Political Science QA Lead - Remote
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Key skills for this role
About the Role
We are seeking a Political Science Quality Assurance Lead to oversee quality and trainer performance across AI training projects. The role involves reviewing AI-generated political science content, providing feedback, and maintaining documentation.
Key Skills for This Role
Responsibilities
- Spot check political science items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues
- Evaluate AI generated political science explanations, comparative analyses, policy summaries, political theory discussions, institutional descriptions, and reasoning for accuracy and balance
- Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and political science specific review standards
- Respond to trainer/QA questions clearly and promptly, especially around institutions, comparative politics, public policy, political theory, international relations, bias, and rubric interpretation
- DM contributors who are inactive or not working, encourage activation, track follow ups, and flag availability issues when needed
- Create and maintain political science project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials
- Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and political science specific review requirements
- Ensure all trainers and QAs apply political science review guidelines consistently and understand updates as projects evolve
- Flag misleading, ideologically one sided, unsupported, outdated, politically inflammatory, or poorly contextualized claims
- Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for political science AI training projects
Requirements
- 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
Full Job Posting
Job Description
- Job Title: Political Science Quality Assurance Lead
- Job Type: Contract
- Location: Remote
- In this hourly, remote contractor role, you will work as a Political Science Quality Assurance Lead to oversee quality, consistency, and trainer performance across political science AI training projects.
- You will review AI generated political science content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards.
- You will assess work for conceptual accuracy, institutional knowledge, comparative context, political theory accuracy, policy reasoning, source awareness, bias sensitivity, clarity, formatting, instruction following, and adherence to project specific rubrics.
- You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently.
- This role requires strong political science expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote expert teams.
- Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise.
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
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