Regional Research Economist, Economic Research

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a Regional Research Economist at Anthropic, you will work to collaborate with governments, academia, industry, and civil society in your region to measure and understand AI's effects on the economy and explore research-driven policy interventions. You will contribute to the development of the Anthropic Economic Index and its extension to generate regionally-relevant insights, establish new methodologies to measure the usage, diffusion, and impact of AI throughout the economy, and work to broaden access to and usage of the insights generated by the Index. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigour will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions. Our team combines rigorous empirical methods with novel measurement approaches. We're building first-of-its-kind datasets tracking AI's impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system (Clio), we analyze millions of real-world AI interactions to understand how AI augments and automates work across different occupations and tasks. Key responsibilities - Build and maintain relationships with academic institutions, policy think tanks, and other research partners as the primary point of contact for these organizations on economic impact work in your region - Advance research collaborations that answer country- or regional-specific economic impact questions - Translate research insights into actionable recommendations for policy discussions - Make fundamental contributions to the development and expansion of the Anthropic Economic Index, including country/regional-specific analysis - Design and collaborate on empirical research on AI's economic effects with governments, academia, industry, and civil society in your region - Develop new methodological approaches, in collaboration with partners in your region, 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 - Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection - Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders Minimum qualifications - 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 - Demonstrated experience working in and relevant relationships across the region - 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 Representative projects - How Australia Uses Claude: Findings from the Anthropic Economic Index - Anthropic Economic Index Report: Economic Primitives - Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption - Estimating AI productivity gains from Claude conversations - The Anthropic Economic Index Additional Information For this role, we're looking for candidates who can combine rigorous economic analysis with novel measurement approaches to understand AI's transformative effects on the economy. The ideal candidate will be comfortable working at the intersection of empirical economics, technological change, and policy impact. T

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. Demonstrated experience working in and relevant relationships across the region. 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.