# Research Economist, Economic Research

**Company:** [Anthropic](https://hotfix.jobs/companies/anthropic)
**Location:** San Francisco, CA
**Role:** Data Science
**Salary:** $320k – $405k/yr
**Skills:** Python, R, SQL, Econometrics, Machine Learning, Causal Inference, Structural Estimation, LLMs, Time Series Forecasting, Agent-Based Modeling
**Posted:** 2026-03-10

> Measures AI's economic impacts through the Anthropic Economic Index using econometrics, ML, and novel data. Conducts empirical research on labor markets, productivity, inequality; requires PhD in Economics and strong empirical track record.

## Job Description

## Responsibilities
- Make fundamental contributions to the development and expansion of the Anthropic Economic Index, including quarterly reports and industry-specific deep dives
- Design and conduct empirical research on AI's economic effects, drawing on external data sources and privacy-preserving measurement systems
- Develop new methodological approaches for studying AI's impact on:
  - Labor markets and the future of work
  - Productivity and task transformation
  - Economic inequality and displacement
  - Industry-specific disruption and adaptation
  - Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios
- Develop causal-inference tooling (e.g., surrogate indexes, heterogeneous-effect pipelines) to evaluate downstream economic consequences of compute, product, and pricing decisions
- Build and maintain relationships with academic institutions, policy think tanks, and other research partners
- Work cross-functionally with technical teams to improve measurement infrastructure and data collection
- Translate research insights into actionable recommendations for product decisions and policy discussions
- Amplify external engagement through research publications, policy briefs, and presentations

## You May Be a Good Fit If You Have
- PhD in Economics
- Strong track record of empirical research, particularly combining novel data sources and economic theory or frontier methods in causal inference and machine learning
- Experience relevant to AI's economic impact, including labor market analysis, task-based technological transformation, large-scale data analysis, econometric methods, large language models for social science, policy-relevant research, experimental/quasi-experimental methods, macroeconomic modeling, agent-based modeling
- Technical skills including:
  - Proficiency in Python, R, SQL or similar for large-scale data analysis
  - Experience with novel datasets and measurement systems
  - Comfort learning new technical tools and frameworks
- Demonstrated ability to lead complex research projects, communicate technical findings, build relationships across communities
- Strong interest in ensuring AI benefits humanity; comfort working with AI systems

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