Data science can be one of the most interesting, exciting and rewarding fields to work in today’s information age. Working as a professional in this field is not for the faint of heart. In fact, this is a highly competitive career and is expected to bring in upwards of eight figures annually. If you are seeking a challenging, fast-paced career that combines solid theoretical and practical understanding along with creative problem-solving abilities, then it may be time to think about becoming a data scientist.
How can you becoming a data scientist? There are only five basic steps to becoming a data scientist: learn SQL; learn computer science and mathematics; obtain some industry-specific training; develop your analytical and logical skills; gain some hands-on experience as an intern in a laboratory or office; and finalize your education with an on-the-job course/ Bootcamp. Of the five steps listed, the third is probably the easiest. You really don’t need any specific background in math, science or computer science to excel in this field. All you need is to be good at problem-solving skills.
The second step in how to become a data scientist is to get some undergraduate level coursework. A good college degree, such as mathematics, computer science or statistics will prepare you for the job market. It is also helpful if your bachelor’s degree is related to a related field (e.g. physics if you are a physical sciences major). Many data scientists start their careers with a bachelor’s degree in one of these three fields.
If you would prefer to start working while you are still in college, there are many entry level jobs for you to consider. These may include working in a department store or retail outlet. Or you may include opportunities with government agencies or with local businesses. You may even find a position in a university or college lab. There are many open positions in the scientific community and there is a high demand for qualified scientists.
You will also need some skills in the data analytics discipline. This includes both mathematical skills and computer skills. You should be able to complete basic spreadsheet programs. You should be able to construct basic programs using SQL and Oracle database management systems.
One challenge that many data scientists and data analysts face is the lack of formal education in the field. Although it is a growing field, there are not many accredited programs in the United States and you will need to rely on books and online tutorials. Courses at technical and community colleges are another option but they usually only cover the most basic principles. They often teach the more advanced concepts in a more general way.
When you are studying, you should focus on learning how to conduct a wide variety of analyses so that you have a wide range of skills that you can apply in many different situations. You should develop your statistical skills and mathematical skills as well as understand the communication skills necessary for a successful career in this exciting field. You should focus on understanding the theory that underlies many of the scientific methods that you will use in your work.
A good data scientist needs to understand many scientific methodologies. Therefore, you will need to know many programming languages. The most common coding languages used by scientists include R, Python, Perl, C, Java, MATLAB, SML, andypress. Although you may start with a simple software package to develop data analysis projects, you will eventually need to begin using more specialized scientific and programming languages.