Senior Staff Data Scientist, Consumer Experimentation

What you'll do

• Serve as the technical authority on experimentation methodology and standards across the Consumer organization.
• Solve complex experimentation problems including spillover effects, network interference, and two-sided experiments.
• Develop advanced causal inference methods for environments where standard randomization assumptions are violated.
• Design experimentation frameworks and guardrail metrics to ensure accurate measurement of true causal impact.
• Build and scale self-serve experimentation tools, platforms, and best-practice documentation for internal teams.
• Influence long-term product strategy by translating experimental results into actionable recommendations for leadership.
• Mentor other data scientists on experimentation best practices, causal reasoning, and statistical rigor.
• Publish methodological advances internally and externally to contribute to the broader research community.

What we're looking for

• Ph.D. in Statistics, Econometrics, Economics, Computer Science, or a related quantitative field with a focus on causal inference or experimentation.
• M.S. degree with equivalent depth of expertise in causal inference or experimentation methodology.
• 12+ years of industry experience in applied science, data science, or experimentation-focused roles for M.S. holders.
• 8+ years of industry experience in applied science, data science, or experimentation-focused roles for Ph.D. holders.
• Deep expertise in causal inference including network interference, two-sided experimentation, switchback designs, cluster randomization, and synthetic control methods.
• Strong theoretical grounding in experimental design, power analysis, variance reduction, sequential testing, and multiple comparison corrections.
• Expert knowledge of SQL and proficiency in R and/or Python for statistical computing.
• Experience building or extending large-scale experimentation platforms and mentoring other data scientists on causal reasoning.