Econometrics Instructor

Alignerr Corp.; Dublin; Remote; EUR 55,000 - 110,000; Part time

Benefits offered by this job

Autonomy

Variety of projects

Collaboration with global experts

Job summary

Alignerr is seeking experienced econometrics instructors to shape the next generation of AI. You will review econometric questions and explanations used to train AI systems, ensuring accuracy and clear communication of results.

This fully remote, hourly contract role values teaching expertise and the ability to work independently on a flexible schedule, collaborating with a global expert community in AI evaluation and model training workflows.

Qualifications

• 3+ years of teaching econometrics or quantitative economics at college/grad level.
• Strong command of regression analysis and causal inference.
• Ability to articulate quantitative reasoning clearly for diverse audiences.
• Experience reviewing structured technical content with precision.

Responsibilities

• Review and validate econometric questions, models, and explanations used to train AI systems.
• Assess statistical accuracy, underlying assumptions, and interpretation of results.
• Identify errors, edge cases, and gaps in AI-generated econometric reasoning.
• Provide clear, structured feedback to improve model outputs and explanations.
• Apply teaching experience to evaluate how complex concepts are communicated.
• Work independently and asynchronously on flexible scheduling.

Skills

Regression analysis

Causal inference

Applied statistics

Clear communication

Independent work

Education

Master's or PhD in Economics / Econometrics

Tools

R

Stata

Python

Job description

About The Role

We're looking for experienced econometrics instructors and quantitative economists to help shape the next generation of AI. Your expertise will directly influence how AI systems understand, reason through, and explain econometric concepts — from regression analysis to causal inference.

Econometrics Instructor (AI Training)

We're looking for experienced econometrics instructors and quantitative economists to help shape the next generation of AI. Your expertise will directly influence how AI systems understand, reason through, and explain econometric concepts — from regression analysis to causal inference.

This is a fully remote, flexible contract role where your academic and teaching experience translates into real impact on cutting-edge AI development.

• Organization: Alignerr (Powered by Labelbox)
• Type: Hourly / Task-based Contract
• Location: Remote
• Commitment: 10–40 hours/week

What You'll Do

• Review and validate econometric questions, models, and explanations used to train AI systems
• Assess statistical accuracy, underlying assumptions, and the interpretation of quantitative results
• Identify errors, edge cases, and gaps in AI-generated econometric reasoning
• Provide clear, structured feedback to improve model outputs and explanations
• Apply your real-world teaching experience to evaluate how well complex concepts are communicated
• Work independently and asynchronously on your own schedule

Who You Are

• 3+ years of experience teaching econometrics or quantitative economics at a college or graduate level
• Strong command of regression analysis, causal inference, and applied statistical methods
• Able to evaluate and clearly articulate quantitative reasoning for diverse audiences
• Comfortable reviewing structured technical content with precision and consistency
• Self-motivated and reliable when working independently on task-based assignments

Nice to Have

• Master's or PhD in Economics, Econometrics, Statistics, or a related field
• Proficiency with statistical tools such as R, Stata, or Python
• Prior experience with AI evaluation, data annotation, or model training workflows

Why Join Us

• Work on cutting-edge AI projects with top research labs — your expertise directly improves how AI handles complex quantitative reasoning
• Fully remote and flexible — work on your own schedule, from anywhere
• Freelance perks: autonomy, variety, and collaboration with a global expert community
• Meaningful work that bridges academic knowledge and the future of AI
• Potential for ongoing work and contract extension