Is it a re-branding? Is it a combination of older professions? Termed “The Sexiest Job of the 21st Century” by the Harvard Business Review, just what might lie ahead for data scientists?
Data science and data scientist are two terms which are in their infancy, and their respective meanings are still debated in some circles. There are those who argue the term “data scientist” is just another way of saying statistician, while others counter this with their belief that although data scientists undertake similar work to statisticians, the former have a substantially broader skill set, one which is rare, highly sought after, and appears to be heading down a similar road to that travelled by the Wall Street “quants” of the eighties and nineties.
The term data science first appeared in the early sixties, being used instead of computer science by Danish computer scientist, and recipient of the 2005 Turing Award, Peter Naur. Fast forward almost half a century, and the term “data scientist” was coined by LinkedIn’s then Head of Data Products and Chief Scientist, DJ Patil, to describe his role, according to apost on the Salesforce Blog by Jennifer Bi in May this year.
In an article onSilicon Republic’s website, head of the Centre for Applied Data Analytics Research (CeADAR), Edward McDonnell, said: “The data scientist is a very unique combination of characteristics. This is a person who is familiar with maths, statistics and computer science, and is able to articulate business problems into technical solutions and give the insights and visualisations.”
In the October 2012 issue of theHarvard Business Review, Patil, and American academic, Thomas H Davenport, described data scientist as “The Sexiest Job of the 21st Century”. Around the same time, the McKinsey Global Institute predicted that 1.5million data managers would be needed by 2018, and that there would be a shortage of more than 100,000 data analytics in the US alone by the same year. According to numerous sources, data scientists are indeed in high demand, and in addition, the role is ranked number one in a list of the “25 Best Jobs in America for 2016” by Glassdoor.
Here in Ireland the role and work of data scientists has begun to be recognised, as back in September, the inaugural annual DatSci Awards were held to show recognition for some of the work and research being undertaken in data science on this small island.
The future for data scientists, like most careers at present, is unknown, it could present endless opportunities and lead to ground breaking changes in society, or it could be somewhat less fruitful and fall flat on its face. According to some sceptics, data scientists could even see themselves go the same way as the assembly line worker and be replaced by machines.
However, with the introduction of an MSc in Data Science and Analytics at University College Cork, and some similar courses in other third level institutes across Ireland, surely the future holds positive prospects for data scientists.
It is the introduction of courses such as these that can potentially convey the role as more legitimate. It will also increase the number of data scientists available for work here in Ireland; and with The Data Incubator and the General Assembly School, as well as other institutions, offering similar courses globally, there is no doubt that the high demand for data scientists will be closer to being met over the next decade.
Vitaly Gordon, the Chief Data Scientist forSalesforce said in theaforementioned blog post: “Thing is, we’re not even realizing how big data science will become.” Co-founder and President of the Data Science Association, Michael Walker, shares some of Gordon’s optimism, as he is quoted in anarticle on Cyber Trend as saying: “I firmly believe that data science will be a profession just like law and medicine, but it’ll take about 10 years.”
As for data scientists being replaced by machines, in theCyber Trend article, Walker conveyed his faith in the evidence that when man and machine work individually, they are both inferior to man and machine working together, so although automated technology may become ever more present in the work of data scientists, from Walker’s standpoint, without the human input they will not achieve the optimum results.
With innovative and inspiringspeakers such as Dongbai Guo (AliExpress), Christine Preisach (SAP), Joyeeta Das (Gyana Ltd), Jules Coleman (Hassle.com), and Marc Preusche (LeROI), as well as many more, the seemingly bright future of data science and data scientists will be a hot topic of discussion for attendees of DTS 2017 when February 15 and 16 rolls around.