

The World Needs Data Scientists - T-A
http://businessintelligence.com/bi-insights/the-world-needs-data-scientists-infographic-2/

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shadowmint
I doubt it.

The rise and fall of data scientists (if they ever rise) will be swift.

Thing is, it's easy to collect a huge pile of data and then retrospectively
look at the data set and see patterns in it (very often, patterns that don't
actually exist but some over fitted model kind of suggests exist).

It's much much harder to get anything tangibly useful from that data.

Sometimes there _is no tangibly useful data_. It's _all just random_.*

'What have you got to show the last 2 weeks of effort?' ... 'Well, we
definitely proved that there's absolutely no correlation between our manager's
new initiative and online sales; that small spike we saw was within seasonal
variation'. How long do you think you'll have a job?

What people need is _better tools_ to auto-classify data into data sets and
perform real time analysis of their data (like Splunk, which is amazing), so
everyone can look at summary information in real time, at any time, and you
can respond dynamically to changes.

* - I know, I know, no data of that sort is totally random. ...but it's often so noisy that no statistically valid information is recoverable.

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upquark
Nah, data science is AI-complete, like natural language understanding. Think
of current state of data science as just the next iteration / rebranding of
statistics, powered by newest developments in CS, machine learning and
software industry. There is no shortage of statistical data exploration and
modeling applications, and we are pretty far from full software automation in
this space.

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jvm
AI-complete, awesome terminology you coined there.

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shn
what does it mean?

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jvm
Solving it would mean solving AI.

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mapt
Are businesses _paying handsomely_ for data scientists?

If not, then they don't _need_ data scientists.

Will they? Maybe, maybe not.

These ten-year industry forecast things are categorically ridiculous, whether
they come from the Bureau of Labor Statistics or some private forecaster.

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alanctgardner2
In my experience, people will throw money at "data scientists", if they can
find them. It really is hard to find someone who is experienced in Physics (or
Math, but they always seem to be physicists), has computational experience,
but mostly who has the right frame of mind. A lot of people I've met who would
be qualified for the role think it's beneath them: they don't want to use
existing libraries, they want to progress the state of the art. And once
you've done a PhD, I think it's hard for us to offer them a consistent level
of challenging work.

Despite the 'science' part, I think there's a significant engineering
component to the job: working within resource constraints and reusing existing
tools. I've heard a lot of good explanations of how to approximate an
integral, but the same people aren't really keen on working on a production
recommendation system.

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thebooktocome
> And once you've done a PhD, I think it's hard for us to offer them a
> consistent level of challenging work.

As someone who's almost gotten their PhD in (mathematical models of) medical
imaging, I think you'd be surprised at what kind of work would be consistently
challenging enough to interest me.

I was at a job forum a couple weeks ago, and whenever I would bring up my
incoming doctorate, company reps would be like "Oh, well our stuff must be
pretty boring to you, then." I really wanted to say, "If I'm talking to you,
it means what you're doing is interesting to me!"

I'm sure some PhDs are driven to improve the state of the art, but there's
also a perception that a PhD won't want to go back to working on problems that
are already solved in principle -- and that perception scares me, because I'm
going to need a job soon....

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kartikkumar
> I was at a job forum a couple weeks ago, and whenever I would bring up my
> incoming doctorate, company reps would be like "Oh, well our stuff must be
> pretty boring to you, then." I really wanted to say, "If I'm talking to you,
> it means what you're doing is interesting to me!"

Yes! There is an absolute myth in industry that if someone who has a PhD shows
interest, then you're best looking elsewhere, because they're likely to not
find the work challenging enough and jump ship easily as a result.

I'm on the verge of completing my PhD thesis, so I can easily relate to what
you're saying. I've pretty much perfected the art of starting with "I'm
getting my PhD, but don't assume that I'm not interested in more "mundane"
things". Pretty much, I think there's a challenge to be had in any tech job,
and I think the main characteristics to convey to a possible future employer
is that beyond having a great tech skill set, you know how to manage a project
(HUGE skill I've gained from managing my PhD), you know how to perservere in
the face of adversity (any PhD candidate that hasn't faced this hasn't done
their PhD the "right" way in my opinion), and you're creative right down to
your core.

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Lucy_karpova
As a recruiter, I’d say that you really need to tell what you’re thinking to
people who might interview you. PhD shows that you’ve spent some years to get
your skills Certified and thus master some of them. Bur it doesn’t mean that a
person with a PhD is better than the one without but with 5-10 years
experience of working in some specific area. Some good programmers and
scientists(like data scientist) never get a PhD and their skills are not lower
compared to their certified peers. So my advice would be: lay it on the line
regarding what you’re looking for in terms of challenges and reward for them
and show what you can. Papers don’t matter much nowadays but personalities do.

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kartikkumar
A PhD might not demonstrate that you're anymore capable of a specific job, but
by the same reckoning plenty of employers pigeon-hole PhDs as "academic-types"
with no sense of how things work in the real world. With respect to that, it
is really is about breaking unfounded stereotypes and debunking myths that if
you've gone through formal training and you have the "Dr." title attached to
your name, that you're not really able to be a team player and achieve what's
necessary in the business world. Bottomline is that whether you have a PhD or
not, as you say, you have to show what you're capable of. The fact of the
matter is that having completed a PhD brings with it a lot of "real world"
skills than simply becoming a domain expert: project management, creativity,
passion, perserverance, to name just a few. My experience, shared by others
with a research background is that the the tech industry often needs
"educating" that PhDs can bring meaningful value to the table, even for
problems that at first might seem to not be of interest.

