Don’t get me wrong. As a marketer, I love that my job is storytelling. But if I knew then what I know now, I would have definitely paid much more attention in my college statistics class.
It’s more than just a question of supply and demand. Yes, data scientists are in high demand everywhere right now and the need for more is only growing. Across every industry – from Financial Services to CPG to Technology – companies believe, with good evidence, that these data savants are the key to unlocking the value of big data, and are offering lucrative salaries as a result. Data Science programs are also showing up at every major university around the country, as each institution feverishly develops their own curriculums and faculty to provide the skills necessary for a competitive marketplace.
Then there’s the hype. Back in 2012, HBR called data scientists the sexiest job of the 21st century. Now, while some might consider this headline hyperbolic, there’s no question that the amount of press this relatively new job title has received over the last few years is quantifiably high. It’s no wonder that people with backgrounds in Physics, Computer Science and Economics are now rebranding themselves as data scientists.
But let’s look beyond the two factors of economics and relative glamor. What really makes me wish I could be a data scientist right now is that the massive investments that companies have made over the last decade are finally starting to pay off – the technology is finally catching up with the ambition. We have reached a point where systems and software can efficiently manage massive amounts of data, and allow for processing speeds that give creative minds the ability to get answers to questions as fast as they can think of them. What we once called data analysis is evolving into something previously unseen. So while many people focus on the data side of the equation, it’s the science that has all the magic for me.
Given a high level of autonomy, a scientist’s job is to explore and discover. Faced with a problem, they develop hypotheses and test them, identifying controls and variables that eliminate possibilities until there’s one credible outcome. They play. They connect the dots. And they work with a network of other scientists to share what they have found to both challenge and improve their results. And because they operate within the great unknown, where they end up could be completely different from their original hypothesis. That sounds tremendously exciting to me.
With the advent of new technologies that can tame semi-structured and unstructured data, that can combine offline and online data in a way that keeps information secure and most importantly anonymized, we are entering a time in history where businesses can provide a safe environment that allows data scientists to work at the speed of play. They don’t have to sit on their hands waiting for the machines to compute. Now they can follow a train of thought or an idea to a conclusion quickly, without sacrificing accuracy. And who knows what creative outcomes they will discover – some that may fundamentally change the way businesses look at using their data to transform their business through meaningful customer engagement, and likely improving the lives of their customers.
A few years ago I was struck by an exhibit I saw at Internet Week called Digital Archeology. Curated by Story Worldwide in partnership with Google, they “showcased a selection of groundbreaking websites from the early days of the web, congruously displayed on the hardware and software they were designed on and for.” Besides waxing nostalgic in front of the pristinely preserved Apple IIC on display, I was impressed by how many of those early sites were just forms of creative expression. These early groups challenged the industry’s approach to what qualified as an interactive experience, introduced animated websites and generally pushed the boundaries of the medium. Before you can monetize it, before you can replicate it, put an evolving technology in the hands of people who can play with it in the right environment, and you might uncover new applications that you couldn’t have previously imagined. And fortunately, the part of human capacity that enables creative scientific discovery can never be made obsolete.
So in 20 years time, if we curated an exhibit on Data Science Archeology, perhaps we will look back and tell the stories of the crazy algorithms or predictive models that changed the way we worked with data forever. It will certainly make for a great story.