It seems that there’s no shortage of re-branding attempts being made in all industries and by all types of people. I still remember when most of us were called computer programmers instead of developers. Not many people writing C# or Java code would want to be called “programmers” today.
One of the latest fads is the call for more data scientists to work on big data, another equally, poorly defined term. However it seems that he definition of what a data scientist is has been so ill defined that almost anyone that can write a query using aggregates might define themselves as a data scientist.
A good thing if you are looking for a job. Many of you might find opportunities (and raises) if you convince a hiring manager that you are a data scientist. However I’d be wary of living on just the new brand without growing your skills. If your company comes to expect more, especially with regards to advanced statistical analysis, you might find yourself in a bind.
I ran across a piece that looks at the skills that a data scientist might actually need. I don’t know how many managers might understand the difference between simple discrete rules engines and more subtle, complex, multi variable, adaptive algorithms, but there can be a big difference in how well the system actually performs for your company.
No matter what you choose for your carer, I’d certainly encourage you to continue to learn more about how to work with data. Whether you want to learn more about statistics, pick up R, or improve your visualization skills. Keep Learning. Keep your brain active and work to improve before you find yourself without a job and in need of training. Every little bit you learn helps and the practice of continuous improvement builds a habit that will serve you well over time.