Political Science QA Lead

Role overview

This remote contractor position is for a Political Science Quality Assurance Lead who will oversee quality control, consistency, and trainer performance across political science AI training work. You will assess AI-produced political science content as well as trainer and QA outputs, compare them with project guidelines, and deliver clear written feedback to help maintain high standards.

The role focuses on checking conceptual correctness, knowledge of institutions, comparative context, political theory accuracy, policy reasoning, awareness of sources, sensitivity to bias, clarity, formatting, instruction adherence, and compliance with project rubrics. You will also identify repeat quality problems, share updates with trainers and QAs, support onboarding, maintain documentation, and help re-engage contributors who are not consistently active.

This company is a fast-scaling AI data services business that creates training data for major AI companies and foundation-model labs. Your work in political science quality leadership will contribute directly to improving AI models by ensuring the data is accurate, balanced, well-contextualized, analytically sound, and aligned with client expectations.

There is no active project immediately available for this role, but qualified candidates may be contacted first when relevant work becomes available and may gain access to future opportunities through the expert network.

Selection process

The hiring process includes an AI interview, a subject-specific task, and a recruiter interview.

Employment details

This is an hourly contract role performed remotely.

Requirements

Candidates should hold 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.

Strong English communication skills are essential for following instructions, coordinating with the team, and writing precise feedback.

A minimum of 3 years of experience in political science research, teaching, policy analysis, public affairs, international relations, political writing, academic review, or similar analytical work is required.

You should have a solid understanding of political institutions, comparative politics, international relations, public policy, political theory, electoral systems, governance, state capacity, civil society, and political behavior.

The role requires the ability to judge political science content against detailed rubrics and identify issues such as oversimplification, ideological bias, unsupported claims, incorrect institutional descriptions, weak causal logic, or poor comparative analysis.

Experience with democracy and authoritarianism, political economy, public administration, constitutional systems, electoral politics, conflict studies, international organizations, policy evaluation, or survey research is preferred.

Prior experience leading or supporting remote teams of analysts, researchers, reviewers, educators, annotators, or QAs is strongly preferred.

You should be comfortable working in fast-moving remote environments using Discord, Google Sheets, Google Docs, trackers, dashboards, and project management tools.

Strong organization and attention to detail are needed to manage style guides, FAQs, trackers, onboarding material, 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 spot-checking political science items, identifying issues, sharing feedback through direct messages, and escalating repeated or serious problems.

Review AI-generated political science explanations, comparative analyses, policy summaries, political theory discussions, institutional descriptions, and reasoning for balance and accuracy.

Communicate with trainers and QAs on Discord about new item guidance, project updates, workflow changes, quality expectations, and political-science-specific review standards.

Answer trainer and QA questions clearly and quickly, especially on institutions, comparative politics, public policy, political theory, international relations, bias, and rubric interpretation.

Manage contributor activation by messaging inactive or non-working contributors, encouraging re-engagement, tracking follow-ups, and flagging availability concerns when needed.

Create 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 calls to explain project expectations, workflows, rubrics, quality standards, and political-science-specific review requirements.

Keep trainers and QAs aligned so that political science review guidelines are applied consistently and updates are understood as projects change.

Flag misleading, one-sided, unsupported, outdated, inflammatory, or poorly contextualized political claims and content.

Identify recurring quality gaps, suggest workflow improvements, and help design scalable QA processes for political science AI training projects.

Additional information

This role is part of a company supporting AI model training for major clients and is intended for contributors with strong domain expertise in political science.

The position is based remotely, and the listed location is Berlin, Berlin, Germany.

Applicants should be prepared for a contractor setup and an hourly working arrangement.