Remote PhD Data Science Intern – Media Mix Modeling

About the Role

Duration: 3 months Employment: Full-time, Paid Internship Compensation: Based on experience Location: Remote Company: FocusKPI About the Role FocusKPI is seeking a highly motivated PhD Data Science Intern to join our team for a three-month, full-time engagement focused on the research, development, and advancement of Media Mix Modeling (MMM) algorithms. This is a hands-on, research-oriented role for someone with a strong foundation in statistics, econometrics, economics, or a closely related quantitative discipline who is interested in applying rigorous statistical methodology to real-world marketing and business problems. The ideal candidate will have deep theoretical knowledge combined with practical experience developing statistical models end-to-end—from problem formulation and data preparation through model development, validation, interpretation, and production implementation. The intern will work closely with senior data scientists and leadership to evaluate and enhance our MMM methodology, explore new modeling approaches, and translate advanced statistical techniques into scalable analytical solutions. What You Will Do Research and evaluate statistical and econometric approaches for Media Mix Modeling and marketing effectiveness measurement Develop, test, and enhance MMM algorithms across the full modeling lifecycle Work with time-series, panel, and observational marketing data to develop robust models of media response and business outcomes Explore methodologies for: Media response curves and saturation effects Adstock and carryover effects Incrementality and causal inference Channel interaction and synergies Seasonality, trends, and external factors Model regularization and variable selection Uncertainty estimation and statistical inference Bayesian and frequentist modeling approaches Develop model diagnostics and validation frameworks to assess model stability, predictive performance, statistical significance, and busi

Requirements & Qualifications

• Strong problem solving foundations, knowledge of modern engineering practices, and interest in technology systems.

Perks & Benefits

• Official mentor support
• verified hiring timeline
• and career progression.