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.
Requirements
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.
Alpheva is a new expert network (launched September 2026); payout methods are not published yet, so confirm your first payment before scaling up.
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