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In terms of current job openings probably R is best. Julia got its first stable release in August 2018, meaning that more companies could be adopting it now, but R has been around since 1995. If you like Python, Julia is probably easy to pick up though. Octave is incredibly slow and no competition for Matlab, Matlab is terrible as a programming language if you're used to Python, so it's likely you wouldn't enjoy your job if it involved Matlab.

In general, no, especially for typical data analysis tasks. MATLAB used to have an edge in signal processing, but (IMHO) lost it to Python-based solutions (especially when running things on GPUs, ML or not). If you're doing a lot of exploratory data analysis and statistics, R is worth a look.

Thanks for the replies. I did a course on Data Analysis from MIT and used R a bit there. I liked GGplot and RStudio. I don't think Python has anything close to those two. R was a bit harder to learn and I've already forgotten most of it, since I don't use it. I understand that it's based on Scheme and has roots in functional programming. I'm curious about Julia as it's being promoted as one of the fastest languages. I don't see a lot of value in that as I do most of my data intensive (in terabytes) work on pySpark on AWS clusters before I touch Pandas or any other BI tool. I couldn't use Julia on my laptop to do that! I guess sticking to R has more short term benefit as most courses on Statistics are heavily dependent on R. Julia will probably catch up soon.