Senior Staff Data Scientist (Consumer Relevance)

Join Reddit as a Senior Staff Data Scientist on the Consumer team. You will be the expert on relevance measurement and evaluation, shaping how Reddit understands content quality and influencing product strategy through rigorous analysis and experimentation. You will develop metrics frameworks, design and analyze experiments, and mentor other data scientists. This role requires expert knowledge of SQL, proficiency in R and/or Python, and a strong understanding of causal inference and experimentation methodology.

• As a Senior Staff Data Scientist on the Consumer team, you will be responsible for shaping how Reddit understands content quality, defining the metrics and analytical frameworks that guide relevance improvements, and influencing product strategy through rigorous analysis and experimentation.
• You will serve as the technical authority on relevance metrics and evaluation methodology across Consumer, setting standards for how we measure the quality of feeds, search results, and recommendations in a complex, community-driven environment.
• You will mentor and elevate other data scientists across the organization on relevance evaluation, experimentation best practices for ranking systems, causal reasoning, and statistical rigor.

• Expert knowledge of SQL and proficiency in R and/or Python for statistical computing
• Excellent communication skills with the ability to explain nuanced statistical and ML concepts and tradeoffs to both technical and non-technical senior stakeholders
• For M.S. holders: 12+ years of industry experience in applied science, data science, or relevance/ranking-focused roles
• Strong understanding of causal inference and experimentation methodology, including practical experience with challenges relevant to ranking systems such as novelty effects, position bias, long-run effect estimation, and ecosystem-level impacts
• Experience defining and validating quality metrics for content ranking, search, or recommendations at scale
• Experience mentoring data scientists and building organizational capability in relevance evaluation and experimentation
• For Ph.D. holders: 8+ years of industry experience in applied science, data science, or relevance/ranking-focused roles
• Strong theoretical grounding in experimental design, including power analysis, variance reduction techniques, and sequential testing as applied to relevance experiments
• Deep expertise in metrics design and evaluation for ranking and recommendation systems, including offline metrics and counterfactual evaluation
• Comfortable in innovative and fast-paced environments with a bias toward action
• Ph.D. in Statistics, Computer Science, Information Retrieval, Economics, or a related quantitative field with a strong focus on recommendation systems, ranking, causal inference, or evaluation methodology; or M.S. with equivalent depth of expertise
• Demonstrated ability to influence product and organizational strategy through data-driven insights about content quality and user experience
• Experience with social network or user-generated content platforms where community-level dynamics create non-trivial relevance and experimentation challenges
• Published research or industry contributions in areas recommendation systems or causal inference for ranking