5 ways to bridge the data scientist skills gap

The demand for data scientist professionals increased by 29% year-on-year between 2018 and 2019, and there are more than 4,000 data scientist job openings expected by the end of 2019. In a report released by LinkedIn, data science has been listed as one of the most promising job sectors in 2019 and this is backed by the growing demand for data professionals and job openings in recent times.

Top skills in data analysis are required by many organisations, however, a problem companies are encountering is a shortage of talent, thus an inability to fill roles fast enough. Cutthroat competition and sky high salaries are also signs of the considerable lack of data science talent.

But how are businesses dealing with this shortage and bridging the skills gap?

  1. Those looking for a career change

Due to the growing need for data scientists and the responsiveness to the sector itself, it is becoming more common that individuals with tech experience or interests in data are considering a career move. Vice President of tech firm SPR believes people who switch fields are people with a “work ethic and confidence,” and believes these people are a “much longer-term investment, than hiring data scientists outright.”

  1. Re-training current employees

In an attempt to bridge the skills gap some companies are turning to their own technical employee base to find potential data scientists. By incentivising and encouraging employees to participate in skill boosting training it is possible for organisations to close the skills gap.

  1. Leverage mentorships

Another way in which organisations address the skills shortage is to utilise the many experts in data science that they already have in house. Creating a mentorship scheme whereby these professionals teach newer recruits to enhance certain data science skills, organisations will address the issue head on and enhance the in house team already in place.

  1. Lean on tech

Not all roles carried out by data scientist need to be performed by data-scientists. In some areas it is possible that other employees in the business have hidden talents, interests and skills that make them very capable at carrying out data related tasks if given the right opportunities and exposure to enhance and develop these talents.

Senior architect at tech consulting firm Munroe Partners believes, “nearly every organisation has data science enthusiasts embedded throughout,” and its key “to take interest in your people to uncover unseen talent – to the point these ‘unknowns’ become highly skilled scientists and engineers.”

  1. Work with higher education

With an increase in college and university data science programs in recent years it has given organisations an opportunity to establish relationships with these learning bodies and therefore become a recommendation to promising talent to apply to. Data and analytics leader at KMPG believes companies should form alliances with these institutions and have a robust campus recruiting strategy”.

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