This project focuses on uncovering insights related to how organizations identify top talent, while reducing bias during the recruiting process.

Along with the innovative use of data science in a new domain, the researchers will draw from a unique data set. They are collecting extensive data on over 200 first-year MBA candidates from six top business schools who were invited to interview for internships at major consulting firms. Participants provide resumes, test scores, GPAs, and other demographic, professional, and academic information, including detailed information about how they prepared for interviews (method, length, and intensity), and they will complete a psychological survey to uncover variables related to fixed vs. growth mindset, intrinsic vs. extrinsic motivation, and other factors. Participants also go through an hour-long comprehensive behavioral and technical mock interview recorded in high definition. The researchers will then track real-world recruiting outcomes (first round interviews, second round interviews, and offers).

This study will use text and video image analysis, and other data science tools, to develop new variables in combination with analytical methods that go beyond traditional statistical analysis to uncover insights and identify predictors of recruiting success.

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