Remote Econometrics Instructor — AI Evaluation & Training

Alignerr Corp.; United States; On-site; USD 55,000 - 96,000; Part time

Job summary

Alignerr Corp. is seeking experienced econometrics instructors and quantitative economists to help evaluate and improve AI systems trained on economic reasoning and statistical analysis.

You will review AI-generated econometric content and provide precise feedback to enhance accuracy and clarity for researchers, students, and policymakers worldwide. The role is remote, hourly, project-based, and flexible, with opportunities for ongoing collaboration.

Qualifications

• 3+ years of experience teaching econometrics or quantitative economics.
• Strong command of regression analysis, causal inference, and applied statistical methods.
• Able to clearly evaluate and articulate quantitative reasoning at a high level.
• Comfortable reviewing structured, technical content with precision and consistency.
• Self-motivated and reliable — you deliver quality work without being micromanaged.

Responsibilities

• Review and validate AI-generated econometric questions, models, and explanations for accuracy and clarity
• Assess statistical assumptions, methodological soundness, and interpretation of results
• Identify errors, edge cases, and reasoning gaps using your real-world teaching experience
• Provide structured, actionable feedback to improve AI model reasoning and communication
• Evaluate content spanning regression analysis, causal inference, time series, and more
• Work independently and asynchronously on your own schedule

Skills

Econometrics teaching

Regression analysis

Causal inference

Quantitative reasoning

Attention to detail

Education

Master's or PhD in Economics/Statistics

Tools

R

Stata

Python

Job description

Alignerr Corp. is seeking experienced econometrics instructors and quantitative economists to help evaluate and improve AI systems trained on economic reasoning and statistical analysis.

You will review AI-generated econometric content and provide precise feedback to enhance accuracy and clarity for researchers, students, and policymakers worldwide. The role is remote, hourly, project-based, and flexible, with opportunities for ongoing collaboration.