From the course: Data Science Team Lifecycle Management
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How to prevent burnout
From the course: Data Science Team Lifecycle Management
How to prevent burnout
- Job burnout is a common problem for data scientists, resulting in decreased morale and productivity, and, in some cases, may even lead to depression. To protect your team's wellbeing, it's essential to have strategies in place to identify burnout before it even sets in, as well as policies promoting preventative action against it. Let's look at how to identify employees who may be at risk of burning out and the steps you can take to help them stay engaged and be productive. Let's start with the easy stuff. You can employ simple tactics, such as encouraging breaks and vacations, promoting a healthy work-life balance, and celebrating successes that provide recognition when deserved. But there are other tools you can use. First, data science managers must set realistic employee goals and avoid overloading them. Sure, there are always times when your team really needs to stretch to meet a deadline, but that shouldn't…
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