Blog Post

Graphic proof of big demand for big data talent

More (graphic) evidence that “big data” skills are very much in demand. Job postings for big data jobs have skyrocketed since January 2010. Just take a look at this hockey stick of big data job listings, courtesy of

And, here’s the hockey stick for the more specific “data scientist” job title.

Feature photo courtesy of Flickr user *n3wjack’s world in pixels

11 Responses to “Graphic proof of big demand for big data talent”

  1. While “big data” skills are undoubtedly in high demand, these graphs have more to do with popularity of given terminology rather than the underlying skills. Just like “social media” has existed long before Facebook and Twitter (it just wasn’t called that), the concept of using massively scalable distributed systems for processing lots of data in parallel isn’t exactly new.

    To see my point, go to Google Trends, and enter

    “big data”, hadoop

    You will see the “hadoop” trend emerging a few years before people started saying “big data” a lot.,+hadoop&ctab=0&geo=all&date=all&sort=0

    • Agree, iTrend.
      And what we need is this type of skill set..a blend of right and left brain thinking in an individual, who looks @ ‘big data’ from an everyday human’s perspective. A generalist in common sense that also ‘gets’ the irrationality in behavior based on context and/or poor/misinterpreted content.

      The key is to develop people to think in the right context of the everyday human, simplify the explanation (interpret/translate in everyday language), and deliver it via accessible ‘communication channels’ (new word ~ commections), so it can be shared, agreed and debated on. Everybody wins because the dialogue itself will develop, encourage and inspire ppl to think.un think and eventually do.something.different.

      Ongoing engagement. Development improves. Simplification improves.Commection ‘consumption’ and better educated opinion/action continues…

      Credit to J Collins* …and the flywheel of continual, self-fulfilling good for everyday ppl, big data actions happens, while doomloop bad for everyday ppl, big data slows. That, my friends, is a commected world for everyday ppl who have access on the tip of their their brain ;) we hope first, rather than their tongue :(
      (sorry 4 any typos, couldn’t reread on my iphone easily;)

  2. reynardloki

    The ongoing dialogue between the digital and physical worlds provides the backdrop for Data Deluge, an exhibition that presents a selection of sculpture, furniture, painting, photography, video, sound and works on paper by artists who shape Web-based and software-generated data into art. The exhibition, curated by Rachel Gugelberger and Reynard Loki, takes its name from the title of a 2010 special report published by The Economist that observed the emergence of “a new kind of professional…the data scientist, who combines the skills of software programmer, statistician and storyteller/artist to extract the nuggets of gold hidden under mountains of data.”

    Data Deluge features work by Rebeca Bollinger, Jon Brunberg, Anthony Discenza, Hans Haacke, Scott Hug, Loren Madsen, Michael Najjar and Adrien Segal that communicates a wide range of concerns, from the development of the world’s stock market indices to terrorist-related deaths, from national water use statistics to male responses to photographs of women in online chat groups. Newly created commissions by Jennifer Dalton, Roberto Pugliese and Anna Von Mertens tap into the unique characteristics of Texas, and Marfa in particular, with a sensitivity to minimalist forms, local weather conditions, the tourism industry and oil.

    Mar 2-Jul 8, 2012

    Data Deluge
    Opening: Friday, 2 March, 6–8pm
    Community Dinner, 8:30pm at the Capri
    Luke R. DuBois with Bora Yoon Performance, 9:30pm at the Capri
    Exhibition Walk-Thru with the Artists, Saturday, 3 March, 2pm
    P.O. Box 1661
    108 East San Antonio Street
    Marfa, Texas 79843
    T 432.729.3600
    F 432.729.3606

  3. Marshall Kirkpatrick

    This is good stuff for sure, but it brings to mind a conversation I was having a few months ago with a well-respected data scientist. I was talking about trying to hire a hot designer and he said, “yeah for all the hype is data scientists get, it’s still probably harder to hire a great designer in-house.”. In other words, demand for those skills remains far, far higher and the supply of design skills can’t meet the demand. I got a great designer, but probably only because our product is unusually awesome!

  4. You are witnessing a new business-buzzword fad. This wasn’t started by the scientists but by the consultancy ecosystem.

    We used to be called “analytic scientist”, “predictive modeler”, “computational scientist” or even the fusty old “statistician”. (Me I used to be called “physicist”).

    BTW, the actual statistics community has had most of the real scientific and computational insights, often decades ago.

    • I agree with this comment. The statisticians (and machine learning experts) have figured out the right perspective on mining large data sets. It is tricky and very specialized. I worry that many of the supposed talent out there is not as experienced as one would desire to really figure out what is in these data sets.

      Those who are putting numbers on the sports spreads in Vegas are likely where the strongest ability can be found.