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We&#39;re building first-of-its-kind datasets tracking AI&#39;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.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Make fundamental contributions to the development and expansion of the Anthropic Economic Index, including quarterly reports and industry-specific deep dives</li>\n</ul>\n<ul>\n<li>Design and conduct empirical research on AI&#39;s economic effects, drawing on external data sources and the privacy-preserving measurement systems internally</li>\n</ul>\n<ul>\n<li>Develop new methodological approaches for studying AI&#39;s impact on:</li>\n</ul>\n<ul>\n<li>Labor markets and the future of work</li>\n</ul>\n<ul>\n<li>Productivity and task transformation</li>\n</ul>\n<ul>\n<li>Economic inequality and displacement</li>\n</ul>\n<ul>\n<li>Industry-specific disruption and adaptation</li>\n</ul>\n<ul>\n<li>Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios</li>\n</ul>\n<ul>\n<li>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</li>\n</ul>\n<ul>\n<li>Build and maintain relationships with academic institutions, policy think tanks, and other research partners</li>\n</ul>\n<ul>\n<li>Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection</li>\n</ul>\n<ul>\n<li>Translate research insights into actionable recommendations for both product decisions and policy discussions</li>\n</ul>\n<ul>\n<li>Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders</li>\n</ul>\n<p>You May Be a Good Fit If You Have:</p>\n<ul>\n<li>PhD in Economics</li>\n</ul>\n<ul>\n<li>Strong track record of empirical research, particularly studies combining 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Our models are foundational to planning, pricing, operational efficiency, and growth strategy — supporting key investment decisions and unlocking OpenAI’s full potential.</p>\n<p><strong>About the Role</strong></p>\n<p>We’re looking for a hands-on technical leader to build and lead a small but mighty team of applied data scientists and ML engineers to develop forecasting capabilities and platforms from the ground up.</p>\n<p>Your team will be responsible for building and scaling robust, interpretable, and production-ready forecasting systems. 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