Anthropic

<div><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h3><strong>About the role</strong></h3>
<p>At Anthropic, we're building AI systems that are safe, beneficial, and transformative. Our mission is to develop AI that benefits humanity, and we believe the most powerful capabilities emerge when we thoughtfully bridge the gap between research breakthroughs and real-world applications.</p>
<p>Frontier AI runs on datacenters, and the world is in the middle of the largest infrastructure buildout in a generation. The binding constraint on progress is increasingly everything around the chips: land, power, permits, equipment, and the design and construction of the buildings themselves. Bringing a single site online involves hundreds of people, thousands of components, and decisions that move enormous amounts of capital. Much of that work still runs on spreadsheets and handoffs.</p>
<p>At Anthropic, we're building software and Claude-powered tools to help Anthropic scale out its compute, and we think there's an enormous opportunity to rethink how that work gets done. It's early, it's already having a real impact, and the engineers who join now will shape how one of the most consequential buildouts in the world gets done.</p>
<p>We're looking for strong, versatile software engineers who love building for people doing real work in the physical world. You'll embed with the teams that source sites, design buildings, procure equipment, and manage construction, learn their work deeply, and build the tools and systems they rely on every day. Datacenter experience is a big plus, but what matters most is that you can earn the trust of expert operators, model a messy domain cleanly, and move fast.</p>
<h3><strong>Responsibilities</strong></h3>
<ul>
<li>Build the core systems that track a datacenter's lifecycle (sites, designs, bills of materials, equipment, and construction progress) in one trusted, permissioned source of truth</li>
<li>Embed with datacenter, energy, and supply chain teams to understand how the work actually gets done, find the critical path, and build the tools they reach for first</li>
<li>Bring order to messy data by migrating and reconciling spreadsheets and legacy trackers, and integrate with the industry's tools, like construction management, scheduling, and engineering systems</li>
<li>Design for trust: fine-grained permissions, auditability, and data quality for information that steers major investment decisions</li>
<li>Ship early, iterate with users, and cut anything that doesn't help bring compute online sooner</li>
<li>Partner with research to understand new model capabilities and share where they fall short in engineering-heavy, physical-world domains</li>
</ul>
<h3><strong>You may be a good fit if you</strong></h3>
<ul>
<li>Have 8+ years of experience building software, with strong full-stack skills and solid grounding in data modeling, APIs, and databases</li>
<li>Have built software that teams in a physical-world industry depend on, such as datacenters, construction, energy, manufacturing, supply chain, or logistics</li>
<li>Have a track record of zero-to-one work in startup or startup-like environments</li>
<li>Are deeply user-centric: you learn the domain from the people doing the work and validate with them before over-investing</li>
<li>Bring high agency and good judgment about what matters, and hold strong opinions loosely</li>
<li>Communicate clearly across engineering, operations, and research, and care about the societal impacts of your work</li>
</ul>
<h3><strong>Strong candidates may also have</strong></h3>
<ul>
<li>Experience in datacenters (at a hyperscaler, colocation provider, operator, utility, or engineering firm), or in adjacent fields like construction, logistics, or legal</li>
<li>Experience with the domain's tooling, such as construction management (Procore, Autodesk Construction Cloud), scheduling (Primavera P6), PLM/BOM, ERP and procurement, CAD/BIM, DCIM, or power system studies</li>
<li>A background in electrical, mechanical, or civil engineering, energy systems, or supply chain alongside a software career</li>
<li>Experience building products with large language models</li>
</ul>
<h3><strong>Candidates need not have</strong></h3>
<ul>
<li>
<p>100% of the skills listed above</p>
</li>
<li>
<p>Formal certifications or education credentials</p>
</li>
<li>
<p>Direct machine learning or AI research experience</p>
</li>
</ul>
<p><strong>Deadline to apply:</strong> None. Applications will be reviewed on a rolling basis.</p><div><div><div><p>The annual compensation range for this role is listed below. </p>
<p>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.</p></div><div>Annual Salary:</div><div><span>$405,000</span><span>—</span><span>$485,000 USD</span></div></div></div><div><h2><strong>Logistics</strong></h2>
<p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>
<p><strong>Required field of study: </strong>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><strong>Location-based hybrid policy:</strong> 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.</p>
<p><strong>Visa sponsorship:</strong> 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.</p>
<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br /><br /><strong>Your safety matters to us.</strong> 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 <u><a href="http://anthropic.com/careers" target="_blank" rel="noopener noreferrer ugc">anthropic.com/careers</a></u> directly for confirmed position openings.</p>
<h2><strong>How we're different</strong></h2>
<p>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.</p>
<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2><strong>Come work with us!</strong></h2>
<p>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. <strong>Guidance on Candidates' AI Usage:</strong> Learn about <a href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" rel="noopener noreferrer ugc">our policy</a> for using AI in our application process.</p></div>

