Principal Data Scientist (Ads)

• Reddit’s Ads Data Science team is seeking a highly motivated Principal Data Scientist to drive the strategic application of advanced quantitative methods across our advertising platform to advance the intelligence powering the advertiser experience on Reddit
• In this pivotal leadership role, you will be responsible for defining and implementing the next generation of foundational data science solutions, leveraging expertise in statistics, econometrics, machine learning and/or other quantitative methods to optimize Reddit’s Ads marketplace
• You will partner closely with Analytics Engineering to ensure our underlying data systems are continuously upleveled to support advanced analysis and modeling at scale
• You will be a strategic partner, collaborating closely with Product, Engineering, and Business leaders to establish the long-term vision for measurement, prediction, and optimization
• As a thought leader, you will champion scientific rigor, causal inference, and economic modeling, while providing deep mentorship to the broader team
• Define the future of Ads Data Science: Own the design and long-term evolution of our core Ads Data Science solutions and infrastructure, building for the next several years of continued scale, revenue growth, and relevance
• Strategic leadership & scientific roadmap: Identify fundamental gaps and opportunities in our current systems (including platform, auction, targeting, and full-funnel relevance models). Lead the strategic design and scientific roadmap for new solutions to significantly improve Advertiser ROI, User experience, and Reddit revenue
• Drive end-to-end impact: Take end-to-end ownership of complex problem domains such as full funnel acceleration, advertiser lifetime value (LTV), and developing advanced predictive and causal frameworks that power Reddit’s strategic investments
• Establish scientific standards: Define and codify best practices for large-scale statistical modeling, economic analysis, causal inference, offline model evaluation, and A/B experimentation to ensure scientific rigor and trust across the Ads data science and engineering teams
• Technical deep dive & authority: Be the undisputed domain authority for data scientists, engineers, and product managers on complex problems involving large-scale behavioral data, foundational models for strategic insights, and the economics of marketplace dynamics
• Translate ambiguity into outcomes: Influence the design and definition of core business and performance metrics, robust measurement methodologies, and collaborate deeply with cross-org XFNs to align on strategic goals and translate insights into tangible action
• Influence and uplevel the organization: Lead technically minded peers and mentor senior data scientists, influencing technical and statistical direction across the entire product and engineering organization, and championing innovation in ad systems through advanced quantitative techniques

Benefits

• Comprehensive health benefits

• Flexible vacation & Reddit global days off

• Family planning funds & 4+ months paid parental leave

• Personal & professional development funds

• Paid volunteer time off

• Workspace & home office benefits

• Experience working in fast-paced, ambiguous environments with cross-functional teams

• Demonstrated expertise in at least one of the following: ads marketplace understanding, auctioning/bidding, ads creative & format evaluation, measurement & experimentation at scale

• Strong understanding of experimental design, causal inference, or A/B testing methodologies

• Proven experience in influencing large (500+ engineers/data scientists) organizations on technical direction, statistical rigor, and machine learning best practice

• Exceptional problem-solving and communication skills, with a track record of influencing product and engineering partners

• For Ph.D. holders: 8+ years of relevant experience applied science, data science, or machine learning engineering roles

• Advanced proficiency in statistical programming (Python or R) and SQL

• Experience with statistical analysis, economic modeling, foundational machine learning and/or optimization techniques

• For M.S. holders: 12+ years of industry experience in applied science, data science, or machine learning engineering roles

• Master’s or Ph.D. in Economics, Statistics, Computer Science, Operations Research, or a related quantitative discipline

• In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI)

• You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews