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Senior Staff Data Scientist - Consumer Experimentation

🕒 yesterday
Causal InferenceExperimentation MethodologyStatistical AnalysisSQL

📜 Description

  • Serve as the technical authority on experimentation methodology across Consumer, setting standards for design, analysis, and interpretation of experiments in a complex, networked environment
  • Tackle the hardest experimentation problems at Reddit, including spillover and network effects, interference between treatment and control, two-sided experimentation, and long-run effect estimation
  • Develop and advance methods for causal inference in settings where standard randomization assumptions are violated, such as cluster-randomized designs, switchback experiments, and synthetic control approaches
  • Design experimentation frameworks and guardrail metrics that account for ecosystem-level effects, ensuring product teams can measure true causal impact rather than biased local estimates
  • Build and scale self-serve experimentation tools, platforms, and best-practice documentation that increase experimentation velocity and literacy across product, engineering, and design teams
  • Mentor and elevate other data scientists across the organization on experimentation best practices, causal reasoning, and statistical rigor

🛠️ Requirements

  • Ph.D. in Statistics, Econometrics, Economics, Computer Science, or a related quantitative field with a strong focus on causal inference or experimentation methodology; or M.S. with equivalent depth of expertise
  • For M.S. holders: 12+ years of industry experience in applied science, data science, or experimentation-focused roles
  • For Ph.D. holders: 8+ years of industry experience in applied science, data science, or experimentation-focused roles
  • Deep expertise in causal inference, including practical experience with challenges such as network interference / spillovers, two-sided experimentation, switchback designs, cluster randomization, and/or synthetic
  • Strong theoretical grounding in experimental design, including power analysis, variance reduction techniques, sequential testing, and multiple comparison corrections
  • Experience with experimentation platforms at scale (e.g., building or significantly extending an internal experimentation platform)
  • Expert knowledge of SQL and proficiency in R and/or Python for statistical computing

Benefits

  • Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support • Family Planning Support
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