I've not done a lot with "numeric" programming, but I was able to pick up Julia really quickly, and I was able to do a more-or-less straight port of my dad's code to Julia. What I was extremely impressed with was how much faster it went out of the box; for some of the more crunchy bits, running on the same hardware, the Julia code ran quite literally 150x faster, and this was without any Julia-specific optimizations other than adding types to the function arguments.
Since then I've learned a lot more about Julia, to a point where it has sort of become my go-to language for starting new projects (assuming I don't need to use a specific JVM library or something). It's basically guaranteed to give me fast code out of the box, it has most of the concurrency constructs that I actually care about, it has a better-than-average macro system (at least compared to something like C++), and personally I just think that the language looks pretty once you get into some more of the details. I wish it were a more popular language, because the only thing that has held me back from using it more has been the lack of library support. Most of the libraries are fine, but for example I had a lot of trouble getting the Bcrypt library working, which is something I wouldn't really have a problem with on a JVM language or C++ or something.
Of course, this is (hopefully) a temporary problem, as the language slowly grows in popularity the library support should just get better.
ETA:
I haven't done proper benchmarks on this so this is purely speculation, but that said I think that the biggest boost comes from the fact that Julia properly optimizes loops. My dad is a smart dude, but not being a software engineer in 2024, didn't really know that using loop constructs in most higher-level language is considered a code smell. I don't now about Octave, but I know in Python it's generally considered way better to try and avoid vanilla "loops" and try and convert looping things into some kind of vector operation.
I think the JIT part of Julia is smart enough to optimize loops out of the box, and so my straight port of my dad's code just "magically" got faster, and I was extremely impressed, but I suspect that if my dad had utilized a lot of the vector operations of Octave and/or Matlab, the results wouldn't be nearly as impressive. I suspect Julia would still have performed better (if nothing else because I was able to add type information), but I suspect it wouldn't be the 100+X speed increase that I was getting.