Data science resume: projects section that beats Kaggle clichés

r/datascience roasts Titanic notebooks. Hireable signals: **production impact**.

**Strong project bullets** Problem → data scale → model/method → deployed outcome → metric moved.

**Weak** "I built a random forest with 90% accuracy" with no business context.

Tailor ML keywords to JD—NLP vs forecasting vs experimentation platforms differ.