About Google
Learn more about Google. Explore our innovative AI products and services, and how we. Backed by Kleiner Perkins.
About the role
As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies.
What they're looking for
- 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
More about this role
- Conceptualize, execute, and publish peer-reviewed economic research, working papers, and research blogs evaluating the effects of AI on the economy. Output form-factor may vary.
- Apply causal frameworks (e.g., difference-in-differences, instrumental variables, regression discontinuity, synthetic controls, quasi-experiments) to understand economic mechanisms from observational data.
- Pioneer new applications of Large Language Models (LLMs), natural language processing, and modern machine learning techniques to structure, classify, and extract high-fidelity economic signals from massive unstructured datasets and product logs.
- Bridge standard econometrics with scalable data science workflows in Python, ensuring methodological matches production-scale execution.
- Advise cross-functional partners in Research, GDM Google Cloud, Policy, and Product leadership on data-driven economic strategy and potential policy implications.
- 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...
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