Julia is amazing for numerics, but the JIT is painfully slow for anything that gets looped only a few times or not at all. I don't think it is usable as a general purpose language until this gets improved somehow.
But is that a problem apart from in scripting? If you ain't looping you ain't waiting in my experience.... Can you give an example which isn't time to plot?
I think that a slow JIT is problematic in any application except for non-interactive numerical calculations. For example in a GUI software or in a server application it would be very undesirable to have each function run a million times slower the first time it gets called.
For GUI's I don't see this as an issue - JITs run alot faster than humans. All of Javascript is on a JIT - and thats the dominant UI for now! For servers generally you find that users are all calling the same function so it's very rare that you hit a blip - much more commonly users get performance problems from something else in the stack like the network or the client, and while Javascript is the dominant front end the dominant back end for servers is Java and that's got a JIT as well.
JavaScript's JIT is a tracing JIT, so it can compile code in the background while the interpreter/less optimized compiled code is actually running. In Julia, the compiler runs first, and then the compiled code is run. This will probably eventually change as Julia's compiler improves, but regardless, it's important to note this distinction.
But if you are creating cut and shut scripts for data science notebooks Python wins... the repl start time alone is a killer for Julia, add in the requirement to actually think about structure and the problem and it's out of my "3 -> 6hr" workflow.