data
Posted 4 weeks agoStaff Data Scientist, Marketing
at Redditinc
United StatesRemote
Responsibilities
- Establish the "North Star" metrics and frameworks that determine how Reddit allocates hundreds of millions in marketing budget.
- Optimize Marketing ROI: Build and refine Media Mix Models (MMM) and Multi-Touch Attribution (MTA) systems to mathematically quantify the incremental impact of marketing spend.
- Bridge B2B & B2C Growth: Design unified frameworks to optimize marketing aimed at both new advertisers (driving revenue) and new users (driving engagement), identifying synergies where brand awareness for one fuels growth for the other.
- Develop methodologies to measure the long-term "halo effect" of brand marketing on organic growth.
- Lead Through Influence: Collaborate deeply with Marketing, Growth, and Finance to translate complex data insights into actionable budget shifts.
Requirements
- With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.
- The Marketing Science team at Reddit leverages data to maximize the impact of Reddit’s own marketing investments.
- We serve as the engine behind our growth, using advanced experimentation, causal inference, and econometrics to understand what drives users to Reddit and what brings advertisers to our platform.
- Reddit is looking for a highly experienced Staff Data Scientist to lead the strategy and technical execution of our Marketing Intelligence efforts.
- Education: Advanced degree (Master’s or Ph.D.) in Statistics, Economics, Mathematics, or a related quantitative field. • Experience:
- experience in marketing science, growth data science, or econometrics.
- Domain Expertise: Deep understanding of the marketing ecosystem, including hands-on
- experience with Marketing Mix Modeling (MMM), Incrementality Testing, and Customer Lifetime Value (LTV) prediction.
- Technical Skills: Advanced proficiency in Python or R and SQL.
- Experience building production-grade data pipelines and using machine learning for predictive modeling (e.g., churn prediction, lead scoring).
- Experience working in fast-paced environments where you must navigate ambiguity and build frameworks from the ground up. Preferred