Remote Econometrics Instructor for AI Training

Alignerr Corp.; Chicago (IL); A distancia; USD 55.000 - 90.000; A tiempo parcial

Descripción de la vacante

Alignerr (Powered by Labelbox) is seeking an experienced Econometrics Instructor to help shape AI training by evaluating econometric questions, models, and interpretations. You will review statistical methods used in AI training datasets, identify errors, and provide clear feedback to improve model outputs.

The role is fully remote with an hourly contract, allowing you to set your own schedule. Expect 10–40 hours per week, collaborating asynchronously with researchers and students worldwide.

Formación

• 3+ years of university-level econometrics or quantitative economics teaching.
• Strong regression, causal inference, and applied statistics skills.
• Ability to explain quantitative reasoning in writing.
• Detail-oriented review of structured technical content.

Responsabilidades

• Review econometric questions and models used in AI training datasets.
• Assess statistical accuracy and interpretation of quantitative results.
• Identify errors and edge cases in AI-generated economic reasoning.
• Provide structured feedback to improve model outputs for clarity and correctness.
• Apply teaching experience to evaluate how concepts are communicated.
• Work independently and asynchronously on task-based assignments.

Conocimientos

Teaching econometrics

Regression analysis

Causal inference

Applied statistics

Written communication

Educación

Master's or PhD in Economics/Statistics

Herramientas

R

Stata

Python

Descripción del empleo

Alignerr (Powered by Labelbox) is seeking an experienced Econometrics Instructor to help shape AI training by evaluating econometric questions, models, and interpretations. You will review statistical methods used in AI training datasets, identify errors, and provide clear feedback to improve model outputs.

The role is fully remote with an hourly contract, allowing you to set your own schedule. Expect 10–40 hours per week, collaborating asynchronously with researchers and students worldwide.