Computer Science 696CA - IS-Career Path Analysis

Previous efforts (Mimno and McCallum, 2008) have demonstrated the usefulness of topic models for understanding the dynamics of the job market. Using a corpus of resumes as training data, we can build a topic model that summarizes the structure of the job market as a whole, where the "topics" are sets of skills required for different positions. In addition, by capturing the sequential aspect of the resume data, we can construct a sequence model to more accurately predict state (role) transitions for individuals over time. The goal of this project is to build on this work and expand its scope to better understand workforce characteristics at a macro level. Example questions examined might include: Which roles are currently underserved by the talent pipeline? Are there differing risk/reward scenarios associated with different career paths that can be mitigated through strategy? What types of roles have the most variability in terms of career path? Students will be responsible for creating a set of analysis tools that interface with a data set consisting of parsed resumes, along with any outside data sources that are useful.

Open to MS-COMPSCI students with a concentration in Data Science. INSTRUCTOR PERMISSION REQUIRED.