I think the main reason Julia hasn't taken off is they arrived rather late to the party in terms of their target audience. Using Python and R to script libraries (or binaries) compiled in C and Fortran already had the momentum in the data science space. Julia first appeared in 2012 [1], which is also same year as the initial release of Anaconda [2], essentially a packaging and streamlining of what many in the scientific community were already doing with Python and R. With deep learning and data science really taking off in popularity the last few years, Python was the ecosystem of choice for most.
Julia might have a bright future. It seems to have a small but thriving community and its ambitions match what a lot of people want out of a programming language. The problem is that at this point "Python driving C+Fortran" is the 200 lb behemoth they're competing with, and face nontrivial competition from a host of other languages (R, Matlab, Go).