Staff Software Engineer: Compute

<div><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h2><strong>About the Role</strong></h2>
<p>As a Data Engineer on the Data Science &amp; Analytics team, you will build the data foundation for Anthropic’s quote-to-cash lifecycle: the path a deal takes from opportunity through revenue. You will design the canonical data models so that Sales, Deal Desk, Order Management, Revenue Operations and Finance work from one governed, auditable definition of what was sold, on what terms, and where each deal stands. You will partner closely with DS&amp;A and with GTM and Finance systems teams who own Salesforce, CPQ and billing to make quote-to-cash data reliable, well-modeled and self-serve as our business scales.</p>
<h2><strong>Responsibilities</strong></h2>
<ul>
<li>Understand the data needs of Deal Desk, Order Management, Revenue Operations, Finance and Sales systems teams, and translate them into technical requirements</li>
<li>Design, build and own data models that transform raw Salesforce, CPQ, and billing data into canonical datasets</li>
<li>Establish high data integrity standards and SLAs to ensure timely, accurate delivery of data</li>
<li>Partner with Salesforce, CPQ and billing engineers on upstream schema changes, new fields and ingestion so the warehouse faithfully mirrors the systems of record</li>
<li>Build foundational data products, dashboards and tools to enable self-serve analytics to scale across GTM teams</li>
<li>Influence stakeholder roadmaps from a data perspective, and become the expert on Anthropic’s GTM data models and architecture</li>
</ul>
<h2><strong>You might be a good fit if you have</strong></h2>
<ul>
<li>5+ years of experience as a Data Engineer, Analytics Engineer or in a similar Data Science &amp; Analytics role, ideally partnering with GTM, Revenue Operations or Finance teams.</li>
<li>A passion for the company's mission of building helpful, honest, and harmless AI.</li>
<li>Hands-on experience modeling Salesforce data and at least one adjacent quote-to-cash system: CPQ, contract lifecycle management, billing and invoicing, or ERP.</li>
<li>Expertise in building multi-step ETL jobs, building robust data models through tooling like dbt; proficiency with workflow management platforms like Airflow and version control management tools through GitHub.</li>
<li>Expertise in SQL and Python to transform data into accurate, clean data models.</li>
<li>Experience building data reporting and dashboarding in visualization tools like Hex to serve multiple cross-functional teams.</li>
<li>A bias for action and urgency, not letting perfect be the enemy of the effective.</li>
<li>A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end, even if it requires going outside the original job description.</li>
<li>Experience building an Analytics Data Engineering (or similar) function at start-ups. </li>
<li>A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress.</li>
</ul><div><div><div><p>The annual compensation range for this role is listed below. </p>
<p>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.</p></div><div>Annual Salary:</div><div><span>$320,000</span><span>—</span><span>$405,000 USD</span></div></div></div><div><h2><strong>Logistics</strong></h2>
<p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>
<p><strong>Required field of study: </strong>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><strong>Location-based hybrid policy:</strong> 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.</p>
<p><strong>Visa sponsorship:</strong> 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.</p>
<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br /><br /><strong>Your safety matters to us.</strong> 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 <u><a href="http://anthropic.com/careers" target="_blank" rel="noopener noreferrer ugc">anthropic.com/careers</a></u> directly for confirmed position openings.</p>
<h2><strong>How we're different</strong></h2>
<p>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.</p>
<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2><strong>Come work with us!</strong></h2>
<p>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. <strong>Guidance on Candidates' AI Usage:</strong> Learn about <a href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" rel="noopener noreferrer ugc">our policy</a> for using AI in our application process.</p></div>

