The discussion around data science and the professions of the 21st century has been going on for quite some time. Thousands of professionals of various backgrounds have already “rushed” to characterize themselves as data scientists, data engineers, data analysts and so on… And those who already were, are now appreciating even more their jobs due to the recent hype. I bet that if you could measure how many job titles in LinkedIn switch from X to “Data-something”, you would get a number with at least 4 digits.
If you ask me, I find myself a bit overwhelmed with all of that. I am not quick to slap a business title on me, just cause of the trend. I am actually a bit annoyed by titles in general. It’s true is that I have been working with metadata for as long as I can remember, so I guess I can claim the title “Metadata Scientist” or something similar, without much discourse. But it’s not the same analogy with data… So, I sat down and took a hard and close look to the skills and traits of each job title and the respective qualifications. I did this to see where I fit (and if I fit) and to be able to navigate my professional interests accordingly.
This is my favourite graph so far… It manages to interconnect the skills needed to be able to identify yourself as a data scientist or a unicorn if you will (let’s keep this term for now). So, a data science unicorn has to have a background in computer science as well as significant knowledge on Math and Statistics. Or the other way around. Having a degree in math and statistics but also a really good command of programming. And on top of those, he/she also has to be a subject matter expert in any field. Tough, right?
Of course, having less than this trifecta, is not bad. It’s just that it does not make you a unicorn! 😉 Also, one could argue that being a unicorn in a world of simple and plain horses, may not be ideal in the end. Unicorns can also be subjected to racistic behaviors in the workplace, but this is another topic for another time… Maybe it’s just too heavy of a title to retain! In any case, if you would like to get a glimpse of some comparisons between Data Scientists, Data Engineers and Data Analysts or Statisticians, you can look here: article 1; article 2; article 3.
As for myself, I am not sure if I need to put a label on me (I could be a chameleon instead of a unicorn maybe…). I certainly feel like a homo datum (if my attempt in latin is correct). If anything else, I certainly am a Man of Data (somewhat like the Man of Steel or better yet the Men of Letters in Supernatural). I have been working with data for the biggest part of my professional life as well as in my personal life for a series of side projects. Albeit not really big ones, I am always advocating that size does not necessarily matter. Or it does, but sometimes you can definitely work past it!
I have a degree in management science and technology and a couple more, closer to information science than to computer science. I do have a subject matter expertise on business management and on e-learning. My math and statistics are on the basic end of the spectrum, mainly cause it’s been some time since I used advanced math and statistics but I hope that the memories are still there. I used to love coding as a teenager but my university studies took that away, so the experience I lack, I make up in excitement. 😉
On the other skills listed as necessary for data scientists, or aspiring unicorns for that matter, I do love a good story and I am usually a pretty solid story-teller. I am quite curious about things and I do love the change to quantify something in order to better comprehend it as I have spent quite some time around researchers! 😉
So, for the time being, I remain a “Data Person, Lover, Researcher”, trying to add the “Scientist” label, I suppose. To this end, I have found a set of really really simple and introductory courses that I recommend to anyone that’s interested. It’s the Big Data University from IBM and so far, it has helped me put things that I have been reading and studying into some order and perspective so that I can move up the ladder one step at a time! My hard-earned badges will be added in my personal page on Acclaim, if everything goes as planned!
I would really love to get your take on this. What’s your job title (if relevant to this post) and what do you think that distinguishes you from the others? If you’re one of us, are there any courses and material that you would recommend? Comments’ section is open!
PS: I really love this “badge” approach that allows you to certify online courses that you take! I have blogged about this again, in regards to the Mozilla Open Badges, but it still gets me any time!