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  • 标题:An Empirical Analysis of Requirements for Data Scientists Using Online Job Postings
  • 本地全文:下载
  • 作者:John Yohahn Kim ; Choong Kwon Lee
  • 期刊名称:International Journal of Software Engineering and Its Applications
  • 印刷版ISSN:1738-9984
  • 出版年度:2016
  • 卷号:10
  • 期号:4
  • 页码:161-172
  • DOI:10.14257/ijseia.2016.10.4.15
  • 出版社:SERSC
  • 摘要:A data scientist is a relatively new job title and is not yet fully defined or understood. Little research has been conducted on data scientists and there is still incongruity among its practitioners. Yet, the job market for data scientists is already active with high demand. Many companies have created their own definition of a data scientist based on their own needs. The purpose of this research is to explore the definition of a data scientist by examining how it is accepted in these industries and businesses. A content analysis of 1,240 job ads from various companies recruiting data scientists was conducted to identify what types of knowledge and skills were generally demanded. As a result, we found that data scientists were expected to be highly experienced professionals with advanced degrees. The main requisite areas of profession were statistics, modeling, machine learning, and analysis.
  • 关键词:Data Scientist; Job Advertisement; Content Analysis
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