Senior Staff Data Scientist – Consumer Experimentation

This is a fully remote position, open to applicants in Canada.

📋 Description

• Act as the technical expert on experimentation methodologies within the Consumer sector, establishing standards for the design, analysis, and interpretation of experiments in a complex, interconnected environment.

• Address the most challenging experimentation issues at Reddit, including spillover and network effects, interference between treatment and control groups, two-sided experiments, and long-term effect estimation.

• Innovate and enhance methods for causal inference in scenarios where conventional randomization assumptions may not hold, such as cluster-randomized designs, switchback experiments, and synthetic control techniques.

• Create experimentation frameworks and guardrail metrics that consider ecosystem-level impacts, enabling product teams to measure genuine causal effects rather than skewed local estimates.

• Discover opportunities where enhanced experimentation methodologies can reveal product insights that were previously unquantifiable or unclear.

• Develop and expand self-service experimentation tools, platforms, and best-practice documentation that improve experimentation speed and understanding across product, engineering, and design teams.

• Shape the long-term product strategy by fostering learning through well-structured experiments and translating experimental findings into clear, actionable insights for senior leadership.

• Guide and uplift fellow data scientists throughout the organization on best practices in experimentation, causal reasoning, and statistical integrity.

• Publish and disseminate methodological advancements internally and, when appropriate, externally to contribute to the wider experimentation and causal inference community.

⛳️ Requirements

• Ph.D. in Statistics, Econometrics, Economics, Computer Science, or a related quantitative discipline with a strong emphasis on causal inference or experimentation methodologies; or M.S. with equivalent depth of expertise.

• For M.S. degree holders: 12+ years of industry experience in applied science, data science, or roles focused on experimentation.

• For Ph.D. degree holders: 8+ years of industry experience in applied science, data science, or experimentation-centric roles.

• Extensive expertise in causal inference, including practical experience with challenges such as network interference/spillovers, two-sided experimentation, switchback designs, cluster randomization, and/or synthetic control methods.

• Solid theoretical foundation in experimental design, including power analysis, variance reduction techniques, sequential testing, and multiple comparison corrections.

• Experience with large-scale experimentation platforms (e.g., building or significantly enhancing an internal experimentation platform).

• Proficient in SQL with expert knowledge of R and/or Python for statistical analysis.

• Proven experience in designing and analyzing experiments at scale within complex or interconnected environments.

• Ability to influence product and organizational strategy through insights gained from experimentation.

• Capability to address ambiguous, technically complex problems and resolve them in a structured, hypothesis-driven manner.

• Excellent communication skills to convey nuanced statistical concepts and trade-offs to both technical and non-technical senior stakeholders.

• Experience mentoring data scientists and building organizational capacity in experimentation and causal reasoning.

• Comfort in dynamic and fast-paced environments with a focus on action.

🏝️ Benefits

• Global benefit programs tailored to your lifestyle, encompassing workspace, professional development, and caregiving support.

• Family planning assistance.

• Gender-affirming care.

• Mental health and coaching benefits.

• Comprehensive medical benefits and health care spending account.

• Registered retirement savings plan with matching contributions.

• Income replacement programs.

• Flexible vacation and paid volunteer time off.

• Generous paid parental leave.