Senior Staff Data Scientist - Consumer Experimentation

Details

Reddit's Consumer Data Science team helps the company better connect people to relevant information and communities. The Consumer organization faces complex experimentation challenges because Reddit is an interconnected network of communities, contributors, and consumers where standard A/B testing assumptions may not hold.

This role serves as the senior technical authority on experimentation methodology across Consumer. The position focuses on causal inference, network effects, experimentation rigor, and translating experimental results into product strategy.

Responsibilities

• Serve as the technical authority on experimentation methodology across Consumer, setting standards for experiment design, analysis, and interpretation in a complex, networked environment.
• Address complex experimentation problems, including spillover and network effects, treatment-control interference, two-sided experimentation, and long-run effect estimation.
• Develop methods for causal inference when standard randomization assumptions are violated, including cluster-randomized designs, switchback experiments, and synthetic control approaches.
• Design experimentation frameworks and guardrail metrics that account for ecosystem-level effects and help product teams measure true causal impact.
• Identify opportunities where improved experimentation methodology can unlock previously unmeasurable or ambiguous product insights.
• Build and scale self-service experimentation tools, platforms, and best-practice documentation to increase experimentation velocity and literacy across product, engineering, and design teams.
• Influence long-term product strategy by driving learning through well-designed experiments and translating results into actionable recommendations for senior leadership.
• Mentor and develop data scientists on experimentation best practices, causal reasoning, and statistical rigor.
• Publish and share methodological advances internally and, where appropriate, externally.

Requirements

• Ph.D. in Statistics, Econometrics, Economics, Computer Science, or a related quantitative field with a strong focus on causal inference or experimentation methodology, or an M.S. with equivalent depth of expertise.
• M.S. holders: 12 or more years of industry experience in applied science, data science, or experimentation-focused roles.
• Ph.D. holders: 8 or more years of industry experience in applied science, data science, or experimentation-focused roles.
• Deep expertise in causal inference, including practical experience with network interference and 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, such as 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.
• Ability to influence product and organizational strategy through experimentation insights.
• Ability to solve ambiguous and technically complex problems using a structured, hypothesis-driven approach.
• Excellent communication skills, including the ability to explain nuanced statistical concepts and tradeoffs to technical and non-technical senior stakeholders.
• Experience mentoring data scientists and building organizational capability in experimentation and causal reasoning.
• Comfortable working in innovative, fast-paced environments with a bias toward action.

Preferred Qualifications

• Published research or industry contributions involving 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 complex experimentation challenges.

Benefits

• Comprehensive healthcare benefits and income replacement programs.
• 401(k) with employer match.
• Global benefit programs covering workspace, professional development, caregiving support, and other needs.
• Family planning support.
• Gender-affirming care.
• Mental health and coaching benefits.
• Flexible vacation and paid volunteer time off.
• Generous paid parental leave.
• Equity in the form of restricted stock units.
• U.S.-based employee benefits including medical, dental, and vision insurance.

Compensation

The base salary range is $232,500–$325,500 USD. The role may also be eligible for equity in the form of restricted stock units and, depending on the position offered, commission.