Join OpenTrain as a remote Economics Expert to create benchmark-quality economics responses, review advanced solutions, and document rationales for AI training—PhD required; $80–90/hr, 20+ hours/week, contract part-time.
Generative AI & RLHF
100% Remote Hourly · $80–$90/hr
$80–$90/hr
Compensation
Worldwide
Eligibility
Entry
Experience
Jul 15, 2026
Posted
Open worldwide
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OpenTrain is the #1 platform for people building careers in AI training and data labeling. We help contributors discover projects, build a unified AI-training portfolio, and grow lasting freelance careers in the fast-moving field of AI.
OpenTrain hires and contracts experts directly for specialized annotation and training work. Creating an OpenTrain account is free and connects you with opportunities across AI training disciplines.
Why AI training matters
AI training is the human side of modern machine learning: experts prepare, review, and refine examples that teach models how to reason and respond. Contributors work remotely, often part-time and flexibly, and directly shape how next‑generation systems behave.
This role focuses on high-quality, real-world economics input—your subject-matter expertise will create benchmark answers and clear rationales that improve model accuracy and interpretability.
Role overview
OpenTrain is recruiting an Economics AI Training Expert to produce advanced, benchmark-grade economics responses, validate proposed solutions, and document clear explanations and justifications to support downstream annotation and model training.
This is a remote, contract, part-time role. Expected time commitment is 20+ hours per week. Compensation is hourly at $80–90 USD (PAY_PER_HOUR). Work is primarily English-language and open to contributors worldwide.
Data type: Text
Labeling work: Text generation and evaluation/rating (TEXT_GENERATION, EVALUATION_RATING)
Employment: Contractor, Part-time
Languages: English
What you'll do
You will create high-quality economics content and review materials that serve as golden benchmarks for model training, plus document the reasoning behind correct answers so annotators and engineers can interpret decisions.
Write comprehensive, precise responses to advanced economics prompts with clarity and depth.
Review and validate economics data, queries, and proposed solutions for accuracy and completeness.
Develop explanations and justifications across foundational and specialized economics topics.
Create benchmark (gold) responses to guide model training and evaluation.
Document context, assumptions, and methodological rationale to support interpretability and downstream annotation.
Requirements
You must meet the core academic and professional criteria and be able to translate complex economic reasoning into clear, teachable text suitable for model benchmarking and human review.
PhD in Economics or a closely related field (required).
Ability to write precise, comprehensive economics explanations and justifications.
Broad familiarity with microeconomics, macroeconomics, econometrics, behavioral economics, labor, or international economics.
Experience developing, reviewing, or publishing scientific, technical, or educational economics materials.
Strong written and verbal communication skills for complex technical ideas.
Strong attention to detail and methodological rigor.
Background in AI, data annotation, or digital content projects is helpful but not required.
How it works / Next steps
If you meet the requirements and want to shape how economics knowledge is represented in AI, apply through OpenTrain. Selected contributors work as contracted specialists, delivering text-generation and evaluation work under agreed hourly terms.
Expect task-focused assignments where you'll supply benchmark answers, reviews, and documented rationales. Pay is hourly at $80–90 USD; time commitment is typically 20+ hours/week and work is conducted in English.
Worldwide applicants accepted; work is fully remote.
This role is classified as contractor, part-time work with hourly pay.
Label types you will work on: TEXT_GENERATION and EVALUATION_RATING.
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