Social Science Research Assistant

micro1 is engaging Social Science Research Assistants to contribute expertise to a cutting-edge customer project focused on benchmarking frontier AI capabilities. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required, your domain knowledge is what matters.

Scope of Work

• Design and author complex, authentic evaluation tasks reflecting real-world research scenarios in your field (e.g., survey analysis, qualitative coding, literature review, statistical analysis).
• Source, synthesize, and create realistic research artifacts, including survey instruments, coded data sets, statistical outputs, and source documents.
• Define appropriate methodological approaches and provide clear, defensible interpretations aligned with social science best practices.
• Write comprehensive, 35+ item grading rubrics assessing methodological choices, execution fidelity, and quality of interpretation.
• Ensure all crafted tasks mirror the complexity and nuance of advanced, day-to-day research work, avoiding simplified or textbook-style exercises.
• Collaborate asynchronously with project leads and reviewers to refine tasks, data, and evaluation frameworks.
• Maintain high standards of rigor, detail, and transparency throughout all deliverables.

Preferred Qualifications

• Bachelor's or Master's degree in sociology, economics, psychology, political science, or a related social science discipline.
• Minimum 2 years of hands-on experience with survey instrument design, qualitative data coding, literature reviews, and statistical software (e.g., SPSS, R, Stata).
• Demonstrated proficiency in synthesizing diverse research sources and constructing well-documented data artifacts.
• Strong methodological rigor and commitment to accurate, reproducible research practices.
• Experience developing or applying comprehensive grading rubrics or evaluation guidelines.
• Comfort with detailed, methodical, and sometimes tedious research assignments across multiple data types and sources.
• Proficient written English skills suitable for authoring technical research content and evaluation materials.

Compensation Structure

Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.

Start Timeline & Availability

We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24 to 48 hours of completing onboarding.