Senior Staff Data Scientist, Consumer Relevance
Lead relevance measurement and evaluation for feeds and search using Python/R/SQL, causal inference, and experimentation to improve ranking algorithms.
- Compensation
- $232.5K–$325.5K / yr
- Location
- Remote - United States
- Work setup
- Remote
- Seniority
- Staff
- Employment
- Contract
- Experience
- 8+ years
- Category
- Data science
- Posted
Skills
Must have
- 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 methodo
- For M.S. holders: 12+ years of industry experience in applied science, data science, or relevance/ranking-focused roles
- For Ph.D. holders: 8+ years of industry experience in applied science, data science, or relevance/ranking-focused roles
- Deep expertise in metrics design and evaluation for ranking and recommendation systems, including offline metrics and counterfactual evaluation
- 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 ef
- Experience defining and validating quality metrics for content ranking, search, or recommendations at scale
- Strong theoretical grounding in experimental design, including power analysis, variance reduction techniques, and sequential testing as applied to relevance experiments
- Expert knowledge of SQL and proficiency in R and/or Python for statistical computing
- Demonstrated ability to influence product and organizational strategy through data-driven insights about content quality and user experience
- Excellent communication skills with the ability to explain nuanced statistical and ML concepts and tradeoffs to both technical and non-technical senior stakeholders
- Experience mentoring data scientists and building organizational capability in relevance evaluation and experimentation
- Comfortable in innovative and fast-paced environments with a bias toward action
Nice to have
- Published research or industry contributions in areas recommendation systems or causal inference for ranking
- Experience with social network or user-generated content platforms where community-level dynamics create non-trivial relevance and experimentation challenges
Full description
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 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit .
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 .
Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet.
Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes.
Reddit's relevance challenges are uniquely complex. Our platform is a deeply interconnected network of communities, contributors, and consumers - where the notion of "relevance" spans personalized content ranking, community discovery, and search across an enormous corpus of authentic, user-generated content. We need a senior technical leader who thrives on these hard problems and can raise the bar for how we measure, evaluate, and improve the quality of recommendations and search results across the entire Consumer organization.
As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on relevance measurement and evaluation, partnering closely with Feeds and Search ML teams to tackle the most complex ranking, recommendation, and retrieval challenges across Consumer. You will shape how Reddit understands content quality, define the metrics and analytical frameworks that guide relevance improvements, and influence product strategy through rigorous analysis and experimentation.
Responsibilities
- 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
- Develop metrics frameworks and offline evaluation approaches for ranking and recommendation systems, including proxy metrics that reliably predict long-term outcomes like retention, community health, and user satisfaction