • Experience with Bayesian, Empirical Bayes, or large-scale inference methods.

• Experience working with product teams to put novel research methods into practice.
• Experience with machine learning frameworks, such as PyTorch or Tensorflow.
• Knowledge of causal graphical models.