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.
Requirements
Demonstrated expertise in at least one of the following: ads marketplace understanding, auctioning/bidding, ads creative & format evaluation, measurement & experimentation at scale
Master's or Ph.D. in Economics, Statistics, Computer Science, Operations Research, or a related quantitative discipline
For M.S. holders: 12+ years of industry experience in applied science, data science, or machine learning engineering roles
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
Strong understanding of experimental design, causal inference, or A/B testing methodologies
Exceptional problem-solving and communication skills, with a track record of influencing product and engineering partners
Experience working in fast-paced, ambiguous environments with cross-functional teams
Proven experience in influencing large (500+ engineers/data scientists) organizations on technical direction, statistical rigor, and machine learning best practice.
Benefits
Comprehensive Healthcare Benefits and Income Replacement Programs
401k Match
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Reddit Global Days off
Generous paid Parental Leave
Paid Volunteer time off
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Master's in EconomicsMaster's in StatisticsMaster's in Computer ScienceMaster's in Operations ResearchPh.D. in EconomicsPh.D. in StatisticsPh.D. in Computer SciencePh.D. in Operations Research