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 Transformative AI Research Economist at Anthropic, you will build macroeconomic models of AI that could be genuinely transformative and develop the scenario-based forecasting tools that let us reason quantitatively about economic trajectories with no historical precedent. You will work on questions of aggregate growth, income distribution, and economic governance under scenarios that most of the profession has not yet modeled seriously.
You will ground projections in microeconomic signals from the Anthropic Economic Index — usage patterns across millions of real-world AI interactions, surfaced through privacy-preserving measurement — so that scenario forecasts are disciplined by what we actually observe about task transformation and productivity. You will use frontier methods in growth theory, computational macro, and structural estimation, and contribute to AI-powered tools that expand what economic research can do.
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, we analyze millions of real-world AI interactions to understand how AI augments and automates work across different occupations and tasks.
Responsibilities
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Build macroeconomic models of transformative AI spanning growth, labor markets, and income distribution
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Develop and maintain scenario-based forecasting tools; publish forecasts for GDP, productivity, and unemployment under a range of AI-capability trajectories
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Ground macroeconomic projections in microeconomic data from the Anthropic Economic Index, constraining theory with observed patterns of adoption and task transformation
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Analyze questions of income distribution and economic governance under transformative-AI scenarios
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Contribute to the development of AI-powered research tools for economics
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Contribute to Economic Index Reports and publish Research Briefs on first-order questions as they arise
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Build and maintain relationships with academic institutions, policy think tanks, and other research partners
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Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders
You May Be a Good Fit If You Have
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PhD in Economics, or an exceptional candidate close to completion
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Background in macroeconomics, growth theory, or public finance ideally with exposure to task-based frameworks and labor economics
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A research record that engages seriously with the possibility of transformative AI — you treat the scenarios in this posting as live questions worth modeling rigorously, not speculation to be hedged against
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Relevant experience in some of:
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Macroeconomic modeling and structural estimation
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Scenario-based and time-series forecasting
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Task-based approaches to technological change
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Computational methods, agent-based modeling, or large-scale simulation
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Income distribution and inequality
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Using large language models in the research workflow
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Technical skills including:
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Proficiency in Python, Julia, or similar for computational economics
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Facility with AI coding agents as part of a research workflow
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Comfort learning new technical tools and frameworks
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Demonstrated ability to:
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Lead research projects from conception to publication
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Ship on tight timelines and revise in public as new data arrives
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Communicate technical findings to diverse audiences
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Strong interest in ensuring AI development benefits humanity
Some Examples of Our Recent Work
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Labor market impacts of AI: A new measure and early evidence
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Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption
Additional Information
For this role, we're looking for candidates who combine rigorous macroeconomic theory with computational fluency, and who are willing to model economic scenarios that fall outside the profession's usual range. The ideal candidate works at the intersection of growth theory, forecasting, and frontier AI.
Deadline to apply: None. Applications are reviewed on a rolling basis
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:$300,000—$405,000 USDLogistics
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 & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.