Data Engineer, GTM

<div><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h2><strong>About the role</strong></h2>
<p>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.</p>
<p>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 (<a href="https://www.anthropic.com/research/clio" rel="noopener noreferrer ugc" target="_blank">Clio</a>), we <a href="https://assets.anthropic.com/m/2e23255f1e84ca97/original/Economic_Tasks_AI_Paper.pdf" rel="noopener noreferrer ugc" target="_blank">analyze millions of real-world AI interactions</a> to understand how AI augments and automates work across different occupations and tasks.</p>
<h2><strong>Key responsibilities</strong></h2>
<ul>
<li>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</li>
<li>Advance research collaborations that answer country- or regional-specific economic impact questions</li>
<li>Translate research insights into actionable recommendations for policy discussions</li>
<li>Make fundamental contributions to the development and expansion of the <a href="https://www.anthropic.com/economic-index" rel="noopener noreferrer ugc" target="_blank">Anthropic Economic Index</a>, including country/regional-specific analysis</li>
<li>Design and collaborate on empirical research on AI's economic effects with governments, academia, industry, and civil society in your region</li>
<li>Develop new methodological approaches, in collaboration with partners in your region, for studying AI's impact on:</li>
<ul>
<li>Labor markets and the future of work</li>
<li>Productivity and task transformation</li>
<li>Economic inequality and displacement</li>
<li>Industry-specific disruption and adaptation</li>
<li>Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios</li>
</ul>
<li>Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection</li>
<li>Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders</li>
</ul>
<h2><strong>Minimum qualifications</strong></h2>
<ul>
<li>PhD in Economics</li>
<li>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</li>
<li>Demonstrated experience working in and relevant relationships across the region</li>
<li>Experience relevant to the study of AI’s impact on the economy, including:</li>
<ul>
<li>Labor market analysis and occupational change</li>
<li>Task-based approaches to technological transformation</li>
<li>Large-scale data analysis and econometric methods</li>
<li>Large language models for social science research</li>
<li>Policy-relevant economic research</li>
<li>Experimental and quasi-experimental methods for causal inference</li>
<li>Macroeconomic modeling and time series forecasting</li>
<li>Agent-based modeling or large-scale simulation</li>
</ul>
<li>Technical skills including:</li>
<ul>
<li>Proficiency in Python, R, SQL, or similar tools for large-scale data analysis</li>
<li>Experience working with novel datasets and measurement systems</li>
<li>Comfort learning new technical tools and frameworks</li>
</ul>
<li>Demonstrated ability to:</li>
<ul>
<li>Lead complex research projects from conception to publication</li>
<li>Communicate technical findings to diverse audiences</li>
<li>Build relationships across academic, policy, and industry communities</li>
</ul>
<li>Strong interest in ensuring AI development benefits humanity</li>
<li>Comfort working with AI systems and ability to think critically about their capabilities and limitations</li>
</ul>
<h2><strong>Representative projects</strong></h2>
<ul>
<li><a href="https://www.anthropic.com/research/how-australia-uses-claude" rel="noopener noreferrer ugc" target="_blank">How Australia Uses Claude: Findings from the Anthropic Economic Index</a></li>
<li><a href="https://www.anthropic.com/research/anthropic-economic-index-january-2026-report" rel="noopener noreferrer ugc" target="_blank">Anthropic Economic Index Report: Economic Primitives</a></li>
<li><a href="https://www.anthropic.com/research/anthropic-economic-index-september-2025-report" rel="noopener noreferrer ugc" target="_blank">Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption</a></li>
<li><a href="https://www.anthropic.com/research/estimating-productivity-gains" rel="noopener noreferrer ugc" target="_blank">Estimating AI productivity gains from Claude conversations</a></li>
<li><a href="https://www.anthropic.com/economic-index" rel="noopener noreferrer ugc" target="_blank">The Anthropic Economic Index</a></li>
</ul>
<h2><strong>Additional information</strong></h2>
<p>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.</p><div><h2><strong>Logistics</strong></h2>
<p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>
<p><strong>Required field of study: </strong>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><strong>Location-based hybrid policy:</strong> 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.</p>
<p><strong>Visa sponsorship:</strong> 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.</p>
<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br /><br /><strong>Your safety matters to us.</strong> 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 <u><a href="http://anthropic.com/careers" target="_blank" rel="noopener noreferrer ugc">anthropic.com/careers</a></u> directly for confirmed position openings.</p>
<h2><strong>How we're different</strong></h2>
<p>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.</p>
<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2><strong>Come work with us!</strong></h2>
<p>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. <strong>Guidance on Candidates' AI Usage:</strong> Learn about <a href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" rel="noopener noreferrer ugc">our policy</a> for using AI in our application process.</p></div>

