
Most people in IT know that the role of the data scientist is growing in importance and many will know that the result of this demand means there is a shortage of people with the necessary skills to do the job. Search for the term “data scientist” and LinkedIn will return over 287,000 responses; data scientists are very much in demand and their services do not come cheaply. Six-figure salaries are mainstream.
First,
let me try to define my terms, because data science is a slippery term that
sloppy thinkers use interchangeably with other fashionable phrases. For me,
it’s to be located at the intersection of mathematics, statistics, business
domain knowledge, programming and research. It’s an attempt to combine the
power of the technologist with the experience of the line-of-business person
via the ability to mine data and apply statistical discipline and software
engineering. Combine all this, and you have a chance to detect underlying
patterns and see tease out meanings…you can see why these people are relatively
scarce in number.
But
if we accept the conventional wisdom that use of data can be a hugely powerful
weapon – and we should – what can we do to bridge the
gap between demand and supply of people with this cocktail of skills? The answer lies in reskilling and a programme of
education and recruitment to create a new generation of data scientists from
the ranks of developers, analysts, engineers and business users. Just as at
times of national crisis the government could call on conscription, companies
are recruiting armies
of citizen data scientists.
Of
course, they don’t have all the know-how listed in my attempt to define data science,
but citizen data scientists are emerging as a pragmatic response to the need
for better use of data. These people often are employees
who may not have been formally trained in mathematics or statistical analysis,
but they are smart, good at communicating and
possess a strong understanding of business
challenges and needs. They should also be excited by the possibility of
changing their organisations and learning to become better data
scientists as they go along.
At its most sophisticated,
data science can be a daunting task that involves complex algorithms and
programming knowledge, but advances in AI, predictive analytics and cloud
computing are democratising the discipline. In the age of Big Data and cloud
platforms such as AWS and Microsoft Azure, every organisation has access to
huge data sets and the compute capacity to query them. And the citizen data
scientist who has deep knowledge of the company’s culture, market and
profitability drivers might be in a better position than the specialist data
analyst with only very limited knowledge
of the employer’s gears and levers.
Paving
the way
But how best to encourage and assist the citizen data scientist?
It’s certainly the case that companies with an open culture of information
sharing will be best positioned. They should also be equipped with analysis
tools that mask underlying complexity and have user-friendly front-ends with
wizards and templates. Thankfully, the rise of assistants such as Alexa and
Siri are driving more conversational user interfaces that hide complex
calculations and encourage users to ask direct business and operational
questions. Similarly, software development is increasingly dependent on ‘low
code’ platforms and visual drag-and-drop user interfaces. The user should have
knowledge of data management and data structures and dependencies, but not
necessarily programming.
This means that the citizen data scientists don’t need to call on
the IT department at every turn, but can quickly create, test and deploy
applications. And this in turn means that analyses can quickly be delivered to
business decision makers and feedback accommodated. This again fits in with the
zeitgeist of our times when rapid application development, agile and scrum methodologies
are increasingly favoured over laborious, time-consuming waterfall approaches.
As organisations we all need to do better with data, corralling it, probing it, testing suppositions and seeking the insights that provide scope for competitive differentiation. Citizen data scientists provide a way to span the chasm between what we want to do and the shortfall in supply that lets us do it. If you feel that you could benefit from better use of the data, but struggle to hire experts, consider creating an internal programme and join the clarion call for citizen data scientists.

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