>>7796936 protip: he is actually a CS major who doesn't want his major oversaturated by idiots and premed "i will major in the highest paying thing" types, so he talks smack about it on a Cantonese imageboard
>>7796740 if you are good, connections are not necessary. I got all of my internships without friend references. I had a few referrals, but I didn't pass the final round at those places.
The internships I got on my own were from a really known company that is amazing, and another one was from big 4. Just be good, do well on coding interviews, have a good resume, and you are in. I guess stats will give you an advantage while applying to finance/trading firms like Jane Street if that's your thing
>>7796937 >bandwagon A lot of companies blares that they need a lot of "data scientists" doing "big data" and how important it is to employ people with data and business skills.
It is all a lie.
Reality is that they SAY they will employ but in reality it is a huge marketing drive where they want to promote themselves and try to shame potential clients into buying their services since it is oh so hot.
Trouble is of course that this is hype straight out of the Gartner hype machine with the dial turned all the way to 11. Ask what it all means and you only get irritated replies masking their own uncertainties. Dig deeper and find no, zero, ziltch good examples that are not things everyone did 15 years ago.
>>7798016 I worked in this field for many years before I ever heard terms like "data science", "big data", and all of the rest of the current buzzwords. Whenever I needed to fill staff positions, it was very difficult to find people with the right mix of mathematics and computer science backgrounds.
Machine learning is not a new field. Statistical learning is not a new field. What is different today than 15-20 years ago is computational power and the sheer volume of data we have to work with. I can solve problems/train models today with a commodity desktop processor and gpu that would have required a supercomputer back then and still might not have been possible. For example, we studied the hell out of neural networks and then most folks drifted away from them because they were too slow to be of any practical use. They are back in vogue today because the hardware has finally caught up enough to make them useful.
I think it is a good time to be in the field, but I also don't think the typical CS undergrad degree today prepares you for it properly.
>>7796740 Actuary in the insurance industry here. We hire statisticians / data scientists, it's definitely on the rise. From a data science perspective, insurance is really exciting; lots of stuff to model. The bigger the cie, the more data they have to crunch and the more analysts they hire. Big insurers in the US (Geico, Progressive, Allstate, etc) employ dozens of them.
You'll need a masters degree and some people skills.
I live in FL and I notice there's not many CS majors here. Any possible explanation why this may be? Is it because there isn't much job market for CS majors in FL? I imagine the West Coast is overpopulated with CS majors. Will this leave me at any disadvantage once I graduate? I'm definitely willing to relocate out of state.
>>7798928 What if I have derived some algorithms for original research? I have taken a few graduate machine learning courses, and, frankly, there isn't much more to them besides the research components. Learning more algorithms does not necessarily make one a better data scientist.
>>7798933 Not sure, depends on school and research available I guess. I major in bioinformatics so my program is very specialized. We have a stats computation program (which is closest to OP I can get for my school) and it has more statistics and math based classes than a general comp. science degree.
>>7798896 Candidates with masters deg usually have better grades. They usually have predictive modeling experience too. Of course if you have other degrees, especially those you list, it might not be a problem, it shows you are above the typical statistical B. Sc crowd.
>>7798835 I am most familiar with the machine learning, so that is what I will comment on. The typical CS major is lacking in the mathematics foundation required for this field. If you want to separate yourself from the crowd, you should consider courses in mathematical statistics (not baby statistics), linear algebra (and really, really get it), linear and discrete optimization, numerical analysis (preferably the version intended for math majors), and maybe some graph theory (once again, the version taught in the math dept.). I'm sure I'm forgetting something, but these are the things that would impress me on a resume. Of course, all of this is in addition to taking every algorithms and ML course you possible can at your school.
>>7799005 Interesting. I am just saying that I am graduating in astrophysics with a minor in Stats/ML. If my senior thesis involves machine learning and I've done various internships, I don't see why I would be discounted so largely against somebody with just a MS degree.
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