10 Must Have Data Science Skills, Updated

An updated look at the state of the data science landscape, and the skills – both technical and non-technical – that are absolutely required to make it as a data scientist.

It has been a year and a half since Linda Burtch of Burtch Works wrote 9 Must-Have Skills You Need to Become a Data Scientist, a post which outlined analytical, computer science, and non-technical skills required for success in data science, along with some resources for gaining and improving these skills. While this post is still relevant and quite popular, I thought I would take a shot at updating it, taking into account the direction of data science developments over the past 18 months.

My approach is a bit different than Linda’s, which was to distill the views of, and conversations with, a number of analytics professionals considering adapting their skills to the field of data science at the time; mine is based on observations of trends, content of articles, prevalence of ideas, and discussions with a number of individuals in various positions of career development in the field. Please take this as additional information to take under advisement, as opposed to any kind of definitive advice.

Burtch provides some numbers related to the educational level of data scientists, indicating that 88% of Data Scientists have, at minimum, a Master’s degree. Burtch does not explicitly provide her source, but I can only assume it comes from her firm’s extensive research, with which I am not going to outright contradict. What I will offer, instead, is that data science is an incredibly diverse field, with no real consensus as to what it even is. I’m sure people will disagree with that, but when I hear the term data scientist, I tend to think of the unicorn, and all that it entails, and then remember that they don’t exist, and that actual data scientists play many diverse roles in organizations, with varying levels of business, technical, interpersonal, communication, and domain skills. If we recall that different roles such as machine learning scientists, data analysts, data engineers, Hadoop administrators, and analytics-focused MBAs often get wrapped up in with the definition, it’s easy to determine that there would be many paths to data science. To be fair, Burtch’s definition of what a Data Scientist is, and therefore what educational levels they have, could vary quite drastically from mine.

That said, there is likely much more variety of education levels held by those considering themselves data scientists. To that end, the 2015 Stack Overflow Developer Survey, which is composed of self-reporting data, provides the following, for example:

Granted, this is a single snapshot in time, and it would be foolish to draw conclusions based on this single piece of data.