'Data Science' Is Dead 139
Nerval's Lobster writes "If you're going to make up a cool-sounding job title for yourself, 'Data Scientist' seems to fit the bill. When you put 'Data Scientist' on your resume, recruiters perk up, don't they? Go to the Strata conference and look on the jobs board — every company wants to hire Data Scientists. Time to jump aboard that bandwagon, right? Wrong, argues Miko Matsumura in a new column. 'Not only is Data Science not a science, it's not even a good job prospect,' he writes. 'Companies continue to burn millions of dollars to collect and gamely pick through the data under respective roofs. What's the time-to-value of the average "Big Data" project? How about "Never?"' After the 'Big Data' buzz cools a bit, he argues, it will be clear to everyone that 'Data Science' is dead and the job function of 'Data Scientist' will have jumped the shark."
data scientist (Score:5, Informative)
Call yourself a statistician or database engineer and I promise there are still jobs around. And contrary to the summary, they are highly valuable jobs.
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indeed, and who cares if someday this alleged "fad" goes away, "get it while the gettings good. and then get out!"
Whooaaaa!!! Hold on there, big boy! (Score:3)
You can't do that, unless you can figure out how to make and file TWO resumes. Different ones, I mean.
Man, these data scientists are all pipe dreams.
Re:Whooaaaa!!! Hold on there, big boy! (Score:5, Insightful)
no pipe dream, my employer has those people, making big money
and what's this nonsense and misconceptions about resumes you have between your ears?
in my career, I've held engineer, science and IT positions. I have "IT-flavored" version of my resume for when I'm seeking an IT focused type job, "engineering-flavored" one, etc. All the resumes are true, no innacuracies and all experience can be verified by contacting previous employers or talking to former coworkers or reference. So the point is of course you can have different versions of your resume with different focus on duties and skills.
Re:Whooaaaa!!! Hold on there, big boy! (Score:5, Informative)
You should have a different resume for each job you apply for......
Keep a master resume with all of your details. When you apply for a job, copy the master and pare it down to the information most relevant to the job you are applying for. Then edit the result so that you look like the perfect candidate.....update project descriptions to emphasize the same buzzwords in the job listing, etc.
If you only have one resume that you blast out to a ton of different job listings and they'll probably focus on the projects that are meaningless to their situation and weed you out more often than not.
Oh, and BI (business intelligence) is still going strong at the company I work for......(not my area, but there's still tons of work under that label).
Where have you been? (Score:3)
You can't do that, unless you can figure out how to make and file TWO resumes. Different ones, I mean.
Man, these data scientists are all pipe dreams.
Well, it is not rocket science to have more than one resume. You have one work history, but you will use more than one resume format to present it in different (but veritable) ways according to the situation.
See, you are supposed to have multiple versions of your resume (which are true and accurate of course) according to job postings or fields of concentration. If you have a varied work experience, or you are contemplating lateral moves, this is a must.
Consider the following situation I had to deal wi
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and you need a college degree loaded with theory in construction that is more for high level design but not for the hands on doing the work part and HR does not like tech / trades schools that do teach the hands on doing the work part.
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As the author of the article, I'm happy to encourage people to call themselves statisticians, database engineers, etc. These roles are definitely in demand and will never go away when the bubble for "data scientists" pop.
I'm just concerned about the recent spate of large companies trying to hire data scientists to "save" their expensive big data projects that arent producing actionable insight. Those jobs are a dead end.
More DICE.COM market "insight" ?? (Score:2, Interesting)
I don't know about you but I am sick and tired of DICE's attempts to
channel and steer the employment market through astroturf postings
to Slashdot, which they also happen to own. Most of what the talking-heads
at DICE churn out regarding employment is simply untrue. Not 'not-the-truth'
as that they don't know any better, but telling lies as in spreading deliberately
misleading information, as in telling a mean-spirited lie.
DICE is not a platform for you and me to find lucrative jobs. Instead it is the
other way
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Indeed, the job of doing serious data analysis is not new, 'data science' is really only a temporarily independent field while we try and sort out some of the technical problems that arise from working with large datasets. Once solutions for large datasets become mainstream, reliable and agreed upon (and inexpensively vendor bought) we'll go back to just having scientists who are specialized in whatever area.