Regional Research Economist, Economic Research

<div><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h2><strong>About the Role</strong></h2>
<p>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.</p>
<p>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 (<a href="https://www.anthropic.com/research/clio" rel="noopener noreferrer ugc" target="_blank">Clio</a>), we <a href="https://assets.anthropic.com/m/2e23255f1e84ca97/original/Economic_Tasks_AI_Paper.pdf" rel="noopener noreferrer ugc" target="_blank">analyze millions of real-world AI interactions</a> to understand how AI augments and automates work across different occupations and tasks.</p>
<h2><strong>Key responsibilities</strong></h2>
<ul>
<li>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</li>
<li>Advance research collaborations that answer country- or regional-specific economic impact questions</li>
<li>Translate research insights into actionable recommendations for policy discussions</li>
<li>Make fundamental contributions to the development and expansion of the <a href="https://www.anthropic.com/economic-index" rel="noopener noreferrer ugc" target="_blank">Anthropic Economic Index</a>, including country/regional-specific analysis</li>
<li>Design and collaborate on empirical research on AI's economic effects with governments, academia, industry, and civil society in your region</li>
<li>Develop new methodological approaches, in collaboration with partners in your region, for studying AI's impact on:</li>
<ul>
<li>Labor markets and the future of work</li>
<li>Productivity and task transformation</li>
<li>Economic inequality and displacement</li>
<li>Industry-specific disruption and adaptation</li>
<li>Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios</li>
</ul>
<li>Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection</li>
<li>Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders</li>
</ul>
<h2><strong>Minimum qualifications</strong></h2>
<ul>
<li>PhD in Economics</li>
<li>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</li>
<li>Demonstrated experience working in and relevant relationships across the region</li>
<li>Experience relevant to the study of AI’s impact on the economy, including:</li>
<ul>
<li>Labor market analysis and occupational change</li>
<li>Task-based approaches to technological transformation</li>
<li>Large-scale data analysis and econometric methods</li>
<li>Large language models for social science research</li>
<li>Policy-relevant economic research</li>
<li>Experimental and quasi-experimental methods for causal inference</li>
<li>Macroeconomic modeling and time series forecasting</li>
<li>Agent-based modeling or large-scale simulation</li>
</ul>
<li>Technical skills including:</li>
<ul>
<li>Proficiency in Python, R, SQL, or similar tools for large-scale data analysis</li>
<li>Experience working with novel datasets and measurement systems</li>
<li>Comfort learning new technical tools and frameworks</li>
</ul>
<li>Demonstrated ability to:</li>
<ul>
<li>Lead complex research projects from conception to publication</li>
<li>Communicate technical findings to diverse audiences</li>
<li>Build relationships across academic, policy, and industry communities</li>
</ul>
<li>Strong interest in ensuring AI development benefits humanity</li>
<li>Comfort working with AI systems and ability to think critically about their capabilities and limitations</li>
</ul>
<h2><strong>Representative projects</strong></h2>
<ul>
<li><a href="https://www.anthropic.com/research/how-australia-uses-claude" rel="noopener noreferrer ugc" target="_blank">How Australia Uses Claude: Findings from the Anthropic Economic Index</a></li>
<li><a href="https://www.anthropic.com/research/anthropic-economic-index-january-2026-report" rel="noopener noreferrer ugc" target="_blank">Anthropic Economic Index Report: Economic Primitives</a></li>
<li><a href="https://www.anthropic.com/research/anthropic-economic-index-september-2025-report" rel="noopener noreferrer ugc" target="_blank">Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption</a></li>
<li><a href="https://www.anthropic.com/research/estimating-productivity-gains" rel="noopener noreferrer ugc" target="_blank">Estimating AI productivity gains from Claude conversations</a></li>
<li><a href="https://www.anthropic.com/economic-index" rel="noopener noreferrer ugc" target="_blank">The Anthropic Economic Index</a></li>
</ul>
<h2><strong>Additional Information</strong></h2>
<p>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.</p><div><div><div><p>The annual compensation range for this role is listed below. </p>
<p>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.</p></div><div>Annual Salary:</div><div><span>£195,000</span><span>—</span><span>£245,000 GBP</span></div></div></div><div><h2><strong>Logistics</strong></h2>
<p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>
<p><strong>Required field of study: </strong>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><strong>Location-based hybrid policy:</strong> 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.</p>
<p><strong>Visa sponsorship:</strong> 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.</p>
<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br /><br /><strong>Your safety matters to us.</strong> 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 <u><a href="http://anthropic.com/careers" target="_blank" rel="noopener noreferrer ugc">anthropic.com/careers</a></u> directly for confirmed position openings.</p>
<h2><strong>How we're different</strong></h2>
<p>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.</p>
<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2><strong>Come work with us!</strong></h2>
<p>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. <strong>Guidance on Candidates' AI Usage:</strong> Learn about <a href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" rel="noopener noreferrer ugc">our policy</a> for using AI in our application process.</p></div>

