Data Scientists: Why are they so expensive to hire?

Therefore, a mere 23 student class size from one university and roughly around 700 graduating students from all universities offering data science programs will not fulfil the fast-growing demand for people with data science skills.In 2018 the average salary for a junior level data scientist is $115,000 and those managing a team of 10–15 members can demand salaries as high as $350,000..Meanwhile, the median years of experience for a data scientist dropped from 9 years in 2014 to 6 years in 2015..Globally, the demand for data scientists is projected to exceed supply by more than 50% by 2019..With more than 40% of companies believing their inability to recruit data scientists is hindering their ability to compete it is no wonder over 60% of businesses train their staff in-house.Andrew Ng Promoting CourseraTwo solutions to fill the gap:There are two main approaches to help alleviate this skills shortage..Firstly, and one championed by AI superstar Andrew NG is to train more data scientists using non-traditional methods such as MOOCs (Massive Open Online Courses)..While this is a brilliant way for current developers and other data-centric employees to “Skill Up”, it is not yet the solution to the bigger problem..I say “yet” because this fundamentally requires a change in behaviour..Employers don’t yet place enough value on this type of education; many employers still look exclusively to the brand name universities when hiring..While this mentality is slowly changing, it is not coming quick enough to solve the problem in the short to medium term.The second approach is to enable more people without data science skills to apply these complex techniques to company data easily..In essence, let Artificial Intelligence and Machine Learning solve its own problems..By using techniques that have been developed (including here at MindsDB) over the last few years, it is possible to mimic a data scientist such that even a non-technical individual could perform data analytics with just a few lines of code or a few clicks.These two solutions are not mutually exclusive and will in tandem help companies use their data in a more meaningful way, driving cost savings and/or drive growth and revenue..For this to happen effectively there needs to be cultural changes inside organisations, resulting in better hiring policies and also a better use of tools and software that can solve many of the data problems they face without the need to expand headcount and hire an expensive data scientist.Adam Carrigan is Co-Founder of MindsDB an easy to use tool to add machine learning to your projects and data challenges.. More details

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