The Emergence of the Professional DIY Data Scientist

As demand for data scientists explodes, professionals will grow their own data science skills.

As demand for data scientists explodes, professionals will grow their own data science skills, eschewing long-term professional programs and advanced degrees in favor of learning immediately applicable skills. If this sounds familiar, it’s because this is how the IT labor market grew in the 90s – supply of developers outstripped demand, and the enterprising and hard-working taught themselves and worked into a new career.

Just like technology, data science is hard, but it isn’t magic. And just like technology degrees and programs, much of what is taught in school (remember everything you learned in your GenEds?) has no application to a real-world career. Strip all the fluff out of an analytics degree and the knowledge required to actually be useful is achievable in a person’s spare time. This knowledge can be learned from books, websites such as kaggle.com and kdnuggets.com, and Massive Open Online Courses (MOOCs) provided by universities. Remember this: many of the top data scientists on Kaggle didn’t study math in school.

As for the hands-on training, professionals will surmount this challenge in 2014 as well, because most of the really good software is free. Combined with cloud services like AWS (Amazon Web Services), standing up a test environment to practice your new skills costs almost nothing. And like everything else, there are plenty of forums with helpful people and posts to guide established professionals into their new career.

By: Drew Brown