AI & Economics Research Scientist

Google LLC; New York, Mountain View (NY, CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google LLC seeks a Share Research Scientist in AI and Economics to lead empirical economic research analyzing the impact of AI on productivity and labor markets. You will design large-scale experiments, publish findings, and translate insights for executives and policy makers.

The role requires a PhD in a quantitative field and strong publication record, with collaboration across ML, policy, and product teams. Location flexibility includes New York, NY or Mountain View, CA.

Qualifications

• 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.

Responsibilities

• Conceptualize, execute, and publish peer-reviewed economic research evaluating AI effects on the economy.
• Apply causal frameworks to understand mechanisms from observational data.
• Pioneer applications of LLMs, NLP, and ML techniques to structure high-fidelity signals from large datasets.
• Bridge econometrics with scalable data science workflows in Python for production-scale execution.
• Advise cross-functional partners on data-driven economic strategy and policy implications.

Skills

causal inference

experimental design

applied econometrics

Python

pandas

NumPy

PyTorch/Jax

scikit-learn

statsmodels

Education

PhD in Economics or related quantitative field

Tools

pandas

NumPy

PyTorch/Jax

scikit-learn

statsmodels

Job description

Google LLC seeks a Share Research Scientist in AI and Economics to lead empirical economic research analyzing the impact of AI on productivity and labor markets. You will design large-scale experiments, publish findings, and translate insights for executives and policy makers.

The role requires a PhD in a quantitative field and strong publication record, with collaboration across ML, policy, and product teams. Location flexibility includes New York, NY or Mountain View, CA.