Senior Staff Data Scientist - Consumer Experimentation
As a Senior Staff Data Scientist, you will be the go-to expert on experimentation methodology for Reddit's Consumer team, tackling complex challenges like network effects and influencing product strategy through rigorous experimental design and analysis.
233k – 326k/yr
Remote8+ YOEData Science
About the role
Responsibilities:
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
Identify opportunities where improved experimentation methodology can unlock product insights that were previously unmeasurable or ambiguous
Build and scale self-serve experimentation tools, platforms, and best-practice documentation that increase experimentation velocity and literacy across product, engineering, and design teams
Influence the long-term product strategy by driving learning through well-designed experiments and translating experimental results into clear, actionable recommendations for senior leadership
Mentor and elevate other data scientists across the organization on experimentation best practices, causal reasoning, and statistical rigor
Publish and share methodological advances internally and, where appropriate, externally to contribute to the broader experimentation and causal inference community
Required Qualifications:
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 control methods
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
Track record of designing and analyzing experiments at scale in complex or networked environments
Demonstrated ability to influence product and organizational strategy through experimentation insights
Demonstrated ability to take ambiguous, technically complex problems and solve them in a structured, hypothesis-driven way
Excellent communication skills with the ability to explain nuanced statistical concepts and tradeoffs to both technical and non-technical senior stakeholders
Experience mentoring data scientists and building organizational capability in experimentation and causal reasoning
Comfortable in innovative and fast-paced environments with a bias toward action
Preferred Qualifications:
Published research or industry contributions in areas such as interference in experiments, network experimentation, or marketplace causal inference
Familiarity with Bayesian experimental methods, bandit algorithms, or adaptive experimental designs
Experience with social network or user-generated content platforms where community-level dynamics create non-trivial experimentation challenges
Benefits:
Comprehensive Healthcare Benefits and Income Replacement Programs
401k with Employer Match
Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
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