Different roles and responsibilities involved in the field of data science

Data science is flourishing in all directions, with a rapidly growing industry and applications. Everyone knows that when a field flourishes, the number of jobs created can be really noteworthy. Same goes with data science too, in another five years, artificial intelligence and data science will reach new heights in terms of innovation and need of workforce for the same.

Data science as a subject is diverse on its own, it involves many different activities which together can give the needed result of finding insight from a vast sea of data. In layman’s sense, data science is a field in which one collects raw data and then tries to find meaning and insights from it which in turn can be beneficial for a company’s growth.

The pipeline of data science

In very simple language, data science involves these activities which are to be done one after the other.

• Collecting data
• Cleaning the data
• Exploring the data
• Machine learning
• Interpreting and communicating the results

All these steps may sound very simple, but it is not and usually requires different people with different set of skills. Now, let’s focus on the different roles that one can pursue in data science.

Data analysts

They are those who are needed for exploring the data and also to keep the algorithms and programs optimized so that they perform in the required manner. One should have really good problem-solving skills, and certification in SQL, R, Python will be needed to secure a data analyst job.

Database administrator

They are the true handlers of the databases that a company has stored in their framework; who can access what database and who cannot, is decided and controlled by database managers. Some of the skills one will require are database security, recovery, backup, data modeling, and designing.

Data engineers

Data engineers are responsible for keeping the entire data science ecosystem updated and stable. They are supposed to update the entire system with the latest technologies and improvements so that the overall efficiency can be boosted. Some of the skills that one needs to be certified in is NoSQL, Java, Ruby, C++, Matlab etc.

Machine learning engineer

This is one of the highly demanding jobs in this sector today. An ML engineer needs to create algorithms and use them to find insights from the data. For this, they have to be efficient in both math and statistics. Some of the tools that one needs an in-depth knowledge of are Java, Python, R, REST APIs, SQL, A/B testing, clustering etc.

Data scientists

They work on both managerial and technical levels, as they need to have a knowledge of business problems and then use data science tools to find patterns which on predictive analysis will give solutions to the aforesaid challenges.

Data Architect

Data architect's main responsibility is to manage data by integrating and centralizing the data and also make sure that data at all times is protected from external foul sources. The skills one needs to have are data warehousing, data extracting and modeling using tools like Pig, Spark, and Hive.

Statistician

They are known for their statistical skills which help in finding meaning from the data clusters using statistical and mathematical tools. Without them, the data engineers will not have processed data to work on.

Business analysts

Though they do not work on data themselves, they have great knowledge about what other activities are. They are the bridge between the data processing and finding business-based solutions by using that data. They link the data to the business strategies and should have knowledge about both data science and business management.

Resource box

As mentioned above, data science jobs are not done by one single person, instead, it requires many people with specialized skills. And to gain and enhance the skills, one needs to get trained under the best data science courses, where one can learn everything, from the very basics to the advanced level of big data.

Knows that when a field flourishes, the number of jobs created can be really noteworthy.