Originally posted on Data Science Central
“I keep saying that the sexy job in the next 10 years will be statisticians, and I’m not kidding”.
Hal Varian, Chief Economist at Google and emeritus professor at the University of California, better known as Berkeley, said on the 5th of August 2009.
Today, what Hal Varian said almost seven years ago has been confirmed, as is highlighted in the following graph taken from Google Trends, which gives a good idea of the current attention to figure of the Data Scientist.
The Observatory for Big Data Analytics & BI of Politecnico di Milano has been working on the theme of Data Scientists for a few years, and has now prepared a survey to be submitted to Data Scientists that will be used to create a picture of the Data Scientist, within their company and the context in which they operate.
If you work with data in your company, please support us in our research and take this totally anonymous survey here. Thank-you from the Observatory for Big Data Analytics & BI.
Graph 1: How many times the term “Data Scientist” has been searched on Google. The numbers in the graph represent the searched term in relation to the highest point in the graph. The value of 100 is given to the point with the maximum number of searches, the others values are proportional.
Mike Loukides, VP of O’Reilly Media, summarized the Data Scientist’s job description in these words:
“Data scientists are involved with gathering data, massaging it into a tractable form, making it tell its story, and presenting that story to others.”
We are in the era of Big Data, in an era where 2,5 quintillion (10^18) of bytes are generated every day. Both the private and public sector everywhere are adapting so that they can exploit the potential of Big Data by introducing into their organizations people who are able to extract information from data.
Getting information out of data is of increasing importance because of huge amount of data available. As Daniel Keys Moran, programmer and science fiction writer, said:“You can have data without information, but you cannot have information without data”.
In companies today, we are seeing positions like the CDO (Chief Data Officer) andData Scientists more often than we were used to.
The CDO is a business leader, typically a member of the organization’s executive management team, who defines and executes analytics strategies. This is the person actually responsible for defining and developing the strategies that will direct the company’s processes of data acquisition, data management, data analysis and data governance. This means that new governance roles and new professional figures have been introduced in many organizations to exploit what Big Data offer them in terms of opportunities.
According to the report on “Big Success with Big Data” (Accenture, 2014), 89% of companies believe that, without a big data analytics strategy, in 2015 they risk losing market share and will no longer be competitive.
Collecting data is not simply retrieving information: the Data Scientists’ role is to translate data into information, and currently there is a dearth of people with this set of skills.
It may seem controversial, but both companies and Data Scientists know very little about what skills are needed. They are operating in a turbulent environment where frequent monitoring is needed to know who actually uses which tools, which tools are considered old and becoming obsolete, and which are those used by the highest and lowest earners. According to a study by RJMetrics (2015), the Top 20 Skills of a Data Scientist are those contained in the following graph.
The graph clearly shows the importance of tools and programming languages such as Rand Python. Machine Learning, Data Mining and Statistics are also high up in the set of most requested skills. Those relating to Big Data are at about the 15th place.
The most recent research on Data Scientists showed that these professionals are more likely to be found in companies belonging to the ICT sector, internet companies andsoftware vendors, such as Microsoft and IBM, rather than in social networks(Facebook, LinkedIn, Twitter) Airbnb, Netflix etc. The following graph, provided – like the previous one – by RJMetrics, gives the proportion of Data Scientists by industry.
It is important to keep monitoring Data Scientists throughout industrial sectors, their diffusion and their main features, because, in the unsettled business world of today, we can certainly expect a great many changes to take place while companies become aware, at different times and in different ways, of the importance of Data Scientists
