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Anthropic

Regional Research Economist, Economic Research

Tokyo, Japan

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hirly's read of this role

Seniority
Mid level
Country
JP
Work mode
On-site / unstated
First seen by hirly
22 Oct 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

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 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 rigor 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.

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.

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- and 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; and 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 implementing frontier methods in causal inference and machine learning

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

Proficiency in Python, R, SQL, or similar tools for large-scale data analysis

Demonstrated ability to lead complex research projects from conception to publication

Demonstrated ability to communicate technical findings to diverse audiences

Demonstrated ability to build relationships across academic, policy, and industry communities

Preferred qualifications

Experience relevant to the study of AI’s impact on the economy, such as 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; or agent-based modeling and large-scale simulation

Experience working with novel datasets and measurement systems

Comfort learning new technical tools and frameworks

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

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Comput

Original posting on Anthropic's site ↗

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