Data Science Career Paths

The data science field is pretty new, it has been around 15 years since this particular field started and is still developing there are a lot of changes that are happening on a regular basis.

There are a lot of websites, articles, and institutes that try to give it their version of a data science career path. Me being in this industry for 15+ years and worked closely with all the components of the data science field I am trying to decode and give my viewpoint of the data science career path that I have personally seen in the industry. This particular article helps in describing the data science career path in a very simple way according to the hierarchical needs of a data science project

These career paths may have an overlap with each other and the definition is a not very concrete it can be flexible according to the needs of the organization and the size of the organization and the type of work culture that organization has but broadly speaking from the Industry Trends and for medium, to large companies, this is how the career path are been mapped.

?You as a Data Science aspirant or a person who wants to develop a Data Science career, have to be Cognizant of these needs and your wants and skills that interest you. You can focus and develop your data science career path, there will always be the intersection of needs but you can grow in your career by picking up any of these and sharpening your skills for your data science career

We will address the ‘big five’ designations and their synonyms for data scientists) and trace their professional career paths.

1. Data Analyst

2. Data Engineer

3. Business Intelligence Analyst

4. Data Scientist

5. Advanced-Data Scientist

All work in Data Science can be broadly divided into 8 levels of Hierarchy needs. The different career paths in Data Science will focus on the combination of these 8 needs

1. Data Analyst: Works mostly in 3rd, and 4th, needs of data science. According to the situation, they might also work in the 5th and 7th needs of Data science
2. Data Engineer: Works mostly in 1st, and 2nd needs of data Science. According to the situation, they might also work in the 3rd needs of Data science
3. Business Intelligence Analyst: Works mostly in 3rd, 4th and 7th needs of data Science
4. Data Scientist: Works mostly in 3rd, 4th, 5th, and 6th needs of data Science. According to the situation, they might also work in the 2nd and 7th needs of Data science
5. Advanced-Data Scientist: Works mostly in 5th, 6th, and 8th need of data Science

An Individual can work in all 8 needs in his career span, but at a particular project, he will be working in one of these 5 careers. To be a specialist in each field will take 5 to 7 years and companies want specialists to deliver on Analytics projects that bring business value. In my next article, I will write detail about each career path and how to play your career.

After talking to 200+ Clients, every individual story is different and their path really depends on their interests and skills. If you still have some confusion and want more clarity, I would recommend booking a call with me.

Agree? Kindly comment on your aspirations and experience in the Data Science field?

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