A Growing Need For Data Scientists + The Automation Paradox

The demand for data scientists and talent capable of working with AI technology is rapidly increasing, according to a new survey by recruiters Robert Walters and VacancySoft. They also noted that the economy is experiencing an ‘automation paradox’, where the roles most affected by new technology are in the ‘middle-tier’ of the workforce.

First, the growing demand for data experts. Focusing on the UK as a good example of a G7 economy that is undergoing a period of employment role evolution, the survey found that specialist data science and analytics roles have increased significantly within medium to large companies in the UK between 2015 and 2019 (see below).

They also found that job growth for information security has ‘levelled-out after what was an active recruitment period in the lead-up to the GDPR deadline’.

Robert Walters and VacancySoft, (2019, projected).

This triggers two questions: why now? And also: does this connect to the legal world?

To answer this, check out the table below.

The British Academy (2018)

How much is a zettabyte? Er….well,  it’s a lot of data. Using more prosaic language, if a gigabyte is a mole hill, then zettabytes are Himalayan in scale. And there is no sign yet that this will slow.

It’s true that part of this explosion in data is due to video content, but it’s fair to say that text-based, unstructured data has also grown rapidly in the commercial world as well.

So what? If corporate clients, banks and insurance companies are producing more data that provides one challenge and one opportunity. The challenge is to keep up the legal sector’s ability to manage this flow of words and numerical data that relates in large part to contractual obligations. The opportunity is to use tech that can provide insights into this growing data set to help the clients.

Hence, law firms and large companies that handle large data stacks need….or at least should have these days….data scientists on hand to help them with it. In the legal sector this is no doubt tricky, as the data they’re working with has distinct legal aspects and therefore may need someone with science and legal knowledge. Those are very rare.

How many firms does this impact? Likely it relates for now to the firms handling very large e-discovery matters, as well as major M&A deals and compliance reviews, as well as those companies seeking to really look into their contractual data – and have the resources and the will to make that happen.

Naturally, legal AI tools play directly into this, as they are clearly the best tools available right now to engage with that mass of unstructured data. This suggests growing demand for such tools and platforms.

The Automation Paradox

The other interesting insight, which it appears is not directly from the survey, but rather something Robert Walters saw in other data and wanted to highlight, was that employment growth is at either end of the complexity curve.

I.e. experts in certain fields (e.g. data scientists), or with great knowledge in complex matters (e.g. top level commercial lawyers) are in demand. Also, people with limited skill sets, likely being asked to do manual tasks, are also seeing a growing demand.

Where demand is weaker is the lower tier office worker band, where repetitive labour, often in a digital environment is being automated, or made so much more efficient it no longer needs a dedicated person to manage it. E.g. the decline in the total number of secretaries per executive in a company, or partner at a law firm.

Conclusion: larger law firms and legal functions will need to hire data scientists, if they have not done so already, if they wish to stay on top of the challenges and opportunities that this firehose of data provides.

And, if you want a secure future in the legal world, then aim high. The more expert in your field you are the less likely what you do will decrease in value. What computers are good at is absorbing repetitive, digitally-based tasks.

P.S. as to why lower value manual employment is growing, AL’s view is that is this is being driven by a lack of investment in mechanised systems that can handle complex physical work. This in turn will reduce productivity and likely trap businesses and the workforce in a cycle of reduced skill demand and low investment.

(You can download the report here).

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