Staff Data Scientist, Ads Measurement

About Reddit

Reddit is a community of communities, built on shared interests, passion, and trust. It's the internet's most authentic conversation space, attracting millions of daily active visitors who engage with diverse topics. Learn more at www.redditinc.com.

About the Ads Data Science Team

The Ads Data Science team leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights derived from experimentation and cutting-edge DS methods. We tackle challenging problems in ads and platform measurement, campaign management, advertiser growth, monetization, and brand/community engagement, using machine learning and statistical modeling.

About the Role

This highly experienced Staff Data Scientist will advance the intelligence powering the advertiser experience on Reddit. You will take deep ownership of high-impact problem spaces within advertising, specializing in measurement, identity, and signal quality. This is a high-impact, high-autonomy role where you'll influence strategic direction, set a high technical bar, and drive cross-functional initiatives.

Responsibilities

• Design the Future of Ads Identity: Develop and employ probabilistic models for identity resolution, linking on-platform and off-platform actions while honoring privacy.
• Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure for large-scale, high-velocity, low-bias testing.
• Maximize Signal for Predictive Performance: Define strategy for new signal sources, mathematically quantify their value, and work with modeling teams to incorporate them into predictive models, improving bidding efficiency and ROAS.
• Define Ground Truth & Evaluation Frameworks: Solve industry challenges in validating identity and measurement. Design objective functions and truth sets for model training and impact measurement.
• Lead Through Cross-Functional and Technical Influence: Collaborate with engineering, product, and sales to align on strategic goals, translate insights into action, and drive execution. Mentor others and champion best practices.

Qualifications

• Required:
• Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Physics, Economics, or Operations Research.
• For M.S. holders: 10+ years of industry experience in applied science or data science.
• For Ph.D. holders: 6+ years of industry experience in applied science or data science.
• Deep understanding of the ads ecosystem.
• Demonstrated expertise in at least one of the following:
• Measurement & Experimentation at Scale (lift and attribution focus).
• Identity Graph Creation & Resolution Methodology and Infrastructure.
• Predictive Modeling with Signal Loss.
• Advanced proficiency in statistical programming (Python or R) and SQL.
• Experience with machine learning or optimization techniques.
• Strong understanding of experimental design, causal inference, or A/B testing methodologies.
• Exceptional problem-solving and communication skills, with a track record of influencing partners.
• Experience in fast-paced, ambiguous environments with cross-functional teams.

Benefits

• Global Benefit programs for workspace, professional development, and caregiving support.
• Family Planning Support.
• Gender-Affirming Care.
• Mental Health & Coaching Benefits.
• Comprehensive Medical Benefits & Health Care Spending Account.
• Registered Retirement Savings Plan with matching contributions.
• Income Replacement Programs.
• Flexible Vacation & Paid Volunteer Time Off.
• Generous Paid Parental Leave.

Pay Transparency

This job posting may span multiple career levels. In addition to base salary, this role is eligible for equity (RSUs) and potentially commission. Reddit offers a comprehensive benefits package for US-based employees, including medical, dental, and vision insurance, 401(k) with employer match, and generous time off.

Base Salary Range (US-based): $217,000 - $303,900 USD.

Final offers are determined by skills, experience, and other factors.