The One App You Need On Your Resume If You Want a Job At Google

HughPickens.com writes Jim Edwards writes at Business Insider that Google is so large and has such a massive need for talent that if you have the right skills, Google is really enthusiastic to hear from you — especially if you know how to use MatLab, a fourth-generation programming language that allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. The key is that data is produced visually or graphically, rather than in a spreadsheet. According to Jonathan Rosenberg , Google's former senior vice president for product management, being a master of statistics is probably your best way into Google right now and if you want to work at Google, make sure you can use MatLab. Big data — how to create it, manipulate it, and put it to good use — is one of those areas in which Google is really enthusiastic about. The sexy job in the next ten years will be statisticians. When every business has free and ubiquitous data, the ability to understand it and extract value from it becomes the complimentary scarce factor. It leads to intelligence, and the intelligent business is the successful business, regardless of its size. Rosenberg says that "my quote about statistics that I didn't use but often do is, 'Data is the sword of the 21st century, those who wield it the samurai.'"

Comments

Shash-job-vertisement

[toQDuj]

Ugh, this reads like a job ad.

When I moved from Matlab to Python three years ago, I saw a massive speed increase of my methods. Also I no longer have to decide whether or not to shell out more cash for the statistics package, it's all there!

Looking back at my old Matlab code also makes me cringe a bit about the syntax of that language.

Re:Shash-job-vertisement

[solidraven]

I settled on a combination between Python and Perl (depending on if a lot of parsing is necessary or not). But when a lot of data is involved I go for the old fashioned choice of Fortran. It might not be pretty, and it sure as hell isn't the easiest language; but it beats the crap out of everything else when it comes to speed and convenience for parallelisation. People often forget that this is what Fortran was supposed to be good at, and it really is if you take the time to learn how to use it. Throw in Intel's Fortran compiler and a small cluster and you can chew through gigabytes of data at amazing speeds. The only thing it misses is visualisation tools, but you have a few good opensource dataset viewers, and you can always use Matlab or Python when necessary.

Re:Shash-job-vertisement

[Theovon]

R syntax is a lot better. In Matlab, the dimensions of a 3D array are Y,X,Z. That's just one of the many papercuts that makes Matlab difficult and unintuitive to use. R makes a hell of a lot more sense to me.

That being said, R is also very slow. For one project, I used R and ended up having to use a supercomputer (I only needed a few hundred Opertons out of the 4096 available) to get all the work done in time. For a followup project, I rewrote it in C++ and reran all the same stuff in the same period on a Core 2 Duo. R is really that slow.

But then, R is an interpreted language, so that's not a surprise. And I was able to rewrite my code in C++ because we didn't need any special libraries; if we had, I wouldn't have had the expertise to reimplement it. R is really convenient to use for many things, and it's also faster than Matlab for everything I've tried in both. Matlab is a dog, and the Mac version crashes at the drop of a hat too. I can't believe people pay money for that crap, except that it's pushed on universities, so people get used to it.

matlab is not new

[rabun_bike]

I used Matlab extensively in upper level mathematics courses as an undergrad from 1993 to 1995. I was surprised people don't know much about it or that Wolfram Alpha comes from the same company and even accepts Matlab syntax.

Analogy

[Charliemopps]

Data is the sword of the 21st century, those who wield it well, the Samurai.

So, data is a weapon used against us?
And those that wield it are our new feudal lords?

At least we know how Googles Senior management really feels about things.

MatLab is not really a good programming language

[orzetto]

MatLab is an old, crufty, feature-creeped script engine that I try to hold myself away from as much as I can. As a researcher and academic (got up to post-doc), Matlab is indeed ubiquitous in academia, but it's mostly due to entrenched positions. I see fewer and fewer people using Matlab these days, and that's a good thing.

Matlab is by all means not a fourth-generation programming language: it is procedural just like Fortran, which it supplanted in academia, but it does not have type-checking as C, it does not have OO support as C++, it does not do away with semicolons as end-of-line markers like Python; true, it has some advance features like OO and some functional programming, but (almost) nobody uses them, and most Matlab code is a horrible cruft made by self-not-so-well-taught academics. There is nothing in Matlab you cannot do better in Python with scipy, numpy, matplotlib and pandas. Or with declarative PLs like Modelica.

Matlab is also known for outrageous prices, leveraging on the fact their customer base are universities with big pockets and small administrative brains, and large corporations: they split their code base in many small chunks, and for each you need to pay more and more: as the saying goes, In Matlab you cannot do shit unless you buy a licence for the Toilet Paper toolbox.

Long story short: Matlab is the Perl of academia.

Python

[PvtVoid]

Python has obsolesced Matlab. There are even Matlab to Python cross-compilers and packages that allow Matlab to work like a Python library.

Who wants to work for Google nowadays?

[gweihir]

I know several really capable people that left Google, because of bureaucracy, corporate greed, incompetence, and general lack of vision. Google has become an ordinary large enterprise. And they do not even pay that well.

Octave

[Anonymous Coward]

Octave is a hugely better option. I once used 128 instances of Octave on a cluster to run something that the computer center only had 5 matlab licenses for. Running matlab on a cluster is just stupid.

Oh, and if you care, Octave is as compatible with matlab as matlab is with itself. Every time you upgrade matlab you have to deal with broken things. Octave is not bug-for-bug compatible with matlab; it's better. Hugely better.

Re:Sexy job

[TapeCutter]

Statistics and Logistics were a major part of my CS degree way back in the late 80's, more so than writing programs. If you think the only place statistics are used in tech companies is in marketing material then I have to conclude you have never worked as a corporate plumber and have no idea what they do. The core reason developers have always attracted good salaries at large corporations is that they can sift through mountains of data and tell the managers something about their business that they didn't know.

I'm not that far from retirement but that job will disappear in the near future, the technology in IBM's Watson will "democratise" data analysis in the same way the PC has "democratised" programming. Experts will have a "conversation" with the computer in which man and machine will both "learn" something, Google style search engines will look as quaint as a "ready reckoner" book of maths tables. And yes, Watson relies heavily on statistics, it doesn't actually give you an "answer" it gives a range of answers with an associated probability. Sounds kinda flakey but the fact that it can beat the world's top trivia buffs in an open ended problem domain is old news.

When it won the Jeopardy championship a few years ago it needed 2 tons of air-conditioning alone and was an exclusive toy for IBM devs. Today it fits on a "pizza box" server and IBM have recently opened the API to the public.

Disclaimer: Worked for IBM in the 90's, not shilling, just my personal opinion that "cognitive computing" may turn out to be more significant to human history than anything else that's happened since WW2.