There is an increasing demand for data scientists every year due to the growing usage of big data analytics within companies. Researchers believe that in the United States alone, there will be a shortage of approximately 140,000-190,000 data scientists by the year 2020. Because of the huge demand and unique skill sets required, companies are offering an average salary of over $100,000 USD.
Many people are attracted to the high salary and employability of data scientists. However, do not be fooled by thinking the process of becoming one is easy. You need to excel in a variety of areas including mathematics, statistics and pattern recognition.
Identifying trends and patterns within a company’s data set is one of the main duties you must fulfill as a data scientist. Pattern recognition is such a vital skill as it delivers new insights into information sourced from big data sets - allowing a company to make better, and more informed decisions. A low level of analytical skills will ultimