Staff Data Scientist (Ads)

• Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability 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 that supports large-scale, high-velocity, low-bias testing for advertisers
• Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will mathematically quantify the value of these signals and work with modeling teams to incorporate them into predictive models, directly improving bidding efficiency and ROAS
• Define Ground Truth & Evaluation Frameworks: Solve the industry-wide challenge of validating identity and measurement. Design the objective functions and truth sets used to train our models and measure the incremental impact of our identity graph
• Lead Through Cross-Functional and Technical Influence: Collaborate deeply with engineering, product, and sales to align on strategic goals, translate insights into action, and drive execution. Set a high technical bar by mentoring others and championing best practices across modeling, experimentation, and measurement

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

• Deep understanding of the ads ecosystem

• Identity Graph Creation & Resolution Methodology and Infrastructure

• 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 roles

• Predictive Modeling with Signal Loss

• For Ph.D. holders: 6+ years of industry experience in applied science or data science roles

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

• Experience with machine learning or optimization techniques

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

• 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

• Demonstrated expertise in at least one of the following areas:

• Measurement & Experimentation at Scale (with focus on lift and attribution)