Regional Research Economist, Economic Research

Details

Anthropic is building reliable, interpretable, and steerable AI systems and seeks a Regional Research Economist to collaborate with governments, academia, industry, and civil society in the region to measure and understand AI's effects on the economy and explore research-driven policy interventions.

Responsibilities

• Build and maintain relationships with academic institutions, policy think tanks, and other research partners as the primary point of contact for economic impact work in your region.
• Advance research collaborations answering country- or regional-specific economic impact questions.
• Translate research insights into actionable recommendations for policy discussions.
• Contribute 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) for studying AI's impact on labor markets, productivity and task transformation, economic inequality and displacement, industry-specific disruption and adaptation, and aggregate economic trajectories under varying AI-adoption scenarios.
• Work cross-functionally with other technical teams to improve measurement infrastructure and data collection.
• 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 implementing frontier methods in causal inference and machine learning.
• Demonstrated experience and 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, large-scale data analysis, econometric methods, large language models for social science research, policy-relevant economic research, experimental and quasi-experimental methods, macroeconomic modeling and time series forecasting, and agent-based modeling or large-scale simulation.
• Technical skills: 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, and build relationships across academic, policy, and industry communities.
• Strong interest in ensuring AI development benefits humanity and comfort working with AI systems and thinking 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

• Annual Salary: $307,200 - $331,200 SGD.
• Location-based hybrid policy: staff are expected to be in one of Anthropic's offices at least 25% of the time (some roles may require more time onsite).
• Visa sponsorship: Anthropic states they do sponsor visas and retain an immigration lawyer to help, though sponsorship is not guaranteed for every role/candidate.
• Minimum education listed as Bachelor’s degree or equivalent combination of education, training, and/or experience (posting requires PhD in Economics in Minimum qualifications section).
• Anthropic is a public benefit corporation headquartered in San Francisco; the role is based in Singapore.
• The posting encourages applicants who may not meet every qualification and emphasizes diversity and representation.

How we're different

• Anthropic emphasizes large-scale "big science" research efforts, collaboration across teams, and communication skills. They view AI research as an empirical science with connections to disciplines beyond computer science.