How to start a career in Data Science for Management students

Data Science and its related terms such as Business analytics, Business Intelligence, Data Mining etc have become a vital and power tool for growth in the 21^st century. Management graduates having understanding of data or those who are able to derive some meaningful information by exploring data have wider scope and acceptability in business world.

According to predictions of Mckinsey, by 2018 there will be a 50% gap in the supply and demand of data scientists.  This clearly indicates that the demand for data scientists and Business analysts is increasing at a rapid pace. So, there are significant opportunities for management students in this field.

If a management graduate is looking for making a position in data science industry, He or She needs to follow these steps:

• Choose a right role:

Before getting into this career opportunity you need to choose right role for you. There are a lot of varied roles possible in data science industry such as data visualization expert, a machine learning expert, a data scientist, data engineer etc. Depending on your background and your work experience, getting into one role would be easier than another role. Generally management graduate are hired on the role of Business analyst, Data analyst, Market Research analyst, Business Intelligence expert etc.

• Take up an additional relevant course in Data Science/ Business Analytics

Since you have understood the role, now the next logical thing is to acquire necessary skills for this role. A management graduate has already been taught some relevant subjects related to data science or business research. To further sharpen your analytical skills you can take up any online course (MOOC Course) on data science/Business Analytics. You can also do some regular six month/one year diploma in Data Science/Business Analytics.

• Learn a software tool

Now days the data scientist use various softwares to perform their research or analytical activity. Some commonly used softwares are Excel, SPSS, R, Python, Tableau etc. The million dollar question is which tool is best. It is hard to define. Every tool has its own features and applicability. So you need to select the one in which you are more comfortable.  Generally one of the tools is taught in most of the online courses on Data science/ Business Analytics.

• Focus on practical application not just theory

Data science/ Business Analytics is a field which demands lot of practical application of the concepts. It does not mean that the theory is not important. Theory will provide starting point to think but further problem will be solved by applying the concept in the real situation. So always keep in mind, while doing any relevant course you should focus on the practical applications of things you are learning.

• Keep Learning and Practicing

This industry is very dynamic and demands high level of motivation. You can not be a great data scientist or business analyst in one day. There are thousands of techniques available for data scientists, which can not be learned in one day.  It requires a constant learning attitude. If you are able to motivate yourself to learn new skills you can become a great data scientist.