Staff Data Scientist, Marketing
Leads strategy and technical execution for Reddit's marketing intelligence, building MMM and MTA systems to optimize B2B advertiser acquisition and B2C user growth. Requires advanced degree, 6-10+ years experience in marketing science/econometrics, and expertise in Python/R/SQL for causal inference and experimentation.
About the job
Responsibilities
- Set Long-Term Marketing Strategy: Define the 2–3 year technical roadmap for marketing measurement. 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.
- Advance Causal Inference & Experimentation: Lead the design of complex "always-on" incrementality testing and geo-holdout experiments. 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.
- Be the Technical Guide for the Team: Mentor junior scientists and set the technical bar for code quality and statistical rigor across the Marketing organization.
Minimum Qualifications
Education: Advanced degree (Master’s or Ph.D.) in Statistics, Economics, Mathematics, or a related quantitative field.
Experience:
- For M.S. holders: 10+ years of industry experience in marketing science, growth data science, or econometrics.
- For Ph.D. holders: 6+ years of industry experience.
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).
Strategic Communication: Proven track record of influencing C-suite stakeholders and "translating" complex statistical concepts into business strategy.
Adaptability: Experience working in fast-paced environments where you must navigate ambiguity and build frameworks from the ground up.
Preferred Qualifications
- Experience with Bayesian structural time series or causal inference libraries.
- Previous experience in a high-growth marketplace or social media platform.
- A passion for the Reddit community and an understanding of our unique "Ads-as-Content" philosophy.
Benefits
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
Base Salary Range: $217,000—$303,900 USD (plus equity and benefits)
Skills
Python, R, SQL, Marketing Mix Modeling, Multi-Touch Attribution, Causal Inference, Incrementality Testing, Machine Learning, Bayesian Structural Time Series, Media Mix Models
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