And that's perfectly alright.
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Call yourself a statistician or database engineer and I promise there are still jobs around. And contrary to the summary, they are highly valuable jobs.
Is a data scientist really a pseudonym for SEO analyst? (SEO = Search Every Option or Search Engine Organization or that other one, ending in Optimisation)
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lol isnt it "Principal Engineer"? But point taken, it seems like "Scientist" is being bandied about quite a bit by just about anyone.
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To me, a research scientist used to be the person that did experiments, made notes, maintained a log book, drew conclusions, and published papers.
Now, when I see the job adverts, the research scientist is now the one writing research grant applications, visiting sponsors, making presentations at world conferences, leading a team, drawing up budget requests.
Data scientist seems to a combination of AI programmer and database programmer.
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"To me, a research scientist used to be the person that did experiments, made notes, maintained a log book, drew conclusions, and published papers."
Which is what a data scientist does, by the way.
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Scientist is an occupation, not a title ... a data scientist is mostly just misnamed, regardless of PhD.
Science is a philosophy, not a vocation (Score:3)
A Phd is valuable in that it demonstrates that you can research a given topic in an academic setting and formally communic
Maybe (Score:5, Insightful)
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I hold a Master's in EE specializing in Information Theory. That seems to sound like a "data scientist", but I've never met anyone that presented themselves as one.
Maybe I should modify my resume to include my years of experience as a "nocturnal ergonomics specialist" or "cinematic purveyor".
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Lot's of people are up in arms here thinking im against data, queries or even information in general. LOL
I think guys like you are going to be in serious demand, and yes data is piling up hugely. The winning organizations will have serious, smart and well trained people who know how to manage it.
And yes, I think "nocturnal ergonomics specialist" is the career of the future =)
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To say that 'data scientist' roles are dead in the near future based on a ROI analysis is to suggest that all these huge data sets aren't likely to pay off for a corp in the near future. And that doesn't sound right at all.
I think what's really going on here is that lots of organizations have jumped on the Big Data bandwagon expecting that it will be easy, and hired lots of people who don't really know what they're doing (because they also saw an opportunity). There's lots of value in large corpuses of unstructured data, but teasing it out requires more than just a desire and some computing resources. As the field matures and builds up a well-known set of techniques which can be packaged up and on which people can easily be t
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I'm not against big data sets.
I've just noted that a lot of big data projects hyped by vendors are misguided, and that there will be very large and visible failures coming up. this is just a bubble and the "data science" guys will be in trouble.
The long term prognosis for large scale data analysis is good, and machine learning will probably yield good results. Also the pendulum will swing back to structured data.
Strong claim (Score:3, Funny)
That's a very strong claim, I'll need to consult my Data Scientist to see if it actually fits the data.
How appropriate (Score:5, Insightful)
No data has been cited during the creation of that blog post.
Opinion is fine, but when the observations are so weeping, just a little bit of substantiation is nice to have.
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LOL I really like "weeping" it's pretty awesome in this context.
FUD (Score:5, Funny)
1) Write a Slashdot article
2) ???
3) Profit!
Re:FUD (Score:5, Informative)
Science creates knowledge via controlled experiments
Which is false. Science checks hypotheses and tries to prove them, or makes repeated experiments that show the failure to disprove them.
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I think astronomers will be very surprised to learn that they aren't scientists.
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Astronomers due controlled experiments
Just so you know.
On Science, Actuaries, and FUD (Score:5, Insightful)
"Science" lacks a robust definition, but clearly the OP's definition is overly simplistic and narrow. Stephen Hawking has a lecture somewhere (found it: http://www.hawking.org.uk/the-origin-of-the-universe.html) where he talks about the idea of the "positivist" approach defined on the ability to predict outcomes, and I like to apply that definition to Science (Hawking doesn't, directly, but it's sort of an underlying theme). That is, Science becomes the observation and experimentation required to form predictions or cause changes in predicted outcomes.
