Lucrative careers await the new wave of ‘big data scientists’

Data is increasingly being woven into the fabric of every industry sector and is seen as the new oil in the global information economy, enabling leaders to make better business decisions. Driving economic value from data could add £216 billion to the UK economy alone by 2017. Along with this new desire to tap into the vast amount of information around us, comes the emergence of a new and vital job role: the data scientist. Graduates in the field could be commanding a starting salary of up to £32,000 a year (around Euro 40,000) – 25% more than the average UK graduate salary, with plenty of opportunities for career development as the skills being demanded are in short supply, writes Laurie Miles.

A “data scientist” isn’t just a pretentious name for a business analyst. A data scientist must be able to explain the data that he or she is analysing, then use that data to glean important insights and make predictions. At a basic level analysts solely report on existing data to let others come up with the clever insight. So, what are the skills necessary to advance in a career as a data scientist? There isn’t just one core skill. Harnessing big data not only requires capacity to store data, but also the brainpower to effectively dissect this information and distil it into something that can be effectively applied. The core responsibilities of a big data scientist will often be more varied than that of a typical data analyst.

To gain access to big data sets, programming skills are required to engage with the likes of Hadoop and SQL type databases. Once access is gained, mathematical skills are really important, with a leaning towards statistics over mechanics, as there is a need to gain an understanding of complex data sets. There is also a requirement to be creative and challenge established patterns, asking new questions that haven’t been answered before. An element of creativity will also go a long way, as developing interesting and clear visualisations from mined data is a vital part of the role. Tied to this are the communication skills necessary to explain the findings in simple terms to management with no analytical expertise. In short, they need computational, creative and communication skills to solve business problems, create new strategies and solutions, and explain all this in simple terms. It is imperative that a data scientist perform at least one of these roles as part of a bigger team.

Graduates who complete a university education in the relevant subjects are increasingly turning their attention towards a lucrative career in the big data industry. The UK Government, in its Seizing the data opportunity paper recognised the need for industry, academia and government to work together to make sure enough graduates are produced with the skills being demanded by business. In particular it mentions the role played by the SAS Student Academy programme, a collaboration between the big data analytics firm and 20 UK universities that trains students in real-life big data skills.

As the job function grows in popularity, many wonder what those with the necessary skills can expect when beginning a career as a data scientist. There is of course the likelihood that they will start as a data serf, or even a data plumber! They will then advance through the ranks from data analyst to data scientist, then onwards and upwards to director of data science. There is even a new position emerging on the boards of some companies – that of the chief data officer. And whereas before the role of a data scientist was confined to individual companies, the remit has expanded. Indeed, not long ago, the Singaporean government appointed its first chief data scientist to help develop local capabilities in data analytics.

Large companies, as well as smaller medium-sized ones across a variety of sectors from banking to healthcare, are eager to extract value from all the data now available inside and outside their organisations. But the already high demand for individuals with the right skills is set to grow significantly. A recent study by SAS and e-skills UK revealed that around a third of the UK’s larger organisations will implement big data analytics programmes up to 2017, pushing demand for big data specialists up by 243 per cent. But the problem is three out of five large UK organisations already find it challenging to hire the specialists that they need. This is the reason for SAS providing SAS University Edition free of charge to those in higher education. This software can be hugely beneficial in creating a new generation with the analytical skills to mine the vast amounts of data in modern society.

There are so many business problems that a data scientist can help solve, it’s largely about solving the ones that will yield the most value. Let’s look at the telecoms industry as an example – there is such a plethora of data available that businesses need to look at how they can mine that to better understand their customers and prevent churn. If you take leading broadband, home phone and mobile company TalkTalk, it was previously looking at single levers of churn, but SAS has helped it identify multiple levers in combination, as well as uncovering new triggers and levers that they did not know existed. This is a significant step not only in terms of improving customer retention, but also in improving marketing and promotional efforts– and it’s all down to the data.

With mobile also providing geo-location data, there’s now scope to make real-time offers to customers’ handheld devices while they’re in-store. As it becomes possible to analyse more data more quickly, offers can be more personalised according to each person’s particular habits and preferences.

The work conducted by data scientists permeates into every area of our lives. For example, personal recommendations on retail sites and “people you may know” features on social networks are all developed and processed by big data analytics teams. Google uses more than 400 data scientists to optimise search algorithms, engineering companies such as GE use data analysts to improve service and maintenance routines, while healthcare firms use big data to determine and predict best patient healthcare practices.

As companies around the world race to gain a competitive edge in the big data industry, data scientists have the opportunity to compete on a global level, in what is becoming a rapidly emerging and important industry. SAS has launched a competition to find the top data scientists that the UK and Ireland have to offer, as we cannot afford to be left behind.