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Research Economist, Economic Research
Job Description:
- 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
Requirements:
- 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.
Benefits:
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours
- Lovely office space in which to collaborate with colleagues
