Political Science QA Lead - Remote

About This Role

Your Profile

• Bachelor’s, Master’s, or PhD degree in Political Science, International Relations, Public Policy, Government, Political Theory, Security Studies, Law, Sociology, Economics, or a closely related 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 political science research, teaching, policy analysis, public affairs, international relations, political writing, academic review, or related analytical workflows.
• Strong understanding of political institutions, comparative politics, international relations, public policy, political theory, electoral systems, governance, state capacity, civil society, and political behavior.
• Ability to evaluate political science content against detailed rubrics and identify issues such as oversimplification, ideological bias, unsupported claims, incorrect institutional descriptions, misleading causal reasoning, or weak comparative analysis.
• Familiarity with areas such as democracy and authoritarianism, political economy, public administration, constitutional systems, electoral politics, conflict studies, international organizations, policy evaluation, or survey research is preferred.
• Experience leading or supporting remote teams of analysts, researchers, reviewers, educators, annotators, or QAs is strongly preferred.
• Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation.
• Experience with AI training, data annotation, LLM evaluation, policy QA, academic review, fact-checking, or rubric-based review is a strong plus.

Key Responsibilities

• Quality monitoring: Spot-check political science items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
• Political science review: Evaluate AI-generated political science explanations, comparative analyses, policy summaries, political theory discussions, institutional descriptions, and reasoning for accuracy and balance.
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and political-science-specific review standards.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around institutions, comparative politics, public policy, political theory, international relations, bias, 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 political science 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 political-science-specific review requirements.
• Quality alignment: Ensure all trainers and QAs apply political science review guidelines consistently and understand updates as projects evolve.
• Bias and risk review: Flag misleading, ideologically one-sided, unsupported, outdated, politically inflammatory, or poorly contextualized claims.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for political science AI training projects.