Results of a survey released today reveal how data scientists see their own field – their favorite job tasks, their biggest obstacles, and how their companies can empower them – and shed some light on the day-to-day activities/roles of the sometimes shadowy job title.
According to the 2015 Data Scientist Report, based on a survey that data enrichment and crowdsourcing company CrowdFlower conducted with data scientists from its online research panel, more than half of data scientists said that messy, poor-quality data is a key hurdle that prevents them from doing the tasks they cited as most interesting in their jobs: predictive analysis and data mining for behavioral patterns and future trends. Two-thirds said cleaning and organizing data was their least interesting and most time-consuming task, and nearly 40 percent said they don’t have enough time to do analysis.
The survey found that, although respondents share the title “data scientist,” the roles of the position vary. Most respondents identified as researchers (54.3 percent) or computer scientists (52.3 percent). Others identified themselves as having business intelligence analyst roles (36 percent). Other roles identified include mathematicians (19 percent), educators (18.3 percent), and entrepreneurs (12.4 percent).
There was widespread agreement, however, that, no matter what roles data scientists fill, there aren’t enough of them. Nearly 80 percent of respondents said there’s a shortage of data scientists. This observation reflects the McKinsey Global Institute prediction of a shortage in the United States of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of big data, as well as the rising popularity of statistics as an undergraduate major – statistics is now the fastest-growing STEM undergraduate degree, according to the American Statistical Association.
Regarding this next generation of data crunchers and trendspotters, data scientists cited a diverse background, real-world experience, and practical knowledge as important more frequently than they mentioned an advanced degree. Nearly 60 percent of respondents said to work with a diverse portfolio of problems, and about half said to focus on gaining business acumen, not just data science skills. Meanwhile, only 22 percent cited the need for a master’s or doctoral degree to advance in the field.
Asked how their organizations can empower data scientists, more than half of respondents (54.3 percent) cited “acquire all necessary tools to effectively do the job.” This was followed by “set clearer goals and objectives on projects” (52.3 percent), and “invest more in training and development to help team members continually grow their capabilities” (47.7 percent).
Results of the survey are illustrated in the following infographic.
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