Data science skills: what’s driving the surge in demand?


Boris Paillard, CEO, Le Wagon

The demand for people with specialist data skills — like data scientists for example — has more than tripled over the last five years (+231%). With nearly every single sector, including banking, transport and retail generating an explosion in data, employers are desperately on the hunt for skilled experts who can make sense of it. 

But while the demand for these skills has been on the rise for some time, the COVID-19 pandemic has accentuated the need for data insights to ensure that businesses recover from the crisis effectively. Without data science, companies across all kinds of sectors run the risk of falling behind.

The boom in digital transformation

The term digital transformation is by no means anything new, despite it still being a widely discussed topic today. In fact, the term was coined way back in the 1990s as companies first started to implement digital technologies within their organisations.

Although digital transformation has been a top business priority for a long time, it’s not a quick and easy process, and has typically been pushed towards the bottom of the to-do list. According to research from Gartner, a significant 87% of senior business leaders highlighted digitisation as a company priority, however only 40% of organisations have implemented digital initiatives at scale.

But when the COVID-19 pandemic hit in March last year, companies who had not yet focused on digitising their operations experienced widespread panic as the whole world was suddenly forced to operate online.

As a result, businesses had to quickly step up their game and pivot their existing operations to meet the demands from customers who had moved toward online channels as a means of purchasing goods or services. In the space of only a few months, the COVID-19 crisis unleashed years’ worth of change in the way companies operate in a very short space of time.

In fact, according to a study from McKinsey, since the pandemic, companies have accelerated the digitisation of their customer and supply-chain interactions and of their internal operations by three to four years. In addition, the share of digital or digitally enabled products in their portfolios has accelerated by a whopping seven years.

But digitising operations means that companies will see a larger amount of processes being automated and more insights into operations being generated. In order to fully reap the benefits of digital transformation, businesses will need the ability to collate, analyse and manipulate huge volumes of data, which can present several challenges.

Not only is it the case the bigger the company, the bigger and more complex the data, it is also the case that the discipline of data science has not yet reached a stage of having well-documented, well-known and well-established processes and best-practices. There is not an easy playbook companies can rely on to not only interpret the data, but to understand how it can be used to benefit the business — whether it’s increasing operational efficiency, developing new potential revenue streams or the ability to grow existing capabilities. This is a major challenge when businesses have faced up to the fact that they can no longer afford to make decisions based on individual judgement — it needs to be through data.

Mind the (skills) gap

This is completely new ground for every organisation and the simple fact is that there is a lag on the skills education and training front when it comes to data science.

We’re now seeing a huge shift in the ecosystem around the topic. There is far greater understanding of the need to train people in how to apply data science skills to different departments, and how we can retrain people to meet the exploding demand for these skills from employers.

But if we are to meet these needs and equip employers with the right talent to overcome the challenges around data, it’s vital that there is accessible education out there for everyone to not only learn new skills, but have the opportunity to put these skills into practice and understand how to transform data into actionable insights.

While there are a lot of educational resources available, it’s important to encourage those looking to get into data science to start playing around with data. Not only to experiment and get their head around the principles, but to gain a better understanding of their own personal skills and objectives.

There are currently several organisations out there that are helping people to gain new skills and advance their professional career. Short-term formal education courses — like Le Wagon and Imperial College London’s joint Imperial Data Science Intensive Course for example — enable students to learn the theoretical side, but also allow them to experiment through class-based projects to equip them with the skills and knowledge to join a data science team and boost their career. 

Among the significant changes the pandemic has caused on businesses across the world, a reliance on data is one of the most significant. If organisations are to flourish both now and beyond COVID-19, then being able to hire and retain the right talent is a must.

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Boris Paillard

After studying engineering and applied mathematics at Ecole Centrale Paris, Boris Paillard worked 3 years in investment banking. Passionate about tech & education, he quit his job to work on various tech products before founding Le Wagon to teach tech skills to creative people. For the past 7 years, he has been leading the development of Le Wagon's training programmes and platforms. To date, his teams have trained 10,000+ alumni in Web Development and Data Science across 41 cities, making Le Wagon the world’s leading coding bootcamp worldwide.

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