Despite the excitement around "data science," "big data," and
"analytics," the ambiguity of these terms has led to poor communication
between data scientists and organizations seeking their help. In this
report, authors Harlan Harris, Sean Murphy, and Marck Vaisman examine
their survey of several hundred data science practitioners in mid-2012,
when they asked respondents how they viewed their skills, careers, and
experiences with prospective employers. The results are striking.
Based on the survey data, the authors found that data scientists today
can be clustered into four subgroups, each with a different mix of
skillsets. Their purpose is to identify a new, more precise vocabulary
for data science roles, teams, and career paths.
This report describes:
- Four data scientist clusters: Data Businesspeople, Data Creatives,
Data Developers, and Data Researchers
- Cases in miscommunication between data scientists and organizations
looking to hire
- Why "T-shaped" data scientists have an advantage in breadth and depth
of skills
- How organizations can apply the survey results to identify, train,
integrate, team up, and promote data scientists