Hot or Not?
In 2012, Harvard Business Review called Data Science:
"the sexiest job of the 21st century."
They cited the complex skill-set, high demand, and scarcity of data scientists as some of the drivers of this trend. Contrast that with a recent Forbes article whose take-home point is that the sexy days of data science are numbered. They claim that automation and a new crop of professionally-trained candidates will fundamentally change the landscape of this field.
"...the data scientist shortage has been overblown."
These two articles certainly are not the only ones of their kind. And, as I read through article after article, I started to feel like my profession, the one I have loved and worked in for nearly a decade now, was suddenly the subject of a tabloid “Hot or Not” list. As this debate rages on, we in the data science community are hard at work, doing what we love to do: being curious, learning and applying new skills, asking new questions, finding answers. The answer to the question of whether Data Scientists are “hot or not” is irrelevant. I’ll let you in on a little secret:
we're not in it for the sex appeal.
Why do we choose this as a career?
I recently reached out to a dozen of my colleagues in the data science community to ask them why they choose to be in this profession. It probably won’t come as a shock that not a single one of them said they did it because it was “sexy.” So, what are the reasons? Why do we choose this career? Here’s a summary of what I heard from my colleagues, coupled with my own reasons for loving my job.
We love to help people make better decisions. Nothing is more cringe-worthy to a Data Scientist than hearing that a company made a big, expensive decision without any data to guide them.
We are creative. We love making something new out of nothing. My colleague, Nick Ryberg, said it best, “There’s a really nice intersection between the 5-year-old inside of me who, more than anything, simply loves connecting lego blocks in new and interesting ways.”
We are endlessly curious. We feel compelled to explore the unknown and to push the boundaries of what we currently understand. This curiosity doesn’t stop when we’ve answered a question - each answer leads to a new set of follow-up questions.
We are lifelong learners. There is always a new language, tool, or technique to learn. The rise of free or low-cost online learning communities has created a virtual playground for us, and we’re taking full advantage of it.
In my opinion, there will always be a high demand for Data Scientists, although likely not in their current form. To say otherwise is to assume that we will someday know everything, that we will stop learning and growing, and that we will lose our curiosity. I’m much more optimistic than that. Here’s why:
The volume, complexity, and breadth of data is not decreasing. In fact, it is exponentially increasing.
There will always be new questions that need to be answered. As business gets more complex and competition grows, so does our need for answers. Additionally, future work builds off of the work we’re doing today - that is the nature of the scientific method.
Automation has always been present. Truly innovative people use technology and automation to their advantage. Automation can either be viewed as a threat or as a tool to help us accomplish even more. The complex work we can tackle today is possible because technology and automation have freed up time and resources that can be deployed onto new, complex problems.
There will always be something new to learn. Data Scientists are not the type of people who rest on their laurels. Rather, the skills and knowledge that we have today are merely a foundation for the skills we’ll learn next.
In the end, the question of whether the field of data science is sexy is irrelevant. We don’t do this job for the sex appeal. We do it because it’s in our nature to ask, explore, create, and learn. Call me an optimist, but I believe there will always be a huge need for that - it just might look different than it does today.
How about you? Why do you choose to be a Data Scientist?