Data science is a large and expanding field, and the issues it confronts vary greatly with each domain of application. To understand issues within each applied domain, one cannot simply read a book on education theory to comprehend it. Therefore, it is important to have a rich immersion and dialogue with the empirical domain. In doing so, one quickly realizes education is different from medicine, business, or the digital humanities. Not only are the problems of education different, but so are the ethical concerns, stakeholder interests, and the phenomena in question. To make data science of value to educational problems, there is a strong need for substantive immersion and dialogue across data science and education.