Data Scientist: The Sexiest Job of the 21st Century
The Hot Job of the Decade
Hello Data & AI enthusiasts !
You have probably seen the Harvard Business Review article about Data Scientist being the sexiest job of the 21st century. (Link here)
I remember first seeing it and hearing about it from my university colleagues as we were about to choose our definite majors and specializations. We got interested in this new career path and a lot of us really considered pursuing it including myself.
The article talks about some of the skills that the job of a data scientist can provide to a business and the huge value these can add to it. The article starts by giving an example of LinkedIn and their People You May Know Algorithm at its early start. This simple algorithm or feature helped LinkedIn generate millions of new page views, which in return helped Linkedin’s growth significantly.
According to the article, any business can benefit from data scientists if the business stores multiple petabytes of data, if the information most critical to the business is stored in data or if answering important questions related to the business would involve multiple analytical efforts.
Every business today stores some form of data and they should without any question - with the consent of their clients and users obviously.
And with this mountain of data collected everyday over a long period of time - most of the time very unstructured and messy data - comes several questions and hypotheses that need to be tested in which massive value can be driven that would not only benefit the business, but also the clients and the user experience altogether.
If you are a data & AI enthusiast then this is your opportunity to get into the data science space before the end of the century !
The need for data scientists and the attractivity of the job comes from everybody collecting data as you have probably wondered. But there is something that most people don’t talk about, and if you have dabbled with data before then you probably know what I am talking about. Driving value from data is not as easy and compelling as it sounds. You need to have some sort of experience before getting the hang of it and most people struggle heavily at the start.
There are a lot of technologies out there so oftentimes it can feel very overwhelming to even attempt to start the journey.
Doing the right tests and picking the right models only comes with experience, and every data is different so it is always going to be a nonstop learning process.
But you shouldn’t be afraid as it is only a matter of time before you can get used to all of it.
On the plus side, the data science community is very welcoming and very helpful !
The advice that everybody gives new data scientists and data & AI enthusiasts is to make as many projects as possible and to gain as much experience as possible. This is what would help you feel comfortable dealing with complicated messy data, understand the data you are working on and drive real value from it.
Stick to the journey and we will learn together !
The article ends with comparing data scientists to Wall Street quants of the 1980s and 1990s, and Hal Varian, chief economist at Google, compared statisticians to computer engineers of the 1990s. Also he said that the sexy job in 10 years will be statisticians.
We will not get into the difference between statisticians and data scientists, but both rely heavily on data and drive value from it.
Data is the future.
A question is later asked in the article; Should companies wait until the second wave or the next generation of data scientists emerges, so that the candidates are numerous and cheap to hire or should they start now, and they answer this question by saying the following :
Think of big data as an epic wave gathering now, starting to crest. If you want to catch it, you need people who can surf.
The answer is obviously no, companies should start now and immediately.
Side note : The article was written in 2012 so the next generation of data scientists is us, is you reading this.
Have a wonderful week,
Hind