Data Science is a nascent and increasingly popular interdisciplinary field, wherein the data scientist uses large datasets to derive insights and inform decisions. Despite this, Decision Analysis is rarely mentioned as a necessary skill for a data scientist. What are the decision making gaps in Data Science, and what can — and should — decision analysts do to help close those gaps? Can addressing these gaps be the platform by which decision analytic principles are finally scaled throughout the organization? Our panel will tackle these questions and more.