The role of the data scientist in accountancy

Jean-Cyril Schütterlé
VP Product and Data Science
Sidetrade
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Harvard Business Review has described the data scientist as the “sexiest job of the 21st century”.

But why is that? What does the title: ‘data scientist’ mean exactly? And why is this kind of talent in such phenomenal demand within accountancy? Here is my spotlight on the new ‘rock stars’ of IT, and what it could mean for accountants, in a world where numbers and data are key.

Up until now, data scientists have been seen as just data experts, but since the introduction of machine learning and data engineering, they have to have a broad skill set including a solid understanding of the challenges that modern accountancy faces, and how these can be overcome.

People often think that the main aim of data science is to churn out predictive analytical solutions to anticipate and support the decisions that companies make. But it my opinion, its automation that’s adding real value to the role of the data scientist.

What part does machine learning play?

By learning from past experiences, machine learning algorithms mimic how we prioritise jobs and calculate our reasoning. This means they can relieve us of the repetitive manual work which they can do so much more reliably, quickly and efficiently. This could be in the form of filing tax returns, reading thousands of pages of contracts and summarising them, based on what you tell the algorithm is important, or the valuation of assets.

The heavy reliance on vast volumes of numbers and data within the accountancy and finance sector especially, make it a prime candidate for automation.

Humans do still play a role though, and a pretty important one. When it’s a case of mimetic learning, machines need guidance. This is where the data scientist comes in, making sure everything is working as it should.

Data scientists will be called upon to prove that machine-driven tasks are effective and help accountants operate more efficiently. Once they’ve devised an algorithm, they’ll have to compare machine capabilities with human performance, to see if it is feasible to use this type of technology to help with collecting data from contracts or filing tax returns, for example. If successful, how will this change the accountancy sector? Only time will tell, but it is likely this type of technology can only improve the service that clients experience from their accountants, and help them to work more efficiently.

About Jean-Cyril Schütterlé

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