Abstract

Attracting technology talent in today’s hiring climate is more complicated than ever. Recruiting for technology talent in non-technology industries is even more challenging. This intense hiring landscape is motivating companies not only to attract the right talent but also to create a culture that can retain and grow that talent. In this paper, we developed algorithms and present insights that use data provided in reviews to glean information employers can use to address or even change their priorities to meet the demands of an ever-changing job market. The core of our research is to investigate and attribute the role of company reviews in explaining the critical dimensions through which employees perceive their job. In order to provide more in-depth and targeted insights, we limit our focus to Technology related job reviews. Our contributions includes building an IT Professional profile that can help create an edge for recruiters We achieved our research by conducting a comprehensive topic modeling on employee reviews to detect aspects that define technology workers. Three unique topics not related to Indeed.com was discovered from our models; Learning & Development, Technical Skills and IT Support. Eight additional topics shews a more detailed analysis related to Indeed.com’s topics. We feel the information provided in our paper is a tool HR and recruiters can use to attract talent.

Recommended Citation

Madding, Chad; Ansari, Allen; Ballenger, Chris; and Thota, Aswini (2020) "Topic Modeling to Understand Technology Talent," SMU Data Science Review: Vol. 3: No. 2, Article 16.
Available at: https://scholar.smu.edu/datasciencereview/vol3/iss2/16