Research Engineer, Economic Research

Anthropic Anthropic · AI Frontier · San Francisco, CA · Data Science & Analytics

Research Engineer on the Economic Research team responsible for designing, building, and maintaining critical infrastructure for AI's economic impact research. This involves processing large-scale Claude usage logs, expanding privacy-preserving tools, and developing novel data systems that leverage language models, ensuring data reliability, integrity, and privacy compliance.

What you'd actually do

  1. Build and maintain data pipelines that process large scale Claude usage logs into canonical, reusable datasets while maintaining user privacy.
  2. Expand privacy-preserving tools to enable new analytic functionality to support research needs.
  3. Design and implement novel data systems leveraging language models (e.g., [CLIO](https://www.anthropic.com/research/clio)) where traditional software engineering patterns don't yet exist.
  4. Develop and maintain data pipelines that are interoperable across data sources (including ingesting external data) and are designed to support economic analysis.
  5. Contribute to the strategic development of the economic research data foundations roadmap

Skills

Required

  • Python
  • AWS or GCP
  • building and maintaining data infrastructure
  • large datasets
  • internal tools in production environments
  • technical infrastructure to interface effectively with machine learning models
  • deriving insights from imperfect data streams
  • building systems and products on top of LLMs
  • incubating and maturing tooling platforms

Nice to have

  • econometrics
  • statistics
  • quantitative social science research
  • large language models
  • AI systems
  • ML research workflows
  • labor economics
  • technology adoption
  • economic measurement

What the JD emphasized

  • building data processing pipelines
  • architecting & implementing high-quality internal infrastructure
  • working in a fast-paced startup environment
  • navigating ambiguity
  • demonstrating an eagerness to develop their own research & technical skills
  • building and maintaining data infrastructure, large datasets, and internal tools in production environments
  • building systems and products on top of LLMs

Other signals

  • design and implement novel data systems leveraging language models
  • build scalable and robust data systems that support high-leverage, high-impact research
  • maintain critical infrastructure that powers Anthropic's research on AI's economic impact