In this video, we will decode the basic differences between data scientist, data analyst and data engineer, based on the roles and responsibilities, skillsets required, salary and the companies hiring them. Although all these three professions belong to the Data Science industry and deal with data, there are some differences that separate them. Every person who is aspiring to be a data professional needs to understand these three career options to select the right one form themselves. Now, let us get started and demystify the difference between these three professions.
We will distinguish these three professions using the parameters mentioned below:
1. Job description (00:26)
2. Skillset (02:06)
3. Salary (03:26)
4. Roles and responsibilities (03:48)
5. Companies hiring (04:54)
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Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data scientist you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.
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The data science role requires the perfect amalgam of experience, data science knowledge, and using the correct tools and technologies. It is a good career choice for both new and experienced professionals. Aspiring professionals of any educational background with an analytical frame of mind are most suited to pursue the Data Scientist Master’s Program, including:
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