# Research Engineer, Economic Research

**Company:** [Anthropic](https://hotfix.jobs/companies/anthropic)
**Location:** San Francisco, CA
**Role:** Data Engineering
**Salary:** $300k – $405k/yr
**Skills:** Python, AWS, GCP, Data Pipelines, Privacy-Preserving Tools, LLMs, Cloud Infrastructure, Machine Learning, Econometrics, Statistics
**Posted:** 2026-03-11

> Builds and maintains data pipelines and privacy-preserving infrastructure for AI economic impact research. Collaborates with researchers and economists using Python, cloud platforms, and LLMs to support scalable economic analysis.

## Job Description

## 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.

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