Political Science Quality Assurance Lead

About the role

This remote contractor position is centered on quality leadership for political science AI training work. You will oversee consistency, accuracy, and trainer performance across projects that involve political science content. The role focuses on reviewing AI-written material and QA output, checking it against project rules, and delivering clear written feedback so contributors can improve and stay aligned with expectations.

You will assess work for conceptual correctness, institutional knowledge, comparative framing, political theory accuracy, policy reasoning, awareness of sources, sensitivity to bias, clarity, formatting, and overall adherence to each project rubric. The position also involves identifying repeated quality problems, sharing updates with trainers and QAs, supporting onboarding, keeping documentation current, and helping re-engage contributors who are inactive.

This is an hourly remote contractor role with a fast-growing AI data services company that supports major AI companies and foundation-model labs. The work directly contributes to improving political science training data so that AI systems produce answers that are balanced, well-contextualized, analytically sound, and aligned with client standards.

There is currently no immediate project attached to the role. However, qualified candidates may be among the first contacted when relevant work becomes available, and they will also gain access to future opportunities through the expert network.

Selection process

The hiring process includes three stages: an AI interview, a task specific to the domain, and a recruiter interview.

Requirements and profile

• 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.
• Excellent command of English for interpreting guidelines, coordinating with teams, and giving precise written feedback.
• At least 3 years of experience in political science research, teaching, policy analysis, public affairs, international relations, political writing, academic review, or similar analytical work.
• Solid knowledge of political institutions, comparative politics, international relations, public policy, political theory, electoral systems, governance, state capacity, civil society, and political behavior.
• Ability to judge political science content against detailed rubrics and identify problems such as oversimplification, ideological bias, unsupported claims, inaccurate institutional descriptions, weak causal logic, or poor comparative analysis.
• Exposure to 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.
• Prior experience guiding or supporting remote teams of analysts, researchers, reviewers, educators, annotators, or QAs is strongly preferred.
• Comfort working in fast-paced remote setups using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Strong organizational skills and attention to detail, with the ability to manage style guides, FAQs, trackers, onboarding content, 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 advantage.

Responsibilities

• Monitor quality by reviewing political science items, catching errors, giving regular feedback through direct messages, and escalating repeat or serious issues.
• Assess AI-generated political science explanations, comparative analyses, policy summaries, political theory discussions, institutional descriptions, and reasoning for accuracy and balance.
• Keep trainers and QAs informed through Discord about new instructions, project updates, workflow changes, quality expectations, and political-science-specific standards.
• Answer trainer and QA questions quickly 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 become active again, track follow-ups, and report availability concerns when necessary.
• Develop and maintain project documentation such as style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding resources.
• Plan and conduct onboarding and training sessions for trainers and QAs so they understand project requirements, workflows, rubrics, and review expectations.
• Make sure political science review standards are applied consistently and that all team members stay aligned as projects change over time.
• Review for bias and risk by flagging one-sided, unsupported, outdated, inflammatory, or poorly contextualized claims.
• Improve processes by identifying recurring gaps, suggesting workflow refinements, and helping build scalable QA systems for political science AI training projects.

Additional information

This role is remote and hourly, and it is structured as a contract engagement rather than a permanent employment position. Applicants should be prepared for a distributed workflow and a quality-led collaboration style across remote expert teams.