Senior Staff Data Scientist – Consumer Relevance

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Reddit, Inc.

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2005

👥 B2C

📱 Media

🌍 Social Impact

B2C • Media • Social Impact

Reddit, Inc. is a social media platform that acts as a hub for thousands of communities, where users can engage in diverse conversations ranging from breaking news to niche interests. It enables users to post, comment, and vote on content, fostering a vibrant online community. Millions of people globally connect and share their passions on Reddit, creating a dynamic environment for authentic human interaction.

📋 Description

• 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 • Design and analyze experiments for relevance features, accounting for challenges unique to networked platforms such as spillover effects between communities, interference between contributors and consumers, and long-run impacts of ranking changes on content supply • Identify opportunities where improved measurement and analysis can unlock product insights that were previously unmeasurable or ambiguous, particularly around content quality, search intent understanding, and personalization effectiveness • Partner deeply with ML engineers and product teams to translate model performance metrics into user-facing impact • Influence the long-term product strategy for Feeds and Search by synthesizing insights from experimentation, observational analysis, and metric deep-dives into clear, actionable recommendations for senior leadership • Mentor and elevate other data scientists across the organization on relevance evaluation, experimentation best practices for ranking systems, causal reasoning, and statistical rigor • Publish and share methodological advances internally and, where appropriate, externally to contribute to the broader relevance, recommendation systems, and experimentation community

🎯 Requirements

• 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 • 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 effect estimation, and ecosystem-level impacts • 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.

🏖️ Benefits

• 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 • Gender-Affirming Care • Mental Health & Coaching Benefits • Flexible Vacation & Paid Volunteer Time Off • Generous Paid Parental Leave