Graduate Student Research Assistant

About the role

The Department Survey Design & Methodology is seeking a graduate student to assist the Evaluating Synthetic Data Quality project. The role involves building a programmatic pipeline to detect quality issues in AI-generated survey data and supporting the team in developing indicators and tools for social scientists.

Responsibilities

• Co-development of a data quality analysis pipeline in R/Python
• Collection, processing, and analysis of AI-generated survey data
• Literature and software research on silicon sampling evaluation and data quality metrics
• Preparation of documentation and presentations
• Administrative support for AI-related survey research and services

Required skills

• R
• Statistical concepts
• Data analysis
• Social science data processing

Nice to have

• Python

Qualifications

• Enrolled in a Master’s program in Social Data Science, Computational Social Science, Big Data, or Social Sciences with a quantitative focus

Benefits

• Flexible working hours
• Mobile working regulations
• Company health management
• Discounted university sports programme
• Further training measures

About the Company

GESIS – Leibniz-Institute for the Social Sciences is an internationally active research institute, funded by federal and state governments and member of the Leibniz Association.