Different Job Roles In and Around Data Science

August 01 10:41 2017 Print This Article

The term data science is often used quite loosely and in a very general sense. It is true that data science is a wide and deep domain and it encompasses a lot of aspects. Something we need to understand is that not every professional working in this domain is a data scientist, in fact, most are not. There are a lot of job roles in and around data science, let us take a look at some of those.

Different Job Roles In and Around Data Science

Data Architect: Just as the name suggests this position has a lot to do with the management and maintenance of data as well as data sources. A data architect usually designs the blue prints of a system to manage data and to centralize, protect and maintain the various data sources. This job role demands the job holder to be proactive – one must continuously keep learning the new tools. You always want to be at the top of your game as a data architect. If you have in depth knowledge of database architecture, have a knack for data modelling, and you can manage data warehousing solutions, data architecture might be your thing.

Data Engineer: These people get to taste a bit of everything. Since data engineers are involved in development, testing and maintenance of data architectures, you cannot really confine their role into something specific. Quite like data architects, they need data warehousing skills and should have a talent in data modelling. SAS, Python, Matlab, Java, Ruby are a few of the languages that can really help a data engineer out.

Statistician: They were the harbingers of data science as an academic subject and now, they are pretty important assets for any enterprise that is looking to dig deep into data science and advanced analytics. Modern corporate statisticians should be equipped with data mining and distributed computing skills while also possessing in depth knowledge of statistical theory and methodology. These theories and methodologies help them collect, analyze and interpret data.

Getting a data science certificate can get you introduced to most of these skills while you can specialize in a select few of them. Once you join the industry you can always work your way up to the top by learning and mastering new skills and technologies as well as gathering firsthand experience. Data science certificate gets you started and gives you credibility. Another important aspect of joining a certification course is that you get introduced to a community of people which can help you build a network.

The job roles we discussed are only a few among the numerous professions that keep the data science industry up and running. Job roles like database administrator and data analytics manager are also important to the functionality of a data centric enterprise. The purpose of this article is to make people realized that how enmeshed various different roles are under the term data science. And you only become a data scientist after years of experience and hard-work. The intermediate steps are as important.

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