Erik Brynjolfsson
Sarah H. Bana
Daniel Rock
Sebastian Steffen

Using the full text of data from 200 million online job postings, we train and evaluate a natural language processing (NLP) model to learn the language of jobs. We analyze how jobs have changed in the past decade, and show how different words in the posting denote different occupations. We use this approach to create novel indexes of jobs, such as work-from-home ability. In ongoing work, we quantify the return to various skills.