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'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."
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'Data Science' Is Dead

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  • Maybe (Score:5, Insightful)

    by stephencrane ( 771345 ) on Wednesday March 05, 2014 @11:47AM (#46408661)
    But this general domain in the realm of contemporary giant data sets is the basic science research of our times. 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.
  • How appropriate (Score:5, Insightful)

    by Micklat ( 986895 ) on Wednesday March 05, 2014 @11:50AM (#46408687)

    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.

  • by sega_sai ( 2124128 ) on Wednesday March 05, 2014 @11:51AM (#46408699)
    The author of this piece clearly have never done actual science, as confirmed by his resume, and his opinions on what science is and that somehow some observational sciences are "soft" are very questionable at best.
  • 100% disagree (Score:5, Insightful)

    by netsavior ( 627338 ) on Wednesday March 05, 2014 @11:53AM (#46408719)
    In my career I have worked for boring banks and boring monolithic enterprise software giants.

    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.
  • Buzzwords (Score:5, Insightful)

    by SpankiMonki ( 3493987 ) on Wednesday March 05, 2014 @12:09PM (#46408901)
    Since "Data Science" is dead, do we go back to using the old buzzwords? Or do we have to wait until some marketing MBA whiz-kid comes up with a sexy new word for "Analyst"?
  • by iggymanz ( 596061 ) on Wednesday March 05, 2014 @12:23PM (#46409071)

    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.

  • by Sockatume ( 732728 ) on Wednesday March 05, 2014 @12:26PM (#46409111)

    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

  • by ZahrGnosis ( 66741 ) on Wednesday March 05, 2014 @12:28PM (#46409145) Homepage

    "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.

Q: How many IBM CPU's does it take to execute a job? A: Four; three to hold it down, and one to rip its head off.