Senior Staff Data Scientist - Consumer Experimentation

Senior Staff Data Scientist - Consumer Experimentation Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit . 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 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 Family Planning Support Mental Health & Coaching Benefits Pay Transparency This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. The base salary range for this position is: $232,500 - $325,500 USD To learn more about benefits, visit #J-18808-Ljbffr