Standardising The Data Scientist
Appointing the right candidates in data science is no mean feat. A new certification programme hopes to change that
Martin Fleming, Chief Analytics Officer and Chief Economist at IBM, and James de Raeve, VP of The Open Group – an IT consortium – spoke to D/SRUPTION about the role of the data scientist, and a new certification programme for the profession.
Speaking at D/SRUPTION’s annual Disruption Summit Europe, Nell Watson of Singularity University said that in today’s world, we are drowning in data, but that this is a good thing. From the apps on our smartphones to our online browsing habits, we now generate an astonishing amount of data, and this can present significant business opportunities. However, this is only the case if companies can work out what to do with it…
Crucial to many businesses’ understanding and profitable use of data is the data scientist – a role that is becoming increasingly in demand in this digital age.
Why data science?
Business expert, IT expert, mathematician, trends analyst… The data scientist has a unique and varied role. A direct product of the rise of big data, data scientists process the information that is collected by companies, identify patterns and potential areas for growth, and communicate their findings back to both IT and business leaders.
If this seems to you a crucial aspect of modern business, you’re not alone. According to a report by MHR Analytics, 80 per cent of businesses are looking to hire a data scientist in 2019. As Martin Fleming of IBM states: “In this new era of AI, data is the true force of transformation, new roles of influence are emerging, and data professionals are leading the charge. This will enable organisations to solve problems in ways we never imagined and act faster than ever before to capture new opportunities.”
In spite of the exciting opportunities in the profession, however, the field of data science has a problem. The number of organisations looking to hire data scientists vastly exceeds the amount of people currently qualified for the job. According to Fleming, “As artificial intelligence continues to permeate all aspects of business, organisations are scrambling and struggling to identify, train and retain employees who can help them transform data into game changing insight.”
Fighting the dearth of the data scientist
With the data scientist categorised as an endangered species, it is difficult not only for organisations to recruit people into these roles, but also to ensure that they have the skills and expertise required for the job in hand. For James de Raeve of The Open Group, this can be attributed to a lack of standardisation in the profession.
“There needs to be a common understanding around the skills and experiences of professional data scientists,” he says. “This way, there is guidance to help individuals grow their professional competence, while organisations gain support in building career models that meet the requirements of the business now and in the future.”
In an effort to remedy this, The Open Group and IBM have come together to create a new certification programme for data science. Through the programme, individual data scientists can certify their skills via the process of peer review, thereby building trust in their profession. Similarly, at the business level, organisations can not only ensure that job opportunities are filled appropriately, but also develop individuals through their own, accredited programmes.
“The certification programme and the milestone based evaluation model we have developed provides organisations with an assessment model they can adopt internally to help mature their internal professions,” says de Raeve.
Staying ahead of the curve
This kind of industry wide programme is ideal for a young profession that suddenly finds itself in great demand. With the amount of data collected by businesses only looking set to increase in the future, the insight of the data scientist will remain key to staying ahead of competitors.
However, no certification programme can single handedly plug the skills gap currently seen in data science, or the wider digital skills shortage at large. The standardisation of experience and expertise in data science will help those already in the field, and may slowly impact the number of people considering taking up such roles. But if the relevant skills don’t exist in those people to start with, data science will carry on facing the same old problem.
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