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.