Why Data Scientists and Engineers Quit Their Jobs
<p>A <a href="https://www.globenewswire.com/news-release/2021/10/15/2314725/0/en/Study-Reveals-High-Turnover-Rates-Among-Data-Science-Professionals.html" rel="noopener ugc nofollow" target="_blank">recent study</a> of data scientists made the following quite stark conclusion: “The typical data scientist works for a large tech firm — where they have been employed for roughly one year with an average of 6.2 years of prior experience in the field. Notably, they have switched companies twice (or more) since 2017 and will likely remain with their current employer for a mere 1.7 years on average. Only a tiny minority of those surveyed (2%) had not changed jobs within the last five years.”</p>
<p>Turnover is a big problem in the data science and data engineering professions, and it hurts everyone. Data scientists and engineers themselves do not want to be jumping frequently from position to position, as that does not help them build long term skills and expertise and looks bad on their CVs. Equally, for employers, replacing these skills is hard and expensive. Finding the specific technical background is not easy, and the ramp up time of new joiners is a further opportunity cost. Often, the desire to quickly replace someone leads to a vicious cycle of poorly qualified hires which exacerbates the turnover problem.</p>
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