The Data Talent Gap: DataCon discuss Big Data’s “Elephant in The Room”

When it comes to business, there is no doubt that an enthusiastic embracing of the data revolution is imperative. The success of LinkedIn lends much to the data analysis expertise of the data analysis of Jonathan Goldman, and indeed, a pervading message throughout Corinium’s Datacon East Africa conference in Nairobi, 11th-12th September, seems to have been “believe in data or be left behind.”

But as Pezesha CEO Hilda Moraa joined the conversation at Datacon, another issue was clear: when it comes to data analysis and data science roles, demand vastly outweighs supply, and we need to work out what to do about it unless we are to “bring the productivity gains from data to a grinding halt.”

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According to The Quant Crunch report conducted by Burning Glass Technologies, Business-Higher Education Forum and IBM, data analysis job openings are being kept open for 45 days — 5 days longer than the market average; an indication of the struggle to hire.

There is the argument that, in the same way that computers have moved from something arhaic and mysterious to something that the common layman can access and use, sooner or later data will be an area where most of us at least have some degree of literacy.

However the problem is more urgent than that, with The Quant Crunch reporting that by 2020 the number of data analysis job openings will increase by 364,000 to a total of 2,727,000.

Why the talent gap?

“We cannot ignore academics.”

During her talk on data centricity, Pezesha CEO Hilda Moraa spoke of a talented young PhD mathematician who reported that, contrary to all these findings, his experience was that there are no opportunities for data scientists, and that all his quantitative skills aside, hirers are demanding business credentials.

Findings from The Quant Crunch support this notion:

“Overall, 81% of all Data Science and Analytics (DSA) job postings request workers with at least three years of prior work experience. The strong demand for experienced candidates, combined with the strong growth of many DSA roles, creates a chicken-and-egg problem within the DSA job market: there aren’t many opportunities for workers to gain the DSA-related experience that employers are requesting.”

Furthermore, it seems that a lack of consensus over how exactly a data scientist might fit into an organisation (as well as a lack of clarity over the exact skills required for such a role) is not helping matters.

Speaking on precisely this issue at Datacon, Hartnell Ndungi (Head of Business Intelligence & Analytics, Co-operative Bank Kenya), painted a picture of the appropriate candidate who not only has all the necessary statistical know-how, but is business-savvy also — a strategic thinker, a value seeker and an innovator. Perhaps a combination of assets, which, as things stand, is rarely found.

So what do we do?

Pezesha’s Hilda suggested an experimental approach, fostering the relative talents of software engineers and academics alike.

“We believe in harnessing the skills of software engineers, such that they can become data engineers as part of their growth plan. Let’s get developers in a room with academic data scientists and see what happens.”

This would eliminate the issue of experience, and also perhaps help solve the issue of role definition. By encouraging talented graduates to use their already learned skills in a professional environment, we would be allowing individuals to grow their capabilities in the real world, and also give us a better idea of exactly what a data analyst can be, and what they can do.

Indeed, this is an approach which echoes the recommendation from The Quant Crunch report for businesses to take an active role in specifying what they really need when it comes to these roles.

“To mitigate this talent shortage, organizations across the analytics ecosystem must build a detailed understanding of their talent needs. This will enable them to invest strategically in DSA talent pipeline development.”

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Data is at the heart of Pezesha’s mission. Using it to access the truth — to determine the true creditworthiness of our prospective borrowers — we are determined to leverage data to expand the level of financial inclusion in Africa. This mission we take very seriously, and as such, the value of data in our business cannot be overstated.

As a fast-growing company we are always keen to hear from enthusiastic and aligned individuals who can help us realise our vision for a more financially inclusive Africa.

You should be following us if you love and value data as much as we do:-).