About the job
As an Economist at Anthropic, you will work to measure and understand AI's effects on the global economy. You will make fundamental contributions to the development of the Anthropic Economic Index, establishing new methodologies to measure the usage, diffusion, and impact of AI throughout the economy using privacy-preserving tools and novel data sources. You will use frontier methods in econometrics, machine learning, and structural estimation.
Responsibilities
Make fundamental contributions to the development and expansion of the Anthropic Economic Index, including quarterly reports and industry-specific deep dives
Design and conduct empirical research on AI's economic effects, drawing on external data sources and the privacy-preserving measurement systems internally
Develop new methodological approaches for studying AI's impact on:
Labor markets and the future of work
Productivity and task transformation
Economic inequality and displacement
Industry-specific disruption and adaptation
Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios
Develop causal-inference tooling — e.g. surrogate indexes, heterogeneous-effect pipelines — to help Anthropic evaluate the downstream economic consequences of its own compute, product, and pricing decisions
Build and maintain relationships with academic institutions, policy think tanks, and other research partners
Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection
Translate research insights into actionable recommendations for both product decisions and policy discussions
Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders
Qualifications
Minimum
PhD in Economics
Strong track record of empirical research, particularly studies combining novel data sources and economic theory or those implementing frontier methods in causal inference and machine learning
Experience relevant to the study of AI’s impact on the economy, including:
Labor market analysis and occupational change
Task-based approaches to technological transformation
Large-scale data analysis and econometric methods
Large language models for social science research
Policy-relevant economic research
Experimental and quasi-experimental methods for causal inference
Macroeconomic modeling and time series forecasting
Agent-based modeling or large-scale simulation
Technical skills including:
Proficiency in Python, R, SQL, or similar tools for large-scale data analysis
Experience working with novel datasets and measurement systems
Comfort learning new technical tools and frameworks
Demonstrated ability to:
Lead complex research projects from conception to publication
Communicate technical findings to diverse audiences
Build relationships across academic, policy, and industry communities
Strong interest in ensuring AI development benefits humanity
Comfort working with AI systems and ability to think critically about their capabilities and limitations
Preferred
No preferred qualifications listed.