Honors Theses and Capstones

Date of Award

Spring 2023

Project Type

Senior Honors Thesis

College or School

PAUL

Department

Data Science

Program or Major

Marketing and Information Systems & Business Analytics

Degree Name

Master of Business Administration

First Advisor

Billur Akdeniz Talay

Abstract

Professionals in the data science and analytics field are in high demand. Recently, business schools have introduced various academic programs to train students in those fields. However, what makes business school students interested in these career fields is not entirely known. Research questions such as who the major influencers are for business school students' career choices or whether there are any differences between genders in terms of their awareness, readiness, and interest in data science and analytics careers remain to be answered. Therefore, this study examines the segmentation of business school students in how they prepare for careers, drivers of interest for careers in data science and analytics fields, differences between genders, and business school students' major influencers. The results show that business school students can be divided into three different segments as Financial Return Seekers, Wholesome College Experience Seekers, and Role-Model Seekers. Using these segments colleges can better target students in raising their awareness, readiness, and interest for data science and analytics. Findings also show that both awareness and readiness positively affect a student's interest in data science and analytics careers. There were also differences found between men and women, where women scored lower with awareness, interest, and readiness to pursue careers in data science and analytics. Lastly, the research provided that parents and faculty are the major influencers of business school students' career decisions. Based on the results there are many opportunities for business school leadership and faculty to help students become more aware of the career path, with support around the identified segments, and efforts to increase participation of women with data science and analytics.

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