4 ms·

From a hiring perspective, I'd like to know how bifurcated the Python skills employment ecosystem is from the Matlab employment ecosystem. Is Python all the ML

From a hiring perspective, I'd like to know how bifurcated the Python skills employment ecosystem is from the Matlab employment ecosystem. Is Python all the ML & dstascience folks, and Matlab is all the 'true-blue' mechanical, aerospace/automotive, & controls engineers? All else equal, is having either software package on a resume an inadvertent signal to the hiring manager that you're only in one ecosystem / community and not the other? Strategically should a job seeker emphasize experience in one of the packages for roles in one ecosystem (while downplaying/hiding skills in the other), and the inverse for facing comparable roles in the other ecosystem?

robertlagrant 4y ago
Depends on the hiring manager. All you can do is make sure your CV says what you want it to say and they will infer what they will.
jstx1 4y ago
> Strategically should a job seeker emphasize experience in one of the packages for roles in one ecosystem If you're on the data science job market, you should know Python because that's basically all the jobs right now (the Python vs R debate was relevant 5-6+ years ago and Matlab was never that big). I don't know enough about the engineering job market to comment on it.
- auggierose 4y ago
  Oh, is R not relevant anymore, or declining?
  - jstx1 4y ago
    It hasn't been relevant for a while, it's a tiny percentage of the job market and only getting smaller over time.
  - BrandonS113 4y ago
    I just hired a R engineer, so not that tiny. For a data science job with a lot of stats and math. R still beats Python for stats/data science programing. In my market, R people have more math/stats than Python applicants,
KeplerBoy 4y ago
A lot of that classical engineering stuff is moving to Python. At least that's what I'm observing at uni. The last real stronghold of Matlab is controls engineering, because dynamic systems and simulink are just a good match, but even there sympy is used for the symbolic calculations.
- bmitc 4y ago
  > At least that's what I'm observing at uni. That's not an industry and employment observation though.
  - deleted 4y ago
    [deleted]
7thaccount 4y ago
Generally speaking most data science stuff appears to mostly be Python with a little R and then a very very small amount of many other ecosystems (e.g. most of the elite banks do a lot of kdb+ in addition to a lot of Python). In engineering fields, it all just depends. Control systems (via Simulink) is still pretty rooted in Matlab last I checked and is a lot better documented than Python. In power systems (my field) most "programming" is either at the application level (like C, C++, or Fortran) if you're a vendor and at the scripting/API level with 95% of that being in Python and the other 5% probably being something like C#, Java, or shell script. All data analysis is either in Python or SQL. SQL is better if the data is already in a database. We deal with such large quantities of data that pandas usage is relatively rare though. It's more common to use a Python script to push a bunch of data to a SQL database to then do analysis. I do know some places that do post jobs with Matlab as a requirement and those are mostly the little R&D sections of those companies that tend to hire workers from academia that haven't been exposed to Python as much as Matlab. Comparing the two language ecosystems (what matters), I'd say that Python is much easier to do general programming in and ML, but Matlab has easier and definitely more consistent facilities for charting and graphs. I prefer Python for a lot of scripting work, but Matlab is still pretty nice if your company can afford a license. I wouldn't want to just be stuck in Matlab, but there are plenty of cases where I might reach for it over Python if available. At the end of the day though, they're both scripting languages and aren't very hard to learn. Any sane hiring manager should accept candidates with experience in either one as long as they don't need to hire a super expert to lead a big effort on day one.
l_theanine 4y ago
[dead]

robertlagrant 4y ago

Depends on the hiring manager. All you can do is make sure your CV says what you want it to say and they will infer what they will.

jstx1 4y ago

> Strategically should a job seeker emphasize experience in one of the packages for roles in one ecosystem If you're on the data science job market, you should know Python because that's basically all the jobs right now (the Python vs R debate was relevant 5-6+ years ago and Matlab was never that big). I don't know enough about the engineering job market to comment on it.

auggierose 4y ago
Oh, is R not relevant anymore, or declining?
- jstx1 4y ago
  It hasn't been relevant for a while, it's a tiny percentage of the job market and only getting smaller over time.
- BrandonS113 4y ago
  I just hired a R engineer, so not that tiny. For a data science job with a lot of stats and math. R still beats Python for stats/data science programing. In my market, R people have more math/stats than Python applicants,

KeplerBoy 4y ago

A lot of that classical engineering stuff is moving to Python. At least that's what I'm observing at uni. The last real stronghold of Matlab is controls engineering, because dynamic systems and simulink are just a good match, but even there sympy is used for the symbolic calculations.

bmitc 4y ago
> At least that's what I'm observing at uni. That's not an industry and employment observation though.
- deleted 4y ago
  [deleted]

7thaccount 4y ago

Generally speaking most data science stuff appears to mostly be Python with a little R and then a very very small amount of many other ecosystems (e.g. most of the elite banks do a lot of kdb+ in addition to a lot of Python). In engineering fields, it all just depends. Control systems (via Simulink) is still pretty rooted in Matlab last I checked and is a lot better documented than Python. In power systems (my field) most "programming" is either at the application level (like C, C++, or Fortran) if you're a vendor and at the scripting/API level with 95% of that being in Python and the other 5% probably being something like C#, Java, or shell script. All data analysis is either in Python or SQL. SQL is better if the data is already in a database. We deal with such large quantities of data that pandas usage is relatively rare though. It's more common to use a Python script to push a bunch of data to a SQL database to then do analysis. I do know some places that do post jobs with Matlab as a requirement and those are mostly the little R&D sections of those companies that tend to hire workers from academia that haven't been exposed to Python as much as Matlab. Comparing the two language ecosystems (what matters), I'd say that Python is much easier to do general programming in and ML, but Matlab has easier and definitely more consistent facilities for charting and graphs. I prefer Python for a lot of scripting work, but Matlab is still pretty nice if your company can afford a license. I wouldn't want to just be stuck in Matlab, but there are plenty of cases where I might reach for it over Python if available. At the end of the day though, they're both scripting languages and aren't very hard to learn. Any sane hiring manager should accept candidates with experience in either one as long as they don't need to hire a super expert to lead a big effort on day one.

l_theanine 4y ago

[dead]