So Social Science can be a science in so far as it actually informs usefully on how people will behave or provides useful ways to affect and improve the behavior or state of society's future. Computer science is a science insofar as it is required to make computers function as expected (as predicted) -- if you want something to perform faster, you must do the research and experimentation to cause the outcome to be faster. Even archaeology can be a science by this definition in that discoveries are added to a general model of the past that predicted all sorts of things -- ancient society's behavior, glaciation, geological events... "predict" may be a stretch there (except when archaeological finds help predict the future), but in this case the method of building a model of how the world worked based on observation to describe and generalize behavior (of the earth, of ancient religions, or what have you) is a form of prediction; it's just after the fact.
Data Science is very much science in this form; the job of a data scientist is almost universally to predict what the data will say about the future given what it has said in the past. This is invaluable to businesses and while the name may fall into disfavor, in the same way "actuary" which means something very similar already has, the abuse in this article is unwarranted, unfounded, and inaccurate. I will only agree that many who sport the "Data Science" moniker may not actually be doing science by any definition, but that's the individual's fault, not the concept's.
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thanks for your thoughtful post. I agree actually that the word "Science" is a bit elusive in definition, and that certainly just because a field of inquiry is not a science by one definition does not mean it's without value.
Also, I accept that there are multiple definitions of the word and some may include fields like Computer Science and Social Science, which of course are all legitimate fields of inquiry.
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I think your post makes good points mostly, but I have to ask, since when did the phrase "actuary" fall in to disfavor, and when was anyone going to tell me?
Signed,
A P&C actuary
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Thanks fort he nice replies... "disfavor" was probably strong, in terms of "Actuary", but I meant it more in terms of not having a negative connotation, just not having a rock-star or very popular buzz-word sort of connotation that "Data Scientist" seems to have now. I grew up wanting to be an actuary, curiously -- my father was one -- I got the math degree, I just wandered off into database work, but I do actually see our jobs as very similar. I think actuaries still come in as some of the "best" jobs an
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Re:FUD (Score:4, Funny)
According to this guy, Mathematics is not a science because you don't conduct experiments.
He's obviously wrong. Try this experiment - it proves addition:
# python
# print 1+1
# 2
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According to this guy, Mathematics is not a science because you don't conduct experiments. The key error is this:
Science creates knowledge via controlled experiments
Which is false. Science checks hypotheses and tries to prove them, or makes repeated experiments that show the failure to disprove them.
It's not just in mathematics that this is false. Controlled experiments are one of doing science. By the definition of the author of the original article, combing through existing genomic data to identify SNPs possibly associated with disease isn't science. By his definition, identifying comets or asteroids or planetoids by examining collections of astronomical images taken by others isn't science. By his definition, the work of theoretical physicists who do not perform experiments isn't science. By his def
Not-scientist about science (Score:5, Insightful)
Re:Not-scientist about science (Score:4, Insightful)
I especially liked the bit where he described the following as "buzzworld-filled", then launched into the unsupported assertion that people doing this aren't doing science:
develop and investigate hypotheses, structure experiments, and build mathematical models
agreed... Re:Not-scientist about science (Score:3)
From TFA (emphasis added):
Yes, by this standard, Astronomy and Social Sciences are also not sciences. I have no idea what Computer Science is, but no, it’s not a science either.
*sigh* RTFA was a waste of time.
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"Big Data is like teenage sex: Everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it too." from http://www.linkedin.com/groups/Big-Data-is-like-teenage-1814785.S.5796554060756692996
While I won't argue if 'Data Scientist' is or is not a bullshit title, the fact remains that a lot of people just don't understand what they (or someone else) mean when they say things like 'Big Data' or, worse, 'put it in the cloud'. I think the
Where's the argument? (Score:2)
shouldn't there be a link to an article or a more in-depth argument presented than just "b/c i think so"? Perhaps, say, explain who the hell Miko Matsumura is, or provide greater context?
I get it though, nobody reads the articles on slashdot... :/
100% disagree (Score:5, Insightful)
If there is one thing I know for certain it is that big enterprise will ALWAYS have a huge appetite for quantification of data. It almost doesn't matter if it actually does anything for you, executives at giant corporations have to DO SOMETHING have to REVIEW SOMETHING. Large scale data aggregation and reporting (one of the many things that go by "big data") might not have sciency uses, but any time a V level can provide a C level with "something" that says "We are doing stuff" there will be a huge market for it.
