

Data scientists are the new rockstars - tijsmarkusse
http://startupjuncture.com/2013/05/08/data-scientists-are-the-new-rockstars/

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xradionut
Bullshit.

"Big Data" and "Data Scientist" are the latest buzzwords like Web 2.0 and Java
were during their ORA hype-r eras.

There is a lot more data. There are a lot more tools and technology to deal
with data. There is a need for high quality people that understand how to
handle data. But there are no rockstars, there are people that have passion
and spent years learning and teaching their craft. But they aren't rock stars.
The best may get paid as much as a very well off doctor or business owner, but
they aren't going to fill stadiums around the world, sell millions of t-shirts
or be targets of media gossip columns.

~~~
jkldotio
My main objection to it is that this rebranding of statistics (and machine
learning I suppose) obscures the deep political connection statistics has[1]
and in so doing obscures the fact it's going to have major political
ramifications across this century. Happy clappy summer of code donations from
Google to EFF or the Sunlight Foundation are entirely not proportional to the
extremely high level of abuse that could potentially stem from these
technologies (see the use of IBM sorting machines in the Holocaust).

Technology at a basic level amplifies agency, certain techniques and their
resultant technologies have benefited individuals and citizens more than State
agencies and with others it's been the inverse. I think we are moving into an
stage where there is potential for massive recentralisation of control in
various domains.

But this is HN, not a political discussion forum, most of the 'frighteningly
ambitious ideas' to grace these pages are to do with pushing out more ads or
other such pablum. PG isn't a philanthropist and YC isn't a charitable
foundation; HN is naturally aligned with those objectives.

[1][https://en.wikipedia.org/wiki/History_of_statistics#Etymolog...](https://en.wikipedia.org/wiki/History_of_statistics#Etymology)

~~~
goldfeld
Thanks for this. It's a humbling comment that puts reality into perspective:
there are several ethical and moral challenges we coders are gonna be put
through in this century, far, far removed from the Silicon Valley bubble and
it's love of ads. And it's this love of ads (read, millions and billions of
dollars) at the expense of enriching corporations and tearing down privacy
that worries me a lot about our future, if it's going to depend on
programmers' current moral standards--though really, it's all human nature,
it's not like we're a different breed. But we definitely are more informed
than the average citizen, and more of us should take responsibility for
increasing freedom and basic human conditions, as opposed to selling social
local deals.

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MrMan
So plain old "scientists" don't already use Data the right way? How about
boring old "statisticians?" Not enough javascript?

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marknutter
Please, let the term "rock star" die.

~~~
petercooper
Slippery slope though. We might need to throw in ninja, craftsman, hipster,
and guru while we're at it, too.

~~~
beachstartup
that sounds like an awesome slope to slip down on. let's get rid of all of
those ridiculous terms.

how about we just use the oh so boring "professional" instead? i want respect
from society for my work, not a cute pet title co-opted from other industries,
where they can use these terms with a straight face and without rolled eyes
from the audience.

~~~
petercooper
Unfortunately even "professional" gets a bum rap from some quarters:
<https://twitter.com/dhh/status/1631100714> ;-)

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bane
What troubles me most about the title "Data Scientist" is that it really means
"Statistician" or "Statistical Analyst". There are so many interesting things
you can do with lots of data, stats is but one of them. What do we call people
who are good at some of the other disciplines?

I've spent bits of my career working with fairly large data sets at one time
or another, and providing discovery, insight and analytic tools into that
data, but very little of it seems to have anything remotely to do with what
the job descriptions for "Data Scientist" are asking for.

Consider this, building a very large graph of the internet, then using various
models on that graph to find unique and actionable insights: such as finding
routing bottlenecks for a video delivery service, involves lots of data, lots
of scientific like exploration, yet isn't a "data scientist" job by the job
reqs.

How about this, building a text parser that can finely categorize and make
recommendations for a research organization based on millions of grant
proposals, all categorized into various "mission silos" that research
organization is built around. Not a "data scientist" job.

Analyze multi-lingual news stories to build a real-time alert system for
conflict analysts. Not a "data scientist" job.

Building a tool that can scan multi-spectral aerial imagery and automatically
extrapolate man-made structures from natural, catalog all of the different
vehicle makes and models, and generate a predictive model of commuting
patterns, or make recommendations for housing development based on perceived
socio-economic conditions? Not a data-scientist job.

Collecting information on who propositions who from a dating web site,
normalizing the data for population and writing a report on the findings?
_That's_ a "data scientist's" job.

It's not that that kind of work isn't valuable, only that there are so many
other kinds of things that involve what might intuitively be called "data
science" that calling just the one discipline "data science" is doing a
disservice to what should be an amazing discipline -- part Computer Scientist,
Part Analyst.

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tel
As someone who's statistically inclined, I am not looking forward to this.

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rrrrtttt
How do you call the phenomenon that leads statisticians to rename themselves
"data scientists"? I propose the Freud-inspired "science envy".

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eigenvector
Is there a type of science that does not involve data?

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rm999
This is a pretty fluffed up article that missed the wave of "data scientists
are awesome" articles last year.

But I think it's important to not underestimate the shift that has been
happening. The race to automate tasks has always been accelerating, but it hit
an inflection point a few years ago when mainstream business people realized
what current technology can achieve. Pretty much every industry I've seen has
been or can be drastically transformed by better data management and
predictive analytics.

It's going to affect all of us, so I think it's worth following closely.

~~~
koenhavlik
I agree. The article was meant to be a high-level introduction to the
phenomenon for the Dutch audience. They missed that wave. I had know idea it
was going to end up here:) Apparently a controversial title can still trigger
lingering emotions:) Most people still don't seem to have a clue what is
possible, though.

IMO something is accelerating/changing and we hit an inflection point. It does
help to give it a denominator. It's human, not just marketing. I'm sure one
time people thought compsci and software engineering were redundant or
pretentious. I'm still ambivalent about the name data scientist.

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SatvikBeri
Data Science and "Big Data" have done a _really_ good job of marketing
themselves. As a result, people recognize that these roles are valuable, Data
Scientists get paid & treated well, and it tends to work out well for
everyone.

What can we learn that we can apply to technology in general? I feel like
"programmers" and "IT" tend to be undervalued while Data Science tends to be
accurately or even overvalued.

~~~
46Bit
> What can we learn that we can apply to technology in general? I feel like
> "programmers" and "IT" tend to be undervalued while Data Science tends to be
> accurately or even overvalued.

Given that Data Scientist is just a sexier rephrasing of Analyst, my
suggestion would be to retitle Programmers as Computational Engineers. Or use
Lisp.

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bthomas
If anyone from the site reading this, didn't work on my nexus galaxy. A dumb
share popover took up the whole screen and didn't scroll away.

~~~
wkneepkens
thanks, DiggDigg issue catching us out :S

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ianstallings
Delusional thoughts from fantasy island.

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jcampbell1
It is confused to give data science much credit for the success of Netflix.
Netflix succeeded because of content, wide platform availability, and solid
marketing. They ran a million dollar prize contest that ultimately did nothing
for their code base, but did generate a lot of positive press.

------
csexton
But who are the new ninjas?

~~~
misiti3780
"growth hackers", whatever that means

~~~
xradionut
Sounds like someone who prunes trees and shrubs.

"Did some growth hacking on the hedge funds, bagged it, 100% organic
product..."

