Quick answer: Julia is often faster than Python and other high-level languages. Rather than writing high-level code in Python, R, or Matlab and performance-critical code in C, the idea is that one writes the whole thing in Julia.

Edit: I agree that the "...more interesting" comment above sounds condescending. I have not found the Julia community to be condescending.

One of the thing I like from Julia compare to Python is that it have the concept of missing data representation. Python's data science library represent it via NaN or Null which is good enough for most cases but not all cases.

I often wish R's syntax was cleaner and faster, Julia is may accomplish this. I don't think Python is a great substitute for R in many areas where statistic is heavily used and influenced. I've used Python for Deep Learning and NLP. Time series and many other statistical base stuff I use R.