Basically what I am saying is, even if "Big Data" is nothing but a placebo, like say "HR Training", "Wellness programs", "performance reviews" or "teambuilding" it is a permanent fixture in the big, boring, high paying, stable job providing corporate world.
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100% agree (with your post).
The argument made in article is ridiculous, but even if we grant it and companies suddenly lose interest in their data, the skills used to analyze it can easily be rebadged and applied in other fields. Not like all the large scale infrastructure, data management, and algorithm skills are only specifically applicable in the "big data" realm, that's just the most profitable place to apply them at the moment.
IT isn't a job where you learn a skill then make money from it forever. You
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Yep, managers and bosses love widget counting even if your business has little to do with widget production. You'll always have a job if you can give your boss some table or graph to wave around in meetings, meaningless or not; kept me employed for 20 years.
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fully agree, data and big data will always have a home, and corporate behavior is very much how you describe.
Just thinking that the pendulum is going too far from structured data and that people are getting a bit ahead of themselves with respect to vendor hype in this area.
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A "Devops Engineer" is an engineer working on the operations for a development environment. In other words, he's the guy who says "hey, our team needs better communications with the QA team, so let's set up a proper ticketing system, rather than just emailing problem reports".
Chuckle all you like, but ideally every dev team would have such a person. We've all heard the horror stories [worsethanfailure.com] of developers using Word for source code, not keeping backups, and relying on a wall of Post-It notes for bug tracking.
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Who is this guy? (Score:1)
Seriously. Who is this guy and why does his opinion matter? Either he has credentials or he backs up what he says with some evidence. Neither seems to be the case.
TFA is BS (Score:5, Interesting)
Unfortunately, unless this is structured data, you will be subjected to the data equivalent of dumpster diving. But surfacing insight from a rotting pile of enterprise data is a ghastly process—at best.
Sounds like this Miko Matsumura has no idea how successful Big Data projects actually work.
To refine his analogy, unstructured data is much like processing recyclables. Everything that might possibly be good gets thrown into a large bin, and several sorting processes run to extract individual relevant (though messy) pieces. While those pieces alone aren't pure enough to be useful, there's enough meaningful information in them that statistical analysis can separate the good from the bad, and that's where the insight comes from.
With a typical RDBMS, insight is readily apparent. A hypothesis that 75% of a user's purchases were widgets is simple to verify. In a non-relational database, as is often used in Big Data projects, that would be an inefficient computation (though it can be done). Rather, those databases are more aligned to produce a whole list of correlations between user demographics and purchasing habits, showing for example that users who buy widgets have often already bought foo bars. The "Data Scientist" didn't have to ever look specifically at statistics for widgets or foo bars, but the correlation is presented in a nice and accessible form, gleaned from millions or billions of independent data points.
Miko Matsumura is a Vice President at Hazelcast, an open source in-memory data grid company.
This is a SlashBI article written by executives for executives, with little basis in fact. Lovely.
Buzzwords (Score:5, Insightful)
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hardly dead, analytics and data analysis are still huge and growing field with high salaries for those with formal training. my employer has department of such people.
Computer Scientists in lab coats (Score:3)
The term reminds me of "Computer Scientist". I remember a TV commercial from the 80s for a digital watch that mimicked analog watches. The announcer would declare that the watch had been designed by "computer scientists" while an actor was displayed wearing a lab coat and looking at the watch under a microscope. The first time I saw it I was afflicted with fits of laughter.
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Lets get rid off the "Dexter Lab Coat" stereotype.
Many people, kids or adults doesn't really like to use "lab coats" & prefer to use the clothing they use on the school or street.
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.
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You do realize that there are practical reasons to wear a lab coat and it's not just a fashion statement?
You gotta be kidding me... (Score:2)
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Data Scientist, may sound Statistics to some of us, and Data Base related to others. Maybe you are right, and we are wrong.
Could you provide a link to a web site, where Data Science could be described ?
I do believe that concepts like Data Statistics, Relational Algebra, SQL, could be consider part of a Data Science diploma, but, none of this concepts should be consider individually Data Science, by themselves.
