What’s the difference between a data analyst and data scientist?

There are different type of data analysis jobs. Two of the main positions are data analyst and data scientist.

Here’s a breakdown of the differences:

While both positions deal with analyzing data, the main difference is the focus of the analysis. Data analysts examine data to identify trends, develop charts, and create visual presentations to help businesses make more strategic decisions. The best data analysts have both technical expertise and the ability to communicate well about their quantitative findings to non-technical colleagues or clients. A data scientist focuses on designing and constructing processes for data modeling and production, using such things as algorithms and predictive models.

According to Robert Half Technology (RHT)’s 2020 Salary Guide, data analysts have an earning potential of between $83,750 and $142,500, and data scientists have an earning potential of between $105,750 and $180,250 per year.

Thanks to companies’ need to make sense of and capitalize on their data, qualified individuals for data-focused careers, such as data analyst and data scientists, are in high demand in the job market today.