Research Engineer, Economic Research

Responsibilities:

• Build and maintain data pipelines that process large scale Claude usage logs into canonical, reusable datasets while maintaining user privacy.
• Expand privacy-preserving tools to enable new analytic functionality to support research needs.
• Design and implement novel data systems leveraging language models (e.g., CLIO) where traditional software engineering patterns don't yet exist.
• Develop and maintain data pipelines that are interoperable across data sources (including ingesting external data) and are designed to support economic analysis.
• Contribute to the strategic development of the economic research data foundations roadmap.
• Ensure data reliability, integrity, and privacy compliance across all economic research data infrastructure.
• Lead technical design discussions to ensure our infrastructure can support both current needs and future research directions.
• Create documentation and best practices that enable self-serve data access for researchers while maintaining security and governance standards.
• Partner closely with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic’s safety mission.

You might be a good fit if you have:

• Experience working with Research Scientists and Economists on ambiguous AI and economic projects.
• Experience with building and maintaining data infrastructure, large datasets, and internal tools in production environments.
• Experience with cloud infrastructure platforms such as AWS or GCP.
• Take pride in writing clean, well-documented code in Python that others can build upon.
• Are comfortable making technical decisions with incomplete information while maintaining high engineering standards.
• Are comfortable getting up-to-speed quickly on unfamiliar codebases, and can work well with other engineers with different backgrounds across the organization.
• Have a track record of using technical infrastructure to interface effectively with machine learning models.
• Have experience deriving insights from imperfect data streams.
• Have experience building systems and products on top of LLMs.
• Have experience incubating and maturing tooling platforms used by a wide variety of stakeholders.
• A passion for Anthropic's mission of building helpful, honest, and harmless AI and understanding its economic implications.
• 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.
• Strong communication skills to collaborate effectively with economists, researchers, and cross-functional partners who may have varying levels of technical expertise.

Strong candidates may have:

• Background in econometrics, statistics, or quantitative social science research.
• Experience building data infrastructure and data foundations for research.
• Familiarity with large language models, AI systems, or ML research workflows.
• Prior work on projects related to labor economics, technology adoption, or economic measurement.