Maybe, a new proposal for a Data Science diploma, could be created from this post.
Thanks.
Data scientist is like an IT janitor (Score:5, Interesting)
90% of what a data science expert do is what people like to call data-juijitso (data reconfiguration). Which basically means getting data out of your RMDBs, SAP, Twitter, Facebook, random text (.csv, etc) file dumps, random Excel/Word Files and legacy databases and into some place you can actually generate conclusions from (like inside a HDFS Hadoop cluster). Plus during this process you need to normalize all your data so you can apply the same algorithm no matter where the data came from.
All this means is that you will spend countless hours trying to connect to the client legacy stuff and then countless hours trying to get the data out (without impacting production systems!), so you can then spend countless hours formatting this data around to be able to spend countless hours trying to get this data into your Big Data(tm) solution so you can finally run some algorithms and create results. Now multiply all that by the number of different kinds of databases the client has and you get the idea.
As an IT professional you really do not want to work in this field. No organization keep its data in a clean uniform way, data scientist is like an IT janitor.
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So, just basic BI and data warehousing, but without the lessons learned in the past?
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Well technically the data science part is what you do after the data reconfiguration, but most people just use some kind of tool for doing that, so it is also very boring (you have to learn the tool and configure it to your data format).
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Yeah, that's the way I see those guys get treated.
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Basically yes.
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That's DBA work, not Data Scientist work.
Try again.
It's data, and it's a science, so... (Score:2)
Um, I'm a calibration scientist. My job is to pick through data and look for errors, which I then correct. I'm a scientist, not an engineer, because the data and its errors are from real physical processes. (The data I work with comes from multispectral satellite instruments.)
If I can't call myself a 'Data scientist' on a resume, what term should I use? Approximately zero jobs are available for a 'Calibration scientist'.
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As an addendum, the day I put 'engineer' on my resume is the day my career is over. My degree is in theoretical physics. I have zero engineering background or training. I'm a scientist, and I can't compete with engineers for engineering jobs, nor do I want to. I've spent decades keeping the word 'engineer' off my job title and resume despite stupid managers trying to tack it on.
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I once had to fight to keep 'software engineer' off my job title.
I kept explaining that I was not an engineer, that engineering was a specific regulated profession, and that to call me an engineer would be illegal and incorrect.
It took a long time for our Personnel Management Engineers (HR) and the VP (who thought it sounded cool) to understand why it had to be otherwise.
In some cases, companies like it because it sounds cool. But they have no idea that you can't simply call yourself an engineer any more t
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IN some sites it's a crime to be called engineer if you don't have a PE Cert.... or drive a train.
As it should be,
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Its a problem with the computer sciences in general. They keep cannibalizing terms and changing he meaning, like engineer and scientist.
I am an aerospace engineer that specialized in fluid mechanics. Guess what? I know more about computer programming, linux, unix, memory architectures, compiling environments, programming language, etc. than most computer "scientists/engineers".
But I need to know about all those things because I take the theory and discretize it for solution on whatever architecture
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It does get confusing especially with job adverts... I see titles like "software consultant", "freelancer", "programmer" (for visualisation work), "scientific programmer" (for parallel processing research into fluid dynamics), member of technical staff, test engineer, compiler engineer, software engineer, senior software engineer, principal engineer, architect, as well as data scientist (with "Big Data", R, Java/Hadoop and Reduction).
The main different between a programmer and an engineer was that the engin
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really? Most ?
Doubtful
"computer science degrees are simply collections of network certs."
No, they aren't
I don't think you know what a computer scientist is or does.
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...and the only place that will hire me with that description is the place I'm working at now. Very few private subcontractors are flying remote sensing satellites.
Theory vs Real World (Score:1)
There are several subjects disscused in this post.
* First, wheter there is a "Data Science" career. Since, I discover how math can be applied to handle data, when learnt Relational Algebra, & Data Normalization, in Collegue, I realized there could be a "Data Science" school diploma. And include OLAP, Key-Value, NoSQL, Statistics data handling, with their respective math theorical support.
* Second, like any other career, there is a diference in how is taught in school, & how is applied in business.
