Hypotheses, Not Hunches: What an AI Data Scientist Gets Right
TL;DR for operators The paper introduces an “AI Data Scientist”: a six-subagent system that moves from raw tabular data to cleaned data, tested hypotheses, engineered features, trained models, and business-facing recommendations.1 The useful idea is not that another agent can write Python. Congratulations, we have met 2025. The useful idea is that hypothesis testing becomes the workflow’s organising rail. ...