Taming the Chaos: How Embeddings Transform Messy Job Titles into Actionable Data
Discover how language model embeddings solve the perennial problem of messy user-entered job titles by mapping free-text entries to standardized occupational categories. This technical deep dive demonstrates a production-ready pipeline using O*NET data and JobBERT-v2 to bring structure to chaos without predefined rules or external APIs.