This article is for current data scientists who want to move up in their careers as well as for people switching careers to the data science landscape and want to know what separates and defines a senior role. It is important to note that not every workplace or company will offer both of these positions; however, if you satisfy the characteristics of a senior data scientist, you may be able to prove to your company why getting that title is worth it for you and them.

The senior data scientist position does not just mean that you are a data scientist with a certain amount of years of experience. It is rather, a position that entails a difference in responsibility of the impact of your data science or machine learning models on the business that you work for.

Not only are there key differences between the two job titles, but there are also some interesting differences and overlaps between the amount of machine learning, business intelligence, and product management from each role. Below, I will discuss both my experience in the two positions as well as reference material on distinguishing the two titles.

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