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What Data Science Means to Data Scientists

By   /  November 9, 2015  /  No Comments

teamby Angela Guess

Bob Hayes recently wrote in Customer Think, “The value of data is measured by what you do with it, and organizations are relying on data scientists to extract that value. I recently conducted a survey of data professionals to better understand what it means to be a data scientist. I discovered a few things in this study that can help organizations optimize the value of their data. While I wrote about these findings in prior posts, I want to summarize the major points here, in a more concise way… While some of these points below seem rather mundane or obvious, it’s important to note that these ideas are no longer only opinions; they are backed up by empirical data. This is how data science really works.”

Hayes continues with his first point: “There are a handful of different skills that make up the field of data science. While we measured five distinct skill types, a factor analysis of proficiency ratings of these five skills resulted in three distinct skill types: Business; Technology / Programming; Statistics / Math.” He continues, “There are different kinds of data scientists. Our study identified four distinct job roles among these data professionals: Developer (e.g., developer, engineer); Researcher (e.g., researcher, scientist, statistician); Creative (e.g., Jack of all trades, artist, hacker); Business Management (e.g., leader, business person, entrepreneur). Respondents were asked to select which of the job roles best described their work. They could choose one or any combination of job roles. The correlation across job roles (1 = selected; 0 = not selected) was quite low (average r was -.07; highest r was -.30), suggesting that these four job roles are distinct from each other.”

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