The money is great and the jobs are sexy, so why do most data scientists spend several hours per week looking for new jobs? And why are 13 percent of data scientists actively looking to leave their current job?

Many tech companies are failing their employees, according to Kaggle CEO Anthony Goldbloom. Here is a report from the Financial Times:

According to Kaggle’s survey, most people working in the field say they spend 1-2 hours a week looking for a new job, says Goldbloom. This is borne out by the Stack Overflow data, which is based on a survey of 64,000 developers. Machine learning specialists topped its list of developers who said they were looking for a new job, at 14.3 per cent. Data scientists were a close second, at 13.2 per cent.

People working in this field experience many frustrations, says Goldbloom. Bad data are one of the main ones: their employers cannot provide the essential raw material for them to obtain results. Some also complain of being given a lack of clear questions to answer. Companies may sense the opportunity, but they often do not know enough to get the most from their data assets. This also highlights the lack of technical knowledge among non-specialist managers who work alongside data scientists and machine learning experts. And then there is the frustration that comes from being in the vanguard of any new profession. People complain of a lack of other talent to collaborate with, says Goldbloom.

Companies that grew up on the internet, collecting masses of data about their users’ behaviour and using techniques such as A/B testing to constantly improve their services, provide natural homes for workers like these. If they are to compete for some of tomorrow’s key talent, other companies need to make such techniques core to their own operations.