Deep Learning Data Science Competencies to Promote Workplace Readiness

Data science is a rapidly growing field with a 663% increase in the number of job postings for a data scientist between 2013 and 2018. The demand for college graduates who are trained in data science skills spans every field of science. Therefore, undergraduate and graduate programs must be responsive to align their curricula with these dynamic needs. However, the data scientist title is relatively new and formal data science competencies are yet to be defined. In this talk, I will describe our efforts at the University of Texas to 1. determine what these data science technical and soft skill competencies are by analyzing data from national job postings, and 2. systematically investigate how the pattern of required skills varies by co-occurrence, domain of science knowledge, and characteristics of the jobs and employers. Such knowledge can help identify gaps between academic preparation and the skills employers seek by identifying data science competencies employers are requesting within and between domains of science, and then evaluating how well these skills align with science curriculum and finally, predicting the future of job market’s supply versus demand for data science skills.