Every data scientist endeavors to make an impact with their analysis, and ultimately that is typically tied to some kind of visualization. There needs to be a way to a) build the visualization you want and b) get it out there to people who would find it useful.
Just plotting in matplotlib means that you must either export as a PNG (ew) or provide the analysis itself to users/decision makers. PNGs are terrible because you completely lose interactivity. Providing the analysis means figuring out deployment of your python environment, which is possible but just causes another step between analysis and decision made on the analysis.
Altair and the vega-lite grammar of visualizations provides an interoperable and data centric way to build visualizations. It is extremely flexible when building visualizations and I find it very intuitive when it comes to complex plots. They can also be easily embedded into any webpage after being exported using the vega-lite spec, just include the vega-lite script in the html page. Can even be used with in dashboarding tools like Spotfire (I assume also with things like PowerBI although I haven't done it).
Imo no real reason to use matplotlib as a data scientist lest you seriously limit the future impact of your work