Co-operative education (co-op) programs enable students to gain real-world experience by alternating work and study terms. Understanding employers' expectations of students in different disciplines is therefore critical for success. To do this, the relationships between co-op job postings, required skills, and academic backgrounds can be modeled using graphs. This study proposes a novel graph methodology for analyzing employer expectations of co-op students by grouping academic backgrounds and either co-op job titles or required skills into graph clusters. A case study is used to demonstrate the effectiveness of this methodology. Over 13,000 co-op job postings are used to uncover key differences in employer expectations for students in each program, including the importance of communication for arts students who are expected to fill interdisciplinary roles and the prevalence of data science and highly specific technical skills in many academic programs.