Senior Research Data Scientist, Meridian AI

• Lead the design and development of innovative measurement methodologies and products, setting the strategic technical direction for Meridian and AI development.
• Serve as the core bridge between classical data science and frontier AI by embedding rigorous Bayesian statistical frameworks into autonomous AI agents, encoding econometric reasoning, heuristic logic, and human analytical intuition into LLM-driven workflows from the ground up.
• Pioneer advanced quantitative methods by integrating cutting-edge causal inference, statistical modeling, and machine learning techniques to solve highly ambiguous and complex measurement challenges.
• Drive the research and development of next-generation Marketing Mix Modeling (MMM) methodologies, setting the technical strategy for integrating advanced econometric models into the Meridian AI product suite, ensuring Google remains at the forefront of marketing analytics.

Minimum qualifications:

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
• 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree.
• Experience with econometrics, machine learning and Bayesian statistics.

Preferred qualifications:

• 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.
  

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
• 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree.
• Experience with econometrics, machine learning and Bayesian statistics.