Remote Econometrics Instructor for AI Training

Alignerr; Johannesburg; On-site; ZAR 892,000 - 2,006,000; Part time

Benefits offered by this job

Autonomy

Global collaboration

Freelance perks

Job summary

Alignerr is seeking experienced econometrics instructors and quantitative economists to help evaluate and improve AI training data and explanations. This fully remote, hourly contract role offers 10–40 hours per week with flexible scheduling and the chance to influence AI reasoning in economics.

You will review econometric questions, assess statistical assumptions, and provide structured feedback to improve model outputs, drawing on your teaching experience in a remote, asynchronous setting.

Qualifications

• 3+ years of experience teaching econometrics, quantitative economics, or closely related field.
• Strong command of regression analysis, causal inference, time series, and statistical methodology.
• Able to clearly evaluate and articulate quantitative reasoning — both what's correct and what's not.

Responsibilities

• Review and validate econometric questions, models, and explanations used in AI training datasets
• Assess statistical accuracy, underlying assumptions, and interpretation of quantitative results
• Identify errors, logical gaps, and edge cases in AI-generated economic reasoning
• Provide clear, structured feedback to improve model outputs and explanations
• Apply your real-world teaching experience to evaluate whether content is both technically correct and pedagogically sound
• Work independently and asynchronously to complete task-based assignments on your own schedule

Skills

Econometrics teaching

Regression analysis

Time series

Causal inference

Statistical methodology

Education

Master's or PhD in Economics/Statistics

Tools

R

Stata

Python

Job description

Alignerr is seeking experienced econometrics instructors and quantitative economists to help evaluate and improve AI training data and explanations. This fully remote, hourly contract role offers 10–40 hours per week with flexible scheduling and the chance to influence AI reasoning in economics.

You will review econometric questions, assess statistical assumptions, and provide structured feedback to improve model outputs, drawing on your teaching experience in a remote, asynchronous setting.