Reddit aims to turn its advertising business into a massive, highly differentiated revenue driver by leveraging its passionate communities and building advanced data science solutions to maximize advertiser value.
Requirements
- Platform experience and a deep understanding of the ads ecosystem
- Demonstrated expertise in at least one of the following: Ads Creative & Format Evaluation, Measurement & Experimentation at Scale, Consumer or Customer Growth and Lifecycle Analysis
- 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
Responsibilities
- Build and deploy predictive models, optimization frameworks, and decision-support systems that power Reddit’s strategic investments in advertiser acquisition and retention.
- Define core business and performance metrics, and design robust methodologies to measure the impact of product and modeling changes on advertiser ROI and user experience.
- 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.
- Leverage causal inference, economic analysis, and large-scale data systems to solve novel problems in a rapidly evolving ad ecosystem.
- Take end-to-end ownership of complex problem spaces such as funnel acceleration and advertiser LTV.
Other
- Master's or Ph.D. in Statistics, Computer Science, Economics, Operations Research, or a related quantitative discipline
- For M.S. holders: 10+ years of industry experience in applied science, data science, or machine learning engineering roles
- For Ph.D. holders: 6+ years of relevant experience applied science, data science, or machine learning engineering roles
- 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
