About the role
Work directly with AI systems to create high-quality analytics data and teach models what careful, reproducible analysis looks like. Apply your graduate-level analytical skills while learning how evaluation examples and human feedback support AI post-training.
What you'll do
- Interact with AI models on data cleaning, exploratory analysis, metric definitions, SQL, spreadsheets, and Python-based tasks.
- Create realistic analytical questions, reference solutions, and explanations that make assumptions and limitations clear.
- Validate AI-generated calculations, code, charts, and conclusions against the underlying data.
- Compare responses, annotate mistakes, and develop evaluation criteria that reward accurate and reproducible analysis.
What you'll learn
- Learn how domain-specific examples and human feedback are used to support AI post-training.
- Gain practical experience evaluating AI responses, applying annotation guidelines, and checking dataset quality.
- See how factual accuracy, clear reasoning, and consistent feedback help teams assess and improve AI model behavior.
- Build experience at the intersection of your academic field and applied AI through project work and feedback.
Work arrangement
- Remote internship
- Collaborate with the team on scoped AI data and evaluation projects
Project scope, schedule, tools, and expectations will be discussed during the application process. Use only approved materials; do not share confidential employer, client, or university research data.
What we're looking for
- Currently enrolled in a master’s or higher degree program in analytics, statistics, computer science, economics, or a related field.
- Foundational spreadsheet, SQL, or Python skills.
- Understanding of basic statistics and how to communicate data clearly.
- Interest in reproducible analysis, careful validation, and learning from feedback.