About the ProjectPareto.AI is a human data-collection platform connecting leading AI researchers with trusted industry experts to collaborate on AI alignment, safety, and training projects. We are partnering with a frontier AI lab to evaluate an AI model's ability to replicate empirical economics research findings.What You'll Do- Identify suitable causal economics papers with publicly available replication data- Write prompts asking the AI model to replicate findings given a research question, dataset, codebook, and context- Write rubrics to evaluate the AI model's performance across each step of the empirical pipeline:- Data cleaning- Variable construction- Specification choice- Robustness judgmentWho We're Looking For- PhD in Economics (required)- Hands-on experience with causal inference methods — DiD, IV, RDD, RCT, natural experiments- Familiarity with replication-friendly microdata — NLSY, ACS, CPS, administrative data- Proficient in STATA, R, or Python- Strong understanding of empirical research workflow from raw data to published results- Bonus: experience with AI/ML tools or interest in AI evaluationIdeal Background- Active or former academic economist at a research university- Published or working papers in applied microeconomics- Fields: labor, health, development, public, environmental economicsWhy Join- Contribute to cutting-edge AI safety and alignment research- Flexible part-time remote work — task-based engagement- Collaborate with a global network of economists and AI researchers- Competitive compensation per completed task- Compensation - $100/hr USDApply:To apply, submit your CV. We review every application personally — no automated screening. If your background is a strong fit, you'll receive a direct link to join the project and complete your application.