Anthropic
Transformative AI Research Economist, Economic Research
$320K–$405K
San Francisco, CA +1 · Full-time · Posted Mar 11, 2026
- Location
- San Francisco, CA
San Francisco, California, United States - Experience
- Years of experience required will correlate with the internal job level requirements for the position.
- Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience; PhD in Economics or exceptional candidate close to completion.
- Visa sponsorship
- Visa sponsorship is available, but not for every role or candidate; if an offer is made, Anthropic will make every reasonable effort to obtain a visa.
About the job
Build macroeconomic models and scenario forecasts to assess how transformative AI may affect growth, labor markets, productivity, income distribution, and economic governance, using observed AI interaction data.
What you'll do
- Build models and forecasting tools, including forecasts for GDP, productivity, and unemployment across AI-capability scenarios.
- Use Anthropic Economic Index data to ground projections and analyze distributional and governance questions.
- Publish research and briefs, develop AI-powered research tools, and engage with external research partners and stakeholders.
What they ask for
- PhD in Economics or exceptional candidate close to completion.
- Background in macroeconomics, growth theory, or public finance.
- Proficiency in Python, Julia, or similar for computational economics.
- Demonstrated ability to lead research projects through publication and communicate technical findings to diverse audiences.
Nice to have
- Experience with structural estimation, scenario-based or time-series forecasting, task-based technological change, computational methods, simulation, inequality, or LLMs in research.
- Facility with AI coding agents as part of a research workflow.
Pay
$320,000 — $405,000 USD base salary
Tools
Python, Julia
AI focus
Model the economic effects of transformative AI and develop forecasting and AI-powered research tools, using observed AI adoption and task-transformation patterns.
Model-written summary · the original posting is authoritative