The Research Scientist in AI and Economics at Google will focus on conducting empirical research to evaluate the effects of AI on the economy. This role is part of the AI and Economy team, which aims to develop methodologies that leverage various datasets to measure productivity effects and labor market transformations. The position requires a strong academic background and the ability to translate complex economic insights for diverse audiences. The scientist will also contribute to the wider research community by publishing findings and collaborating with external partners.

• PhD in Economics, Quantitative Social Sciences, Statistics, or a related quantitative field, or equivalent practical experience.
• 4 years of post-PhD research experience in academia, research institutes, or industry research labs.
• Experience with causal inference, experimental or quasi-experimental design, and applied econometrics.
• One or more first-author papers accepted at or published in economics journals or peer-reviewed AI/CS venues.
• Experience in Python and standard scientific computing/ML libraries such as pandas, NumPy, PyTorch/Jax, scikit-learn, statsmodels.

• Conceptualize, execute, and publish peer-reviewed economic research evaluating the effects of AI on the economy.
• Apply causal frameworks to understand economic mechanisms from observational data.
• Pioneer new applications of Large Language Models and modern machine learning techniques to extract economic signals from datasets.
• Bridge standard econometrics with scalable data science workflows in Python.
• Advise cross-functional partners on data-driven economic strategy and potential policy implications.

• Employees at Google are often offered benefits like comprehensive health insurance, 401(k) matching, and flexible work arrangements, among other benefits.