Senior Staff Data Scientist - Consumer Experimentation

About Reddit

Reddit is a vibrant community of communities, built on shared interests, passion, and trust. It hosts over 100,000 active communities and serves approximately 126 million daily active unique visitors, making it a primary source of information and authentic conversations online. Reddit is poised for significant innovation and growth, offering a unique chance to influence one of the internet's most influential platforms.

About the Role

As a Senior Staff Data Scientist on the Consumer team, you will be the foremost expert on experimentation methodology, tackling the most complex and high-stakes experimentation challenges across the Consumer organization. You will shape how Reddit learns from its experiments, ensure valid causal conclusions are drawn despite network effects and interference, and influence product strategy through rigorous experimental design and analysis. This role is critical for understanding how to better connect people to the best information and communities on Reddit.

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

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support.
• Family Planning Support.
• Gender-Affirming Care.
• Mental Health & Coaching Benefits.
• Comprehensive Medical Benefits & Health Care Spending Account.
• Registered Retirement Savings Plan with matching contributions.
• Income Replacement Programs.
• Flexible Vacation & Paid Volunteer Time Off.
• Generous Paid Parental Leave.

Equal Opportunity Employer

Reddit is proud to be an equal opportunity employer and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Candidate Privacy

Interviews may be recorded, transcribed, and summarized by AI. Candidates will have the opportunity to opt out. Personal information collected includes identifiers, professional/employment info, and audio/video recordings. This data is used for employment evaluation and will not be sold or used for marketing. Recordings will be deleted promptly after a hiring decision. Refer to the Candidate Privacy Policy for more details.