Data Scientist, Policy

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 one of our first Data Scientists dedicated to policy work, you will play a key role in ensuring Anthropic's work is understood by policymakers around the world. You'll sit at the intersection of data science and public affairs, transforming internal product usage and survey data into clear, accurate, and consistent evidence the Policy team can use to inform its positions, demonstrate Anthropic’s relevance to policymakers, and measure the impact of its work. Your analyses will directly inform how legislators, regulators, and the public understand Anthropic's footprint and contribution. This is a highly cross-functional role that is foundational to Anthropic's mission of bringing powerful AI to the world in a way that benefits humanity. Key responsibilities · Partner with product and business teams across the company to produce supporting analyses and data collateral for specific policy position papers and partnership conversations · Determine which metrics faithfully represent our company to legislators, regulators, and the public · Own the dashboards and pipelines that keep externally-shared numbers consistent, so the Policy team can move quickly without creating discrepancies · Use AI tools to aggregate news, policy developments, and other public data sources to track trends and provide a clear picture of the evolving regulatory landscape · Develop measurement frameworks for policy communications, paid media, and public-affairs campaigns · Design and implement policy analyses to support internal position development or measure the impact of policy implementation for external audiences Minimum qualifications · Proficiency in Python, SQL, and data analysis tools, with experience working with external and public data sources · Experience producing analysis that reaches external audiences such as policy, communications, investor relations, public affairs, or published research · Applied causal inference using quasi-experimental designs (e.g., difference-in-differences, regression discontinuity, synthetic control, instrumental variables, or matching) to measure policy or program impact from observational data · Demonstrated ability to translate complex analyses into clear, actionable recommendations for audiences with differing levels of technical fluency Preferred qualifications · 6+ years of hands-on data science experience · Direct experience supporting a policy, government affairs, or regulatory team with data and analysis · Familiarity with investor-relations or financial-disclosure data standards and the consistency requirements they entail · Comfort operating in ambiguous, fast-moving environments where creating clarity and driving progress is part of the role · A genuine interest in Anthropic's mission of building safe and beneficial AI 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: $285,000—$380,000 USD 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 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.