4 Reasons Why You Shouldn’t Be a Data Scientist

Original article was published by Terence S on Artificial Intelligence on Medium

1. You don’t like the idea of having to constantly learn throughout your career.

Data science is an extremely broad term, which means that it means different things for different companies, and so, different companies desire different skillsets. For example, some companies desire machine learning knowledge others desire experimental design and A/B testing, some desire Python programmers and others desire R programmers, etc… Therefore, the skillset you develop at one company won’t necessarily carry you through your entire career.

On top of that, data science is a multidisciplinary job. You’re expected to have a certain level of knowledge in programming, statistics, mathematics, business understanding, etc… which means there you’ll ALWAYS have room to grow in one of these areas.

Lastly, like everything in tech, data science is constantly evolving. For example, it was only in 2015 that TensorFlow was created, and now, it’s one of the most in-demand skills. As new technologies are created and iterated to be better, you’ll be expected to learn new technologies as well.