Principal Data Scientist, Ads

Details

Reddit's Ads Data Science team is seeking a highly motivated Principal Data Scientist to drive the strategic application of advanced quantitative methods across its advertising platform and improve the advertiser experience on Reddit.

This leadership role is responsible for defining and implementing foundational data science solutions using statistics, econometrics, machine learning, and other quantitative methods to optimize Reddit's Ads marketplace. The role partners with Analytics Engineering to improve underlying data systems for large-scale analysis and modeling, and collaborates with Product, Engineering, and Business leaders on the long-term vision for measurement, prediction, and optimization.

Responsibilities

• Own the design and long-term evolution of core Ads Data Science solutions and infrastructure.
• Identify gaps and opportunities across the platform, auction, targeting, and full-funnel relevance models.
• Lead the strategic design and scientific roadmap for solutions that improve advertiser ROI, user experience, and Reddit revenue.
• Take end-to-end ownership of complex domains such as full-funnel acceleration, advertiser lifetime value (LTV), and predictive and causal frameworks.
• Define best practices for large-scale statistical modeling, economic analysis, causal inference, offline model evaluation, and A/B experimentation.
• Serve as a technical authority for data scientists, engineers, and product managers working with large-scale behavioral data, foundational models, and marketplace economics.
• Influence the definition of business and performance metrics and measurement methodologies.
• Collaborate with cross-functional teams to align on strategic goals and translate insights into action.
• Lead technically minded peers and mentor senior data scientists.
• Influence technical and statistical direction across the product and engineering organization.

Requirements

• Demonstrated expertise in at least one of the following: ads marketplace understanding, auctioning and bidding, ads creative and format evaluation, or measurement and 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 or more years of industry experience in applied science, data science, or machine learning engineering roles.
• For Ph.D. holders, 8 or more years of relevant experience in applied science, data science, or machine learning engineering roles.
• Advanced proficiency in statistical programming with Python or R and SQL.
• Experience with statistical analysis, economic modeling, foundational machine learning, and/or optimization techniques.
• Strong understanding of experimental design, causal inference, or A/B testing methodologies.
• Exceptional problem-solving and communication skills, with experience influencing product and engineering partners.
• Experience working in fast-paced, ambiguous environments with cross-functional teams.
• Proven experience influencing large organizations of 500 or more engineers and data scientists on technical direction, statistical rigor, and machine learning best practices.

Benefits

• Comprehensive healthcare benefits and income replacement programs.
• 401(k) with employer match.
• Global benefits programs covering workspace, professional development, and caregiving support.
• Family planning support.
• Gender-affirming care.
• Mental health and coaching benefits.
• Flexible vacation and paid volunteer time off.
• Generous paid parental leave.
• Equity in the form of restricted stock units.
• U.S.-based employee benefits including medical, dental, and vision insurance.

Compensation

The base salary range is $268,000–$365,100 USD. The position may also be eligible for a commission depending on the position offered.