Senior Staff Data Scientist, Consumer Relevance

🕒 June 1

🇺🇸 United States – Remote

💵 $232.5k - $325.5k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 32%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Reddit, Inc.

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2005

💼 Consulting

📣 Marketing

📱 Media

Consulting • Marketing • Media

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 • Develop metrics frameworks and offline evaluation approaches for ranking and recommendation systems • Design and analyze experiments for relevance features, accounting for spillover effects, contributor-consumer interference, and long-run ranking impacts • Identify opportunities where improved measurement and analysis can unlock product insights • Partner with ML engineers and product teams to translate model performance metrics into user-facing impact • Influence long-term product strategy for Feeds and Search through experimentation, observational analysis, and metric deep-dives • Mentor and elevate data scientists on relevance evaluation, experimentation, causal reasoning, and statistical rigor • Publish and share methodological advances internally and, where appropriate, externally

🎯 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 • Experience with 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 • Expert knowledge of SQL and proficiency in R and/or Python for statistical computing • Ability to influence product and organizational strategy through data-driven insights • Excellent communication skills with technical and non-technical senior stakeholders • Experience mentoring data scientists and building organizational capability • Comfort 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 • Equity in the form of restricted stock units • Medical, dental, and vision insurance • Opportunity to opt out of interview recording, transcription, and summarization