Research Scientist, AI and Economics

What you'll do

• Design, execute, and publish economic research evaluating AI’s effects on the economy.
• Apply causal inference and econometric methods to observational data, using machine learning and language models to analyze unstructured datasets and product logs.
• Advise research, product, policy, and other partners on data-driven economic strategy and policy implications.

What they ask 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.
• At least one first-author paper accepted at or published in economics journals or peer-reviewed AI/CS venues; experience with Python and standard scientific computing/ML libraries.

Nice to have

• Experience combining structural econometrics or causal models with modern machine learning pipelines for high-dimensional, unstructured data.
• Research or collaboration experience focused on AI economics, digital economics, technology adoption, labor/productivity, or communicating technical methods to non-experts.

Pay

$207000 - $300000 (USD) base salary

Tools

Python, pandas, NumPy, PyTorch/Jax, scikit-learn, statsmodels, Large Language Models (LLMs)

AI focus

Research how AI affects adoption, productivity, labor markets, and economic surplus; apply LLMs, natural language processing, and machine learning to extract economic signals from unstructured data and product logs.