Strategic Policy Analysis Expert

You will create challenging analytical tasks that reflect real workplace decisions in strategy, public policy, and political analysis. You will also assess submitted solutions for sound reasoning, accurate policy interpretation, and useful recommendations.

• Design scenarios such as market entry plans, operational turnaround proposals, geopolitical impact assessments, regulatory analysis memos, and statutory risk models.
• Create gold-standard solutions and structured rubrics for evaluating qualitative frameworks and data-backed recommendations.
• Write clear critiques that identify logical flaws, biased inferences, unsupported assumptions, and misunderstandings of policy mechanisms.
• Review and calibrate submissions, resolve difficult strategy or policy cases, and use peer feedback to maintain accuracy.

This is a remote contractor engagement for 12 weeks. The work is open worldwide, and the role requires professional fluency in English.

• Pay: Not specified in the listing.
• Schedule: At least 4 hours per day, up to 40 hours per week, with at least 4 hours of overlap with Pacific Time.
• Time commitment: 20 or more hours per week.
• Experience: 3 to 15 or more years in management consulting, corporate strategy, policy think tanks, government affairs, multilateral institutions, or a related field.
• Skills: Strong qualitative and quantitative synthesis, structured analysis, policy impact modeling, scenario evaluation, and close attention to detail.
• Communication: Ability to write concise executive briefs, policy memos, whitepapers, and objective rubric evaluations.
• Education: A bachelor's degree or equivalent practical experience is accepted. An advanced degree in business administration, public policy, international relations, political science, economics, or a related field is preferred.
• Helpful experience: AI evaluation, data annotation, content review, or quality assurance.

Apply on OpenTrain with your resume, then complete the application on the hiring site.

AI training is the human work behind many artificial intelligence systems. Contributors create examples and review model outputs, while specialists use their professional knowledge to judge whether responses are accurate, clear, and well reasoned.