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kartikkumar
Gearing myself towards a data science career, it strikes me as a particularly
odd way of presenting growth in the field. A lot of these articles seem to
suggest that the field has been recently "discovered", when it's more a case
of the technology supporting more advanced analysis. "Data science" existed
before all of this hype, and I think it's a misnomer to suggest that that
wasn't the case. There's definitely a greater spotlight on data science now,
but I don't think that's any real reflection of how business intelligence and
data analytics were done before the mega-hype kicked in.

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alex_anglin
Speaking as someone for whom statistical software puts food on my table, one
of my favorite statements about data science is (roughly speaking) "If you
don't have data, are you really a scientist?"

I would completely agree with your point about technology supporting more
advanced analysis: Current information processing capabilities allow us to ask
new questions from higher volumes of data than was possible in the past.

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bayesianhorse
"data scientist" sounds much more interesting and succinct than "scientist who
transform and analyzes data which can only be transformed and analyzed by
computational means".

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w_t_payne
Unfortunately, because of all the hype, all it is going to get is douchebags
instead.

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zdw
Having graduated in May of 2001, and seeing my CS classes go from full of
people to a ghost town from March-May, I wouldn't be surprised.

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notahacker
Does the 15000% YOY increase in "data scientist" job postings reflect an
actual greater demand for data scientists, or a trendy retitling of vacancies
that were previously give titles like "market analyst", "data product
manager", "operational research analyst" or even "actuary" and "economist"?

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SCAQTony
Great! More analytics people (and that is what they are being used for)
looking up our butts so as to to spy on inner behaviors, proffer the "correct"
ads in front of our faces, figure out who should be hired and fired and
telling artists what sort of art they have to produce.

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thenomad
Speaking as an artist, if you know someone with provable expertise in
analysing what sort of art I should produce, I would _very much_ like to hear
from them.

Making art and making stuff you think people will like are not mutually
exclusive.

(I am very serious about this, by the way - if you have expertise in analytics
for storytelling, or even just interesting ideas for same, please shoot me an
email.)

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SCAQTony
Well, if that's what your craft is all about Slashdot did an in depth analysis
on the subject here:

[http://slashdot.org/topic/bi/can-big-data-prevent-
hollywoods...](http://slashdot.org/topic/bi/can-big-data-prevent-hollywoods-
blockbuster-flops/)

Here is a white paper on how to roll out you movie based upon "data scientist"
analysis.

[http://www.google.com/think/research-studies/quantifying-
mov...](http://www.google.com/think/research-studies/quantifying-movie-
magic.html)

I have no idea why you are seduced by this? Whistler likened painting
portraits (which he was paid very well for) to prostitution and on his own
time & dime gave us his nocturne paintings which ultimately inspiring Monet in
the process.

[http://www.stargonaut.com/trialog.html](http://www.stargonaut.com/trialog.html)

Analytics tells you where you have been not where you are going. Novelty
changes everything and analytics can't predict innovation. That is why
Hollywood and the music industry suck.

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thenomad
Thanks for the links - interesting stuff!

Why I'm interested: because much like money, analytics are a terrible master
but a wonderful servant.

If you're ruled by them, I agree, that's limiting - but if what they're doing
is providing useful information about your audience, that's invaluable. This
is particularly true if you're a recording-based artist (I am), as it
partially allows you to restore the feedback that you'd get from a live
audience.

As many people have said, before you can break the rules you should probably
understand them. Likewise, before you go against audience expectations it's
helpful to know what they expect.

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mrcactu5
what about videogame designer or "solar panel consultant" ?

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jnbiche
Odd use of a pie chart for a web site devoted to data science, since pie chart
portions usually add up to 100%. It would have made sense if they had shown
the categories as highest degree earned, instead of degree(s) earned.

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robbfitzsimmons
Reminds me of my favorite Tumblr lately, wtfviz
([http://wtfviz.net/](http://wtfviz.net/)).

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jnbiche
Oh god, I'm glad I didn't have coffee in my mouth with some of those. However,
there are a few on there that I actually think are pretty good, if
unconventional (like the senate voting visualization, which does a great job
of showing polarization).

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evli
Any advice on an aspiring data scientist?

I am currently finishing my bachelors in applied math, and computer science.
Started to focus on machine learning this semester and hoping to do my
capstone on it.

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skybrian
It's work in progress but this book seems interesting so far:
[http://www.manning.com/zumel/](http://www.manning.com/zumel/)

(Disclosure: written by a friend.)

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ruang
I skimmed through the intro and just bought the book. Thanks for the rec!

I love the idea of being able to interact with the authors as they write the
book.

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darkhorn
You mean Statisticians.

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bayesianhorse
The world sure doesn't need more nerds to tell it how data scientists have
been around since the scientific method and it's all a bubble any way.

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trimbo
We need more data scientists to make more infographics!

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dancecodes
And the world needs also with good and easy education permanent and easy
access to knowledges.

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badwetter
Yeah for the spy agencies ....

