In Data Science there are two career paths, one is Data scientist and other, Data analyst. These are two different job roles but related and falls under same science but what makes them different is the scope of work and the job tasks. Both positions handling data but at different levels and directions, if we separate them into tasks both have different tasks, in few cases overlapping each other, that’s why sometimes it difficult to confuse them with each other.

This article will try to explain through day-to-day tasks, job scope and skills needed for them, so it may help if you are trying to find a career path in any of them.
Comparing both of the positions, we find more job openings for Data Analyst and it’s easier to move into a Data analysts’ job because you’re expected to have a master’s degree in a lot of cases if it is for a data analyst role PhD is not one of the requirements, on the contrary a Data scientist should be a PhD. There are a lot of data analysts who have taken boot camps certificates online courses as well as bachelor’s and master’s degree to enter the field.

Usually, data analytics often building tangible things for example Dashboards, graphs and charts with a better understanding of the scope of work and as a Data Scientist, you’re often doing Advanced statistics and building models and using machine learning, and work tends to be research focused where there is no tangible output, and hard to show the value of your work.