As the demand for data scientists continues to grow, universities are trying to figure out how to best contribute to the training of a workforce. However, there does not appear to be a consensus on the fundamental principles, expertise, skills, or knowledge-base needed to define an academic discipline. We argue that data science is not a discipline but rather an umbrella term used to describe a complex process involving not one data scientist possessing all the necessary expertise, but a team of data scientists with nonoverlapping complementary skills. We provide some recommendations for how to take this into account when designing data science academic programs.
Keywords: applied statistics; data science; data science curriculum; data wrangling; machine learning; software engineering.