This is a remote, project-based role for applied economists, econometricians and quantitative social scientists with 3+ years of full time experience. You will author realistic empirical economics problems drawn from your work, covering causal questions, panel data, choice models, or forecasting, and work each one through to a reference answer that frontier AI labs use to test model judgment. Work is fully async with no fixed hours, a minimum of 10 hours per week and no maximum, and you can scale up or down week to week. This is an independent contractor role with ongoing project work, paid weekly via Stripe, with no screen recording, keystroke monitoring, or idle timers.
Responsibilities
Author realistic empirical economics problems drawn from your work: causal questions, panel data, choice models, or forecasting
Work each problem through to a reference answer, with the reasoning behind every step
Catch the identification and modeling mistakes that look reasonable but only a practitioner would spot




Required Qualifications
Master's or PhD in economics or a related quantitative social science
3+ years full time in an empirical research or analytics role (internships and school don't count)
Hands-on causal inference or econometric modeling experience
Comfortable with Stata, R or Python
Strong written English and able to explain an analysis clearly
Able to commit at least 10 hours per week
Preferred Qualifications
Experience running difference in differences, instrumental variables, regression discontinuity or synthetic control studies, or building time series forecasts
Why apply
Work stays in your specialty, judged on empirical judgment rather than volume
Set your own hours and scale up or down week to week
Weekly pay via Stripe
Your judgment shapes how the next generation of AI handles economic analysis
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📌 Econometrics Expert (Oña)
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