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With Data Scientists topping the list as one of the best emerging jobs, LinkedIn made a prediction earlier this year that it would be the most promising for 2019. Fast forward to now, the demand for this field has exploded with the number of opportunities and salary rising steadily across the globe – making it one of the most attractive job sectors.
Across all titles in this field, one of the main reasons for its strong growth in salaries is the exponential demand for these skillsets and the lack of suitably qualified talent. Currently, the sector has more than 4,000 vacancies, but these numbers are expected to increase in the next foreseeable future as organisations become even more data-led.
Businesses can tackle the shortage of talents in data science and still get the resources needed for the analysis of data by using tools like Artificial Intelligence (AI). To that end, companies can sift through massive amounts of data and help gain information that could be used to aid in the decision-making process.
Thanks to the advancement of technologies, the capability of AI has improved within the same timeframe. The increase in computational and analytical power means that AI can now complete more tasks in record time without the need for human involvement during its process.
While some may see AI as a threat to the current state of employment, the fact is, AI is also creating new exciting opportunities. According to a World Economic Forum (WEF) report, 75 million jobs are expected to be displaced, but the same deep learning technologies will create 133 million new roles over the next few years. From manufacturing to production lines, AI will simple be reshaping the kinds of jobs that are available.
In many instances, this approach means that businesses can focus on creating and improving higher priority tasks or projects that rely on niche human abilities. Particularly in the data science industry, it would mean that companies will be able to utilise their resources more effectively and maximise the benefits.
Deploying AI to undertake routine data mining is one way to helping businesses combat a general lack of resources in this area, but it isn’t the only solution.
Another option for businesses to address the need for data scientists is to look to recruit further away from the traditional job markets in fields with similar skills. Although it’s more common for companies to hire professionals with a background in data science, recruiting outside this scope will widen a narrow range of available candidates.
Professionals working in similar roles but different markets can transfer their skills from one sector to another with minimal disruptions. The added benefit from this approach is that it can offer a new perspective and challenge common understanding or assumptions that in turn, translate into valuable systematic insights.
Undoubtedly, hiring further from the sector can indeed pose challenges to most human resource teams, and this is especially true if the role is highly-technical. In this instance, businesses can seek support from recruitment consultancies who specialise in hiring and recruiting niche skills. As unlike in-house HR divisions, specialist recruitment consultancies who work across multiple industries have a unique understanding of what is and isn’t a transferable skill.
Get in touch and speak to one of our recruitment consultants for an insight-driven hiring strategy.
Upskilling is a rising trend in many industries, and according to a PwC Talent Update report, could be the element needed to create a workforce of the future. But to do so, businesses must first identify qualifying individuals in their existing workforce.
Modern software like data analytics and dashboards offer organisations and business leaders the chance to empower the visibility of skills, which can then be used to understand upskilling needs. Here, technology plays a vital role and businesses will need to commit to adopting an agile model that ultimately invest and integrate modern learning and development cultures.
In terms of difficulty, retraining professionals from different backgrounds to the data science field may prove to be far too complicated and expensive for most companies. Retraining requires a long-term overview of the organisation to implement skill transformations effectively while keeping up with the demands and advancement of the business.
From a hiring perspective, recruiting data scientists and those with a similar skillset is a relatively straightforward process. But hiring and retraining professionals from other backgrounds will require a different strategy. Organisations who wish to adopt this approach can manage this challenge by seeking support from recruitment consultancies with experience across multiple sectors.
The increase of businesses needing meaningful analysis of an ever-increasing pool of data means that demand for such skill will also continue to rise. In today's rapidly changing economy, companies will need to adopt and adapt different recruitment strategies to meet this challenge head-on.
A successful approach will require a granular understanding of business needs to futureproof employment demand. Whether it's through the use of AI, upskilling professionals with a similar skillset or retraining the workforce, companies must first understand the underlying mechanisms to help companies optimise decisions.