Author empirical economics problems from your own causal, panel or forecasting work, with reference answers that show each step. Suits applied economists and quantitative social scientists with several years of research or analytics experience.
Sobre la vacante
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
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