$150–250/hr
The role in one line
Conduct sophisticated economic research for an AI lab, leveraging your doctoral training and institutional research experience.
Written by Training Turk from the public listing; it may be incomplete or out of date. Read the full posting on Mercor.
What you would do
- Analyze economic datasets using advanced statistical techniques and econometric tools
- Build models to test theoretical hypotheses and validate assumptions
- Review scholarly literature and synthesize findings across multiple sources
- Prepare research documentation and academic papers for technical audiences
- Partner with computer scientists on questions combining economics and AI
Who they are looking for
- Master's or PhD in Economics from accredited program
- Minimum one year research experience at World Bank, IMF, Federal Reserve, or similar institution
- Strong background in applied econometrics and quantitative analysis
- Able to commit 10+ hours weekly for at least four weeks
- Comfortable presenting technical findings to interdisciplinary audiences
Skills this role asks for
What the interview is likely to probe
1.Econometric modeling design
The interviewer checks whether you can structure appropriate analyses for economic questions, select valid estimators, and validate your modeling assumptions.
Expect something like: “You discovered endogeneity issues while replicating a published findings. Describe how you identified the problem and what alternative approaches you considered to address it.”
2.Managing interdisciplinary collaboration
This role requires translating economic concepts for AI researchers and understanding their methodological constraints and research objectives.
Expect something like: “Your AI lab collaborators asked you to quantify economic impact of a machine learning model. How would you scope the measurement task and prioritize data sources?”
3.Data quality assessment
High-stakes research depends on critically evaluating data limitations, missing values, and measurement reliability before proceeding with analysis.
Expect something like: “A new dataset on international trade flows showed suspicious patterns in three countries' reporting. How would you decide whether to exclude these observations or adjust your methodology?”
4.Translating theory into empirical work
Effective researchers connect abstract economic theories to testable hypotheses and measurable outcomes that support AI evaluation.
Expect something like: “Your lab wants to test whether AI adoption follows technology diffusion models from economic literature. How would you operationalize key variables and design an empirical test?”
5.Research documentation and rigor
AI development teams depend on reproducible research with clear methodology, stated assumptions, and documented limitations described thoroughly.
Expect something like: “You completed an analysis of labor market responses to technology shocks. What would you include in the methods section to ensure another economist could reproduce your work?”
Exercise you may get
Analyze a dataset related to technology adoption or AI impact, develop a hypothesis test, and outline the econometric approach you'd use to evaluate it.
How to prepare
- Review recent economic research on AI and automation
- Prepare examples of your past econometric analyses and the datasets you've used
- Refresh your understanding of instrumental variables and panel data methods
- Document a past research project where your analysis influenced policy or strategy decisions
Facts
- Pay
- $150–250/hr
- Commitment
- hourly
- Hours
- 40 per week
- Work arrangement
- remote · Remote
- Domain
- Life, Physical, and Social Science
- Posted
- 9/28/2026
- Open slots
- 13