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On a very basic level, most work-related challenges come from similar sources, regardless of field or industry: having to navigate professional relationships and communicate with people who might not always be on the same page as you. And you have to do that within the constraints of goals, available resources, and limited timeand on top of everything else you might need to deal with in your life.

If we take a closer look, though, we can see different patterns emerge not just across professions and workplace types, but even within well-defined roles and disciplines. That certainly appears to be the case for data and ML professionals, who despite a very broad range of skills and responsibilities, often have to resolve similar issues.

This week, were highlighting recent articles that focus on some of these common data science work and career challenges we see pop up again and again; theyre grounded in the authors personal experiences, but offer insights that can likely help a wide swath of our community. Enjoy!

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Data Science Career Challenges-and How to Overcome Them - Towards Data Science