Long regarded as the most widely used online classifieds service in the world for jobs, real estate and goods for sale, Craigslist currently serves over 700 geographic regions in more than 70 countries. Given the inconsistency of posting behaviors and categorical tagging from job postings, H2O’s teams wanted to create an application that could contextually predict the right categories to improve listing classifications. Using Spark’s Word2Vec model, and training a Sparkling Water GBM model based on the vectors of over 20,000 job postings, H2O was able to predict 80% of the appropriate job categories.