One of the most demanding fields these days is Data Science. It is because various organizations require individuals to identify trends and predict those trends. The role of a data scientist may differ with respect to the industry or organization and so does his responsibilities. These responsibilities are categorized under three types: Type A, Type B, and Type C. In this post, we will make you acquainted with different areas that a data scientist needs to focus on. Also, we’ll explore how learning new skills by enrolling in a data science course in Bangalore with placement will help you start a career in this field.
First of all, let’s have brief look at the responsibilities of a data scientist according to different categories.
Various Roles of a Data Scientist
Type A- Analyst
Type A data scientists are called Analysts. They hold excellence in analyzing data. They are good at collecting a large amount of data and making sense in a relevant manner. They are also regarded as traditional data scientists. To take insight from data, they use their main skills in statistics and modeling. Moreover, they are experts in communicating with non-technical audiences due to their understanding of business implications.
Technically speaking, a data scientist belongs to a very heavy research background. The skills of a data analyst are rare and this makes companies realize that the actual study background of a data analyst matters the least. The only thing that makes the difference is their work experience. One who is a data analyst needs to have important skills like expertise in programming languages, an open mind and needs to be curious. If anyone wants to improve learning and increase curiosity, various data science course in Bangalore are available for their placement.
Type B- Builder
Type B data scientists are categorized as builders and are generally software engineers. Everything is done in the cloud. A builder set up the infrastructure manages how the work will take place, and coordinates with the team to ensure that everything goes in a controlled and perfect way. Additionally, his job is to ensure that team members are writing clean code, unit tests, functional tests, and everything needed for a code to run properly.
The common tern used for builders is the ‘new age machine learning engineers’. Machine learning programs are also built by them. Builders usually work in the production environment. However, to be a type B data scientist, you should know frameworks like Git, Docker, and cloud computing software. The reason is that they are important tools that help in managing and analyzing the information. The frameworks like Git and Docker can be easily learned with the help of a data science course.
Type C- Consultant
Earlier, a data scientist was referred to as a programmer, mathematician, business domain expert, and a lot more. Type C data scientists are a consultant and lie somewhere in the middle of type A and type B, but have very strong consultant skills. In contrast with other data scientists, consultants possess strong stakeholder management and communication skills. This ensures that the business problems are handled wisely with appropriate solutions.
Consultants hold expertise in working with various organizations. This makes it easy for them to adapt to the company’s requirements. Generally, type C data scientists are leaders or project managers. They need to be applauded as they are quick at persuading and communicating with business. If you’ve good communication skills, there are chances that you’ll become a leader. Mostly, type C data scientists can be the manager of data science, head of data science, or chief data scientist.
Looking to Start a Career in Data Science?
Given below are skills that you should possess if you are looking to start a career in data science:
Data science is completely a team sport. Irrespective of your talent, you can’t rely on just yourself to do everything. It is a collaborative field. Thus, you have to coordinate well with others.
Adaptable to Change
As change is the only constant, the field of data science is ever-growing. So, if you are not the one who likes change, data science might not prove to be a perfect fit for you. You need to be adaptable to change, new ideas, and technologies.
How to Start?
You might consider breaking into the field of data science a daunting task. But, with the right approach and some hard work, you will be able to make your name in this ever-growing industry. The best data science courses online will help you learn statistical approaches, machine learning, programming languages, and playing with data.
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