Remote Qa Consultant Jobs (NOW HIRING)

Job Summary:
YO IT Consulting is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. They are seeking an Economics Quality Assurance Lead to oversee quality and consistency across economics-focused AI training projects, ensuring that all contributors meet quality standards and that economics training data is accurate and analytically sound.
Responsibilities:
• Quality monitoring: Spot-check economics items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
• Economics review: Evaluate AI-generated economics explanations, calculations, graphs, policy analyses, data interpretations, and step-by-step reasoning for accuracy and clarity.
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and economics-specific review standards.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around economic models, assumptions, formulas, graphs, causal claims, data interpretation, and rubric interpretation.
• Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
• Documentation: Create and maintain economics project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and economics-specific review requirements.
• Quality alignment: Ensure all trainers and QAs apply economics-review guidelines consistently and understand updates as projects evolve.
• Risk review: Flag overconfident, misleading, politically biased, statistically weak, or assumption-free economic claims.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for economics AI training projects.
Qualifications:
Required:
• Bachelor’s, Master’s, or PhD degree in Economics, Applied Economics, Econometrics, Public Policy, Finance, Statistics, Mathematics, or a closely related quantitative/social science field.
• Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback.
• 3+ years of experience in economics research, teaching, policy analysis, economic consulting, data analysis, econometrics, content review, or related analytical workflows.
• Strong understanding of microeconomics, macroeconomics, market structures, incentives, supply and demand, elasticity, externalities, monetary/fiscal policy, inflation, unemployment, trade, growth, and basic econometric reasoning.
• Ability to evaluate economics content against detailed rubrics and identify issues such as incorrect assumptions, flawed causal reasoning, wrong formulas, misleading graphs, unsupported policy claims, poor data interpretation, or oversimplified conclusions.
• Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation.
Preferred:
• Familiarity with tools or methods such as regression analysis, causal inference, economic modeling, Excel, R, Python, Stata, public datasets, policy briefs, and academic economics writing.
• Experience leading or supporting remote teams of analysts, researchers, reviewers, educators, annotators, or QAs.
• Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Experience with AI training, data annotation, LLM evaluation, economic QA, academic review, or rubric-based review.
Company:
Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) — including machine learning (ML), data analytics, automation, natural language processing (NLP), computer vision, and related technologies — to solve real-world problems, improve decision-making, automate repetitive tasks, and deliver intelligent solutions across industries. Founded in 2018, the company is headquartered in Abu Dhabi, Abu Dhabi Emirate, AE, , with a team of 51-200 employees. The company is currently Growth Stage.