Wh
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this is a good and rational perspective. I think if there is a formalization of the concept of Data Science including academic certification, maybe it could become more credible.
definition (never gets old) (Score:1)
Big Data: the belief that as the size of a pile of shit increases, the probability of finding a pony approaches one.
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Y'know, once your pile covers a large enough area of land, there's bound to be a pony in there somewhere.
Synergized leverage of 5,000 mile view (Score:2)
or
Shut up, and code.
Ask UnderArmor (Score:2)
UA, a Baltimore company hosts data science meetups. Why? Because UA is data science driven. All company decisions are made based on data. So it seems that the OP is complete BS, because it is effectively creating results, and those results are highly successful for a major corporation.
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It's called a counter example.
Another 140 character or less take (Score:2)
OK, I wasn't going after "data science" specifically, but ad algos and how my twitter feed has become a cesspool of mental masturbation for ad algorithm people, which is the "killer app" for "big data":
1. PhD invents fantastic ad algo. 2. Guy sees ad on iPhone, takes EBT card there. 1. PhD applies for EBT card. #OneTwoPunch [twitter.com]
Wow, I can't believe I just typed that many buzzwords in a Slashdot post; but at least I had a reason and put most of them in quotes... dammit. "algos". Anyway, I wonder if ever
Calling yourself a 'scientist' w/out a doctorate? (Score:2)
.
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Why? Calling your self a Doctor without one would be, but not scientist.
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Data Scientists are this bubble's Web Masters (Score:3, Interesting)
I've been working with big data since before it was a term and currently run a scientific software company that touches on many aspects of "data science". Many of my colleagues also work in the field. I've seen many fads come and go. Data Science as a profession is one of those.
Most people who call themselves data scientists are really just doing "big data" processing using tools such as Hadoop. They are delivering results to managers who have jumped on the big data band wagon and, not knowing any better, have asked for these skills. In 99% of the cases, the processing is simply haphazardly looking for patterns or running basic statistics on data that really isn't that big. However, there is a lot of low hanging fruit in data that hasn't been analyzed before and most practitioners who've suddenly become data analysis experts are rewarded for trivial findings. A tiny bit of statistics, programming, and data presentation skills go a long way.
Compare this to the Web Masters of the late 1990s. The Web was new and managers knew that they needed Web sites. HTML and CGI were techie things but also fairly easy to learn. A group of people quickly figured out that they could be very important to a company by doing very little work and created the position of Web Master. A tiny bit of programming, sys admin, and design skills went a long way.
Web Masters disappeared when IT departments realized that you actually needed real software developers, real designers, and real sys admins to run a corporate Web site. Sure, the bar is still low, but expertise beyond a 'For Dummies' book is still needed. And, few people can be experts in each area, hence the need for teams.
Real data science has actually been around for a long time. Statisticians and data analysts have been performing this role for decades and have built up a lot of rigor around it. It a tough skill set to develop, but a very useful one to have. "Big Data" distracted people a bit and let the current generation of data scientists jump in and pretend everything was new and we could throw out the old methods. As the field evolves, data science will necessarily transition back to the experts (statisticians) and become a team effort that includes people skilled in programming, IT, and the target domain (analysts).
That said, there's good money to be made right now, so if you have Web Master on your resume, you might as well be a data scientist while you can. ;)
-Chris
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Somebody better tell leading research universities (Score:1)
Because they're expanding Data Science.
Hype about Hype (Score:1)
I've worked with a lot of top-notch people that would likely be labeled as 'data scientists' and I can tell you that:
1)
There still seems to be plenty of data in science (Score:1)
Our current-generation workhorse instruments here at the telescope [naoj.org] spit out tens of gigabytes per night as it is. The new camera we've been commissioning produces something like two gigabytes per exposure. And oh, yes, that data has to be archived, reduced, analyzed, etc., using things like IRAF or IDL. (Not my job.)
What's the difference between a data scientist and (Score:1)
The End of Data Science As We Know It (Score:2)
Collect data, analyze data, ignore data (Score:1)
I was called a tool for saying this (Score:2)
But after saying this I had a bunch of people jump all over me screaming that I didn't have a clue. About the only intelligent comment was someone as