Data Science Skills and Graduate Certificates: A Quantitative Text Analysis

ABSTRACT

The tremendous amount of data collected from connected devices and social media has created a high demand for new skills to help organizations gain the power of big data. With a shorter completion time, graduate certificates appeared to be a desirable alternative for working professionals to develop these skills. However, it was unclear if graduate certificates met the job market’s needs. Quantitative text analysis was used to analyze data science skills in more than 5,000 data science job descriptions and skills taught in 588 required courses in 166 graduate certificates to investigate if skills needed in the industry were taught in these graduate certificates. The results showed that 21% of skills were common across seven job categories. ‘Team’ was a non-technical skill in high demand, while ‘Python’ and ‘SQL’ were the technical skills in high demand. Although Business offered the highest number of certificates, a lower number of data-science skills were taught in these certificates. The findings also suggested that job categories in the EDISON Data Science Professional Profiles could be grouped into two separate profile groups. The findings of this research provide a comprehensive list of skills that are common in a wide range of data science jobs for universities to consider while they develop their data science programs.

KEYWORDS:

• Data-Science job skills
• Graduate data-science certificates
• Text analysis
• Big data
• EDISON Data Science Professional Profiles