Tons of data is being churned out on a daily basis to keep our economy and society moving. This only increases the demand for a data scientist. Being able to analyse and manipulate Big Data is an extremely useful skill to have and it can help various organisations and businesses with strategy formation as well as market forecasting. A data scientist does not only possess skills in the field of maths and statistic, but would also need to be proficient in data collection, coordination and analysis. This is the reason why we data scientists require adequate training in these fields.

What do data scientists do?

A job scope of a data scientist includes and is not limited to data collection, structuring and coordinating the data, interpreting and analyzing and eventually coming up with solutions and tools to solve certain problems. Data scientists conventionally come from areas of study such as Mathematics, Economics, Statistics or Computer Science. The analysis of data can be used broadly across many different industries such as commodities , FMCG, banks and retail businesses. Also, these talents can be put to good use where social problems are studied upon.

Who can be a data scientist?

It is imperative that you understand what it takes to become a data scientist and then delve into it so that you won’t be subjected to a cultural shock.

Being Inquistive

The road to success in any field is always paved with questioning everything that you come across. Data scientists should possess a curious mind to constantly be asking the question of “Why?”. With this passion of finding out about the data that one possesses, the data can then be better understood and eventually processed.

Coordination and Structuring

Upon knowing more about the data, data scientists would then be required to make use of their structuring skills in order to structure the data in such a way that allows for easy interpretation and analysis. If the data is all over the place, it would also be difficult to explain the data to the end user or customer. This is thus crucial to ensure that data scientists are ahead of competition as customers would definitely look to someone who can explain to them what the data means in layman terms.

Persistence

The job of a data scientist can be very grueling and statistics intensive. In order to be successful in this line of work, one would need extreme amounts of patience and the will to persevere in the face of odds. It is very likely that a data scientist would not be able to derive a solution to a problem on his first try and would need to keep trying out different ways of doing things in order to arrive at the optimal solution. As a result, it is important that a data scientist possesses a strong mind and the persistence to succeed.

Becoming a data scientist

The process to becoming a data scientist is complex and must be well thought out. Firstly, a degree in computer science, maths or business would be integral in providing the data scientist with a strong foundation to build on. While pursuing your degree, it is imperative that an internship is done to bolster your resume in that related field. Upon receiving your bachelors degree, pursuing a masters degree would be a wise choice as the market for data scientists is really competitive and you would certainly want to stay at the top of your cohort where academic qualifications are concerned. It is also worth mentioning that those who rise to management level positions usually hold a PhD in data science.

However, if the above mentioned steps are not possible for you to take due to circumstances, the next best option for you to help yourself, would be to enroll yourself in our data science classes that will kick start you with a data analytics foundation and improve your job options. This certification that will be provided by us will go a long way in helping you to realise your potential as a data scientist.