Exploring the Different Roles within Data Science

I recently published a guide to the different career paths within data science, and how different skills and tools can fit together into the perfect data science role. This was part of my research for the comprehensive guide to getting a first data science job I developed.


Here are five key insights I found on the different roles and career paths within data science:


1- There are going to be plenty of job opportunities in the field at large. McKinsey is projecting a shortage of 1.5 million data-savvy managers, along with a shortage of 150,000 data analysts.


2- There are three broad skillsets that are required to become proficient at data science: data communication, software engineering, and knowledge of math, statistics and algorithms.


3- There are actually three broad roles that interact together in a data science team: data engineers, data scientists, and data analysts.


4- There is a stark difference in expectations and salaries between those roles. A data scientist will earn much more on average than a data analyst.

5- Data scientists are incredibly rare because they need to bridge all three skillsets which requires a broad knowledge and experience in many tools and skills.

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Comment by Rebecca Barber, PhD on April 28, 2016 at 7:32am

I expect that part of the scary-sharp drop in salary for data analyst is related to how that role is defined.  There are data analysts out there who are de-facto data scientists, but there are equally as many (if not more) who are glorified data entry staff.  And when you add in business analysts, you get even further muddied.  (In my organization, business analysts write requirements for the IT folks.)  I think part of why the title of data scientist has emerged is that it implies that higher level, higher skilled type of data analyst, particularly those over-achievers who learned to program on their own in order to get access to the right data faster rather than waiting for someone else to hand it to them or trying to pull it out of a standard report.

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