Data Science is a practical field. Hands-on skills are very important especially when you are interested in working outside academia as a practicing data scientist.
In academia, you need more theoretical and research skills. While in-depth knowledge in the theoretical foundations of data science is important, as a practicing data scientist, hands-on experience is very crucial and one way to showcase you hands-on skills is via building a very great portfolio. Companies interested in hiring you would definitely be asking you for a portfolio, as it gives evidence of your strengths in fundamental data science concepts.
Author: Benjamin Obi Tayo