We explore the evolution of digital career advising companions for the rapidly growing knowledge economies to enable continuous evaluation and re-skilling of workforce in a wide range of domains. These companions deal with a variety of unstructured data sources to glean actionable insights. We present our experiences from building one such companion, and describe interesting natural language processing and machine learning challenges and open problems.
