Numerous data scientists are leaving their positions. This is a worrying trend among firms who lose their valuable employees, even when these people are going to other data scientist positions.

In this post, we'll look at some of the reasons data scientists leave their positions as well as some strategies for hiring and keeping more data scientists. Additionally, we'll provide some advice for data scientists who want to find new positions amid the great hiring freeze.

Reasons Why Data Scientists Are Quitting their Jobs

Employee Disengagement

For tech companies, low employee engagement is a major contributor to employee churn. Low staff engagement reflects your data scientists' lack of passion and commitment for your business and their jobs.

They are not concerned with their work performance or the effects of their roles. High turnover rates and low productivity are the results of disengaged workers. There are numerous causes of employee disengagement, including:

Unsatisfactory pay if the workers believe they are being paid unfairly in light of the market, location, and industry.

• lack of chances for personal and professional growth
• poorly managed
• Stressful working conditions cause burnout and lower productivity.
• Disparity between expectations and reality

Data science was formerly regarded as the sexiest profession in the twenty-first century. Companies hurried to integrate data science, AI, and machine learning into their businesses, but often neglected to clarify their objectives in the process.

Other times, an employer will give a position a wrong description in the job description. A data scientist might, for example, be hired for a machine learning position but wind up managing basic analytics activities.

As a result, businesses will employ data science specialists and assign them tasks unrelated to data science duties. Professionals who are hired for such positions often leave their jobs because they are dissatisfied with them.

Lack of Opportunities for Professional Development

The area of data science is expanding. This indicates that there is a rising need for data science experts. The discipline is experiencing new possibilities and problems at the same time, making it necessary for data science experts to stay current.

Data scientists aspire to use cutting-edge tools to work on novel challenges that advance their personal and professional development, similar to other technology disciplines.

Data science specialists, however, change jobs frequently until they discover one that encourages professional development since they lack the opportunity for both.