Political Science QA Lead

Role overview

This remote contractor position is focused on quality leadership for political science AI training work. The role centers on checking the accuracy, consistency, and overall quality of political science content, while also reviewing trainer and QA output to ensure it follows project standards. You will give detailed written feedback, help keep teams aligned, and support the day-to-day quality workflow for distributed expert contributors.

The work is hourly and remote. It sits within a fast-scaling AI data services business that supports major AI companies and foundation model teams. Your contribution will help improve political science training data so that it is accurate, balanced, well contextualized, and in line with client expectations.

There is no immediate project available for this position right now. If you are a strong match, you may be contacted first when relevant opportunities come up, and you may also gain access to future work through the expert network.

What you will do

• Review political science items to catch quality issues and share ongoing feedback with contributors.
• Assess AI-generated content and reviewer work for conceptual correctness, institutional detail, comparative framing, theory accuracy, policy reasoning, source awareness, bias handling, clarity, formatting, and adherence to task rubrics.
• Keep trainers and QAs updated on new guidelines, workflow changes, and quality expectations through Discord and other team tools.
• Answer questions from trainers and QAs promptly and clearly, especially on institutions, comparative politics, public policy, political theory, international relations, bias, and rubric interpretation.
• Reach out to inactive contributors, encourage them to re-engage, track follow-ups, and raise any availability concerns.
• Build and maintain supporting documentation such as style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Plan and lead onboarding or training calls to walk trainers and QAs through project requirements, review standards, workflows, and quality thresholds.
• Make sure all reviewers apply the same standards consistently as project requirements change over time.
• Flag content that is misleading, one-sided, unsupported, outdated, overly political, or missing proper context.
• Suggest process improvements and help develop scalable QA workflows for political science training projects.

Selection process

Candidates go through an AI interview, a domain-specific task, and a recruiter interview.

Work style and tools

This role is built for a fast-moving remote environment and requires comfort working with collaboration and tracking tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.

Important note

There is no immediate project attached to this opening. Qualified candidates may be contacted when matching opportunities become available, and may be considered for future expert-network projects.

Requirements

• A 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 social science discipline.
• Very strong English skills for following instructions, collaborating with teams, and giving clear written feedback.
• At least 3 years of experience in political science research, teaching, policy analysis, public affairs, international relations, political writing, academic review, or a similar analytical role.
• Solid understanding of political institutions, comparative politics, international relations, public policy, political theory, electoral systems, governance, state capacity, civil society, and political behavior.
• The ability to judge political science work against detailed rubrics and detect oversimplification, ideological tilt, unsupported claims, inaccurate institutional descriptions, weak causal reasoning, or poor comparative analysis.
• Familiarity with democracy and authoritarianism, political economy, public administration, constitutional systems, electoral politics, conflict studies, international organizations, policy evaluation, or survey research is an advantage.
• Prior experience guiding or supporting remote teams of analysts, researchers, reviewers, educators, annotators, or QAs is strongly preferred.
• Comfort using remote collaboration and tracking tools in a dynamic environment.
• Strong organization and attention to detail, with experience maintaining style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation.
• Background in AI training, data annotation, LLM evaluation, policy QA, academic review, fact-checking, or rubric-based assessment is a strong plus.

Additional information

Selection involves an AI interview, a domain task, and a recruiter interview. The role is described as hourly, remote, and contractor-based. The employer is a fast-growing AI data services company serving major AI model developers.