Remote PhD Data Science Intern - Media Mix Modeling

What you'll do

• Research and develop Media Mix Modeling algorithms across the full modeling lifecycle
• Build statistical models using time-series, panel, and observational marketing data
• Explore methodologies for media response curves, adstock effects, causal inference, and seasonality
• Develop validation frameworks and conduct simulations to assess model performance
• Translate research findings into production-ready algorithms and workflows

What they're looking for

• PhD in Statistics, Economics, Econometrics, Applied Mathematics, Data Science, or related field
• Strong theoretical foundation in statistical modeling, econometrics, time-series analysis, and causal inference
• End-to-end model development experience from problem formulation through implementation
• Strong Python programming skills and experience with large, complex datasets
• Ability to work independently while collaborating with senior technical team

Pay and perks

• Full-time, paid internship for 3 months
• Compensation based on experience