Social Science Research Assistant for AI Benchmarking
Overview
Remote contractor role supporting a frontier AI benchmarking project. You’ll design and run authentic evaluation tasks drawn from social science methods, then produce realistic research artifacts and grading rubrics. Your domain knowledge guides how models should be trained to reason and perform, with emphasis on rigor and transparent documentation. Prior AI experience isn’t required; focus is on solid social science expertise and careful task construction. Key tools and areas include survey design, qualitative coding, literature reviews, and statistical outputs, all built to reflect real-world research complexity. Survey design, Qualitative coding, Statistical analysis are central to the work.
What You'll Do6
- 1Design and author advanced evaluation tasks that mirror real-world research in your field, such as surveys, coding schemes, literature assessments, and statistical analyses.
- 2Source and assemble authentic research artifacts, including survey instruments, coded datasets, outputs from statistics packages, and supporting documents.
- 3Choose appropriate methods and provide interpretations that align with social science standards and justification.
- 4Create comprehensive grading rubrics of 35+ items to evaluate methodological choices, execution quality, and interpretive accuracy.
- 5Ensure tasks capture the nuance and complexity of day-to-day research rather than simplified, classroom-style exercises.
- 6Collaborate asynchronously with project leads to refine tasks, data, and evaluation criteria while maintaining rigorous documentation.
Requirements7
- 1Bachelor’s or Master’s degree in sociology, economics, psychology, political science, or a related field
- 2At least 2 years of hands-on experience with survey design, qualitative coding, literature reviews, and statistical software (e.g., SPSS, R, Stata)
- 3Proven ability to synthesize diverse sources into well-documented data artifacts
- 4Strong emphasis on methodological rigor and reproducible research practices
- 5Experience developing or applying detailed grading rubrics or evaluation guidelines
- 6Comfort with detailed, methodical tasks across multiple data types and sources
- 7Excellent written English for preparing technical research content and evaluation materials
Who Should Apply
The ideal candidate is a social science professional with hands-on survey design, coding, and literature review experience who can craft authentic, complex research tasks. This role may not be a fit for those lacking experience with statistical tools or those who prefer highly routine work. Common fit signals include a track record of rigorous, well-documented research artifacts and the ability to justify methodological choices; candidates who struggle with creating extended rubrics or who avoid nuanced data tasks may score lower. The work demands careful attention to detail and a comfort with asynchronous collaboration.
Salary Insight
Pay is task-based and paid per completed item that meets project specifications; no hourly rate is stated. Pay discussions occur later in the process.
Location
Required Skills
Application Tip
Highlight a specific project where you designed a survey or coding scheme and attached a 35+ item rubric to demonstrate your methodological rigor and rubric-building capability.
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How your application is processed
1Application received
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2ATS + eligibility screening
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