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Cette offre a expire le 19/07/2026. Elle n'accepte plus de candidatures.
Political Science QA Lead – Remote
YO IT Consulting
Description du poste
About the role
This contract position is a remote, hourly role focused on ensuring the quality and consistency of political science training data for AI models. You will lead quality assurance efforts across multiple AI training projects, providing precise feedback and maintaining high standards.
Key responsibilities
- Oversee quality, consistency, and trainer performance for political science AI training projects.
- Review AI‑generated political science content and trainer/QA work against detailed rubrics.
- Provide clear written feedback and ensure contributors follow established quality standards.
- Assess content for conceptual accuracy, institutional knowledge, comparative context, political theory, policy reasoning, source awareness, bias sensitivity, clarity, formatting, and instruction‑following.
- Identify recurring quality issues, communicate updates to trainers and QAs, and support onboarding of new contributors.
- Maintain documentation and help reactivate contributors who are not consistently active.
Required profile
- Bachelor’s, Master’s or PhD in Political Science, International Relations, Public Policy, Government, Political Theory, Security Studies, Law, Sociology, Economics, or a closely related field.
- Strong command of English for written feedback and communication.
- 3+ years of experience in political science research, teaching, policy analysis, public affairs, international relations, political writing, academic review, or similar analytical work.
- Deep understanding of political institutions, comparative politics, international relations, public policy, political theory, electoral systems, governance, and political behavior.
- Ability to evaluate content against detailed rubrics and spot issues such as oversimplification, bias, unsupported claims, or inaccurate institutional descriptions.
Required skills
What we offer
- Flexible remote work arrangement.
- Opportunity to influence the quality of data used by leading AI companies.
- Access to future AI training projects through the expert network.
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