<div><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h2><strong>About the role</strong></h2>
<p>As part of our growing Data Science and Analytics team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by driving data-informed decision making across our organization. You’ve worked in cultures of excellence in the past, and are eager to apply that experience to help shape the cultural norms and best practices of a growing data science team as Anthropic continues to scale. In this unique company, technology, and moment in history, your work will be critical to informing our strategy as we deploy safe, frontier AI at scale to the world.</p>
<p><strong>Responsibilities:</strong></p>
<ul>
<li>Deep dive into product and user data to derive actionable insights and size opportunities to improve products, strategy and operations, influencing roadmaps through your insights and recommendations</li>
<li>Develop hypotheses, apply rigorous causal inference methods – controlled experiments, synthetic controls –  and analyze the results in order make actionable recommendations </li>
<li>Investigate anomalies, conduct root cause analyses, and provide data-driven insights to guide priorities and inform decisions</li>
<li>Define core metrics, build measurement frameworks, and maintain core reporting to evaluate success</li>
<li>Build statistical models, optimization frameworks, and simulations to automate decision-making and operational processes</li>
<li>Present complex technical analyses and recommendations to both technical and non-technical stakeholders</li>
<li>Establish foundational data practices and help scale our analytics infrastructure to support rapid iteration and decision-making as our products grow</li>
</ul>
<p><strong>You may be a good fit if you have:</strong></p>
<ul>
<li>7+ years of experience in data science or analytics roles </li>
<li>Deep expertise with Python, SQL, and data visualization tools</li>
<li>Expertise with experimental design, causal inference, statistical modeling, and A/B testing frameworks, particularly in high-scale technical environments</li>
<li>Highly effective written communication and presentation skills</li>
<li>A track record of translating complex data into clear, actionable insights for both technical and business stakeholders</li>
<li>A bias for action and ability to thrive in ambiguous, fast-moving environments where you must create clarity and drive forward progress</li>
<li>A passion for the company’s mission of building helpful, honest, and harmless AI</li>
<li>Some experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem</li>
</ul><div><div><div><p>The annual compensation range for this role is listed below. </p>
<p>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.</p></div><div>Annual Salary:</div><div><span>$285,000</span><span>—</span><span>$380,000 USD</span></div></div></div><div><h2><strong>Logistics</strong></h2>
<p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>
<p><strong>Required field of study: </strong>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><strong>Location-based hybrid policy:</strong> 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.</p>
<p><strong>Visa sponsorship:</strong> 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.</p>
<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br /><br /><strong>Your safety matters to us.</strong> 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 <u><a href="http://anthropic.com/careers" target="_blank" rel="noopener noreferrer ugc">anthropic.com/careers</a></u> directly for confirmed position openings.</p>
<h2><strong>How we're different</strong></h2>
<p>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.</p>
<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2><strong>Come work with us!</strong></h2>
<p>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. <strong>Guidance on Candidates' AI Usage:</strong> Learn about <a href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" rel="noopener noreferrer ugc">our policy</a> for using AI in our application process.</p></div>

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