Remote Econometrics Instructor for AI Training & Evaluation

Alignerr Corp.; Sydney; Remote; AUD 79,000 - 118,000; Part time

Job summary

Alignerr Corp. is seeking experienced econometrics instructors to join our AI training program. You will review econometric questions, validate models, and provide clear feedback to improve AI reasoning and explanations.

This fully remote, hourly contract offers 10-40 hours per week, flexible scheduling, and the opportunity to influence how AI understands statistics, economic models, and causal inference in the social sciences.

Qualifications

• 3+ years of experience teaching econometrics or quantitative economics.
• Strong command of regression analysis, causal inference, and core statistical methods.
• Able to clearly evaluate and articulate quantitative reasoning at an expert level.
• Comfortable reviewing structured, technical content with precision and consistency.
• Self-motivated and reliable in an independent, remote work environment.

Responsibilities

• Review and validate econometric questions, models, and explanations used in AI training datasets.
• Assess statistical accuracy, methodological assumptions, and interpretation of results.
• Identify errors, edge cases, and reasoning gaps in AI-generated quantitative content.
• Provide clear, structured feedback to improve model reasoning and explanation quality.
• Apply your real-world teaching experience to ensure content is both accurate and pedagogically sound.
• Work independently and asynchronously to complete task-based assignments.

Skills

Econometrics

Quantitative economics

Regression analysis

Causal inference

Statistical methods

Education

Master's or PhD in Economics/Statistics

Tools

R

Stata

Python

Job description

Alignerr Corp. is seeking experienced econometrics instructors to join our AI training program. You will review econometric questions, validate models, and provide clear feedback to improve AI reasoning and explanations.

This fully remote, hourly contract offers 10-40 hours per week, flexible scheduling, and the opportunity to influence how AI understands statistics, economic models, and causal inference in the social sciences.