As someone who used Python and R, and also Julia, my take on Julia has changed over time.
My overall assessment is that yes, it's definitely worth getting your feet wet with. It has all the advantages of R or Python (for numerics, a point I will return to), but with much, much better performance. I feel like the syntax is also cleaner than either, although it has more of an advantage over R than Python in that area (I like Python's syntax more than R's).
I had an experience of some prototype R code running for about a day without finishing. The same code in Julia finished in about 5 minutes. It was kind of the final straw that convinced me to gradually move.
Since that time, though, there's one issue that's kind of nagged me, and has only grown over time, which is that Julia is kind of a niche language, like R. It's a big niche, and it might not matter, but over time I've come to appreciate the fact that Python is more general purpose. I am also watching as things like Kotlin, Scala, and Nim gain in popularity and in resources. I suspect that Julia will expand over time, but those others have a head start in some ways (even if they are behind in other ways).
Like some others, I also had some experience of head-scratching changes that occurred with new API-breaking releases. They were subtle changes that were difficult to catch because they weren't deprecations or things that caused errors, but changes in how valid syntax is interpreted. I don't see that as a long-term problem, but it gave me pause.
I guess the TLDR is: if you're interested, I recommend you dip your toes in it, if that works for you, but with some caution. I see it more as a replacement for R long-term than Python, and I see serious competitors rising in popularity.