How to Become a Professional Data Scientist?
It is widely recognised that the world market demand for skills can change with lightning-like rapidity as the functioning of the world economy gets ever more digitised. Today, demand for skills is especially strong in the case of the profession of data scientist. Thus, in this article, we will examine what it takes to be a prospective data scientist of the 21st Century.
So, to begin with, what do we mean by “data science”? Data science is a newly emerging scientific discipline born out of the blending of some subjects such as mathematics, statistics, economics and other computer-oriented courses.
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Why is Data Science so Important?
To begin with, the field is multidisciplinary by nature and comes with its own specialised techniques, methods, algorithms and procedures. To date, there are only a few universities worldwide that have already started offering postgraduate data science programmes, but many institutions are nonetheless hurriedly preparing to offer courses to meet the burgeoning market demand. Besides, the rationale for offering data science as a separate field of study is to produce professionals well trained and skilful at handling, communicating, handling, analysing, interpreting and investigating relationships in big data sets so as to inform better decision making.
What makes a Good Data Scientist?
A data scientist is a professional with the ability to craft a language to silently and vehemently play with disordered data so as to discern some unknown relationship or pattern among data sets. The special quality that a data scientist needs to have at best is curiosity: a desire to explore and dive deep into an issue following his/her own scientific procedures, and thereby develop a hypothesis that can prove or refute an existing theory or model. Furthermore, to prepare oneself to be a prospective data scientist one should make a habit of thinking statistically as well as creatively, and develop an indomitable spirit.
To gain entry to the profession, it is highly recommended to learn and master differentiated statistical programs and languages as diverse as SPSS, STATA, Eviews, SAS, R Studio and Python. The journey to secure towards becoming a fully-fledged data scientist entails coming to understand the advanced applications of multifaceted data visualisation, programming, integration, and manipulation techniques. You need to master a balanced and pragmatic mix of technical and statistical skills.
A data scientist is a particular investigator of the story behind the data, and is much more than the average problem-solver. Becoming a data scientist is not a goal that can be achieved overnight, and the job itself is not too simple, either. It requires a unique personality trait when it comes to dealing with data, namely a capability to turn unstructured big data into a structured form suitable for use. It can be seen that successful data scientists assisting the world of business today are mainly drawn from Mathematics, Economic, Computer Science and other disciplines known for rigour in mathematical calculations. Of course, data science is not only a profession that is highly in demand, but it is also a highly remunerative one. Data scientists are being hired by the world’s leading companies such as Facebook and others. We can be reasonably certain that the highly digitised global economy will be in need of data scientists in the future, too.
Thus, early on, we recommend that the young people should get acquainted with the emerging opportunities in the field of data science and if need be, to embark on a career plan that takes account of the skills required, the costs to be incurred and the likely opportunities lying ahead.
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