Data science employment opportunities of varied complexity and environment are in growing demand across the globe. Data science as a discipline potentially offers a wealth of jobs to prospective employees, while traditional information science-based roles continue to decrease as budgets get cut across the U.S. Since data is related closely to information historically, this research will explore the education of U.S. iSchool professionals and compare it to traditional data science roles being advertised within the job market. Through a combination of latent semantic analysis of over 1600 job postings and iSchool course documentation, it is our aim to explore the intersection of library and information science and data science. Hopefully these research findings will guide future directions for library and information science professionals into data science driven roles, while also examining and highlighting the data science techniques currently driven by the education of iSchool professionals. In addition, it is our aim to understand how data science could benefit from a mutually symbiotic relationship with the field of information science as statistically data scientists spend far too much time working on data preparation and not nearly enough time conducting scientific inquiry. The results of this examination will potentially guide future directions of iSchool students and professionals towards more cooperative data science roles and guide future research into the intersection between iSchools and data science and possibilities for partnership.