If you need more information about data science, machine learning, and other skills that data scientists need to perform well, browse our career guide for data science. After you have assessed your needs and embark on your career in data science, below are five important tips you need to follow to succeed in your chosen field. If you want to network and become a data scientist, you should look online for opportunities.
If you’re wondering about the available opportunities for a data scientist, all you have to do is think about any system that forms part of any business, company or organization with the view of improving how it operates. So that brings into view pretty much any enterprise, doesn’t it?
The official academic route
If you have always wondered how to start a career in data science, you might have identified a need for qualification as a Bachelor in Computer Science or Computer Engineering, a Master or PhD. The first step is to become a data scientist, which usually earns an annual salary of at least $25,000 to $50,500. Some schools offer degrees in data science, so you can enroll, but there are other ways to learn data science skills, such as military boot camps. Data science courses at universities such as the University of California, Berkeley, and the California Institute of Technology also prepare students for a career in data science.
While a degree in data science is the most obvious career path, there are a number of technical and computer-based degrees that will help you collect your data – a scientific career (as this article on Thor IT points out, science and technology are so closely linked, so a good scientific background is important for this type of role). While it is not strictly necessary to be hired in an entry-level role as a data scientist, it will probably become more important if you want to advance your career in data science. You will probably consider taking a job in data science and data analysis.
Data science can also land you a job in unexpected places such as video game design, so it’s useful to think outside the box when considering where to apply your skills. Obviously, you’re going to need an understanding of video games to be able to work for a game developer, but if you’re a gamer in your spare time, it could be the perfect job for you. Take a look at these free scripts for some of the most popular games – they should help you to better understand how you can apply your knowledge to a real-world setting. Video games are full of technical data that you should know all about as a data scientist, game scripts are just where the knowledge has been applied.
If you have no experience working with data, you are unlikely to become a data scientist. You may need to develop a strong understanding of data science and various data analytics platforms like KNIME to successfully pursue a career in data science. Of course, a degree in computer science, computer engineering, or other technical fields will open the door to a career in data science in healthcare.
Data science is relevant to all fields
For data science to penetrate its adjacent fields, you need to acquire a certain set of skills. The most effective way to do this is to enroll in a structured learning program such as a data science course or bootcamp. Entire companies exist in this field, getting into specialties such as Grid Dynamics machine learning. So possibilities are limitless in terms of the career paths to possibly pursue, with no ceiling looming over the level of specialization.
A common next step is to further develop data science skills, often with an emphasis on machine learning, and work in the role of a data scientist. Most data science courses require internships that provide students with practical experience in data analysis, data visualization or data processing.
