作者
Miryung Kim, Thomas Zimmermann, Robert DeLine, Andrew Begel
发表日期
2017/9/19
来源
IEEE Transactions on Software Engineering
卷号
44
期号
11
页码范围
1024-1038
出版商
IEEE
简介
The demand for analyzing large scale telemetry, machine, and quality data is rapidly increasing in software industry. Data scientists are becoming popular within software teams, e.g., Facebook, LinkedIn and Microsoft are creating a new career path for data scientists. In this paper, we present a large-scale survey with 793 professional data scientists at Microsoft to understand their educational background, problem topics that they work on, tool usages, and activities. We cluster these data scientists based on the time spent for various activities and identify 9 distinct clusters of data scientists, and their corresponding characteristics. We also discuss the challenges that they face and the best practices they share with other data scientists. Our study finds several trends about data scientists in the software engineering context at Microsoft, and should inform managers on how to leverage data science capability effectively …
引用总数
20172018201920202021202220232024110254038464942
学术搜索中的文章
M Kim, T Zimmermann, R DeLine, A Begel - IEEE Transactions on Software Engineering, 2017