Rare breeds — the data scientist conundrum, what can we do about it?

Aug 27, 2019 · 3 min read

by Angel Mitev, SVP & Practice Principal at Sciant

Why does Data Scientist rank as LinkedIn’s most promising job in the US for 2019? Well, one reason is data scientists are rapidly becoming the most sought after experts in tech.

A supply and demand problem

The jobsite saw a 56% increase in data scientist job openings since last year, with 4,000 new openings across the US alone. And in the UK 80% of companies are planning on hiring a data scientist in 2018 according to MHR Analytics. Overall, IBM predicts demand for data scientists will rise 28% by 2020.

This is in stark contrast to supply. A survey of LinkedIn found less than 200,000 people with that job title. Basically there is a huge shortfall, making it one of the most in-demand jobs in tech.

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Issues hiring talent (and keeping it)

All of which means if you need to employ a data scientist, you might have some issues. One HR department recently reported taking five months to recruit a data scientist and found that applicants were highly selective about where and what they would settle for.

The same supply-demand dynamics means that if you do manage to get your hands on one of these rare breeds, you might even have more trouble keeping them. High demand from other employers means there will always be a more attractive package just around the corner. Part of an attractive package is of course the salary and work environment, but also the potential of interesting work. Currently, designing and implementing the analytical solution is where they are most required, but when the project is set up and the role shifts to the day to day grind of adding reports, which can be done by a less qualified person, the role loses its lustre, thus making the implementation process ideal for outsourcing.

The situation is such, that data scientists spend an average of one-to-two hours a week looking for a new job, according to a survey by Kaggle, an online community of data scientists and machine learners. Much of this is due to being overloaded with data-related tasks that strictly shouldn’t be part of their remit. In fact a study by SAS found that more than half of data scientists suffer from work-related stress because of this overload. This was reiterated by a CIO of a global hotel chain speaking at the Hotel Tech Conference 2019 who had gone through several data scientists as they were unable to retain them internally, requiring the company to pursue an outsourcing strategy.

Lagging education and skills

Why, you might ask, is there such a lack?

Well it seems the pace of technological evolution has outstripped that of human education. University data science courses are woefully few. Research from the University of California shows less than a third of the global top 100 universities offer data science programmes, and only six of these are open to undergraduates. There is such a dearth of formal education that 66% of Kaggle users described themselves as self-taught, with over half saying they had used online courses to learn their skills.

What can you do?

All of which is pretty grim reading and by no means helps you to employ that data scientist you so badly need. So what should you do? Well, until there is a radical shake up in the education system, there is one clear solution — outsourcing.

Sciant has experts in big data and machine learning that can take the headache away. We offer tailored on-demand projects that achieve exactly what you want when you want it, so there’s no need to go through the months’ long process of hiring an in-house data scientist only to lose them to the next attractive offer that comes along. Just get in touch to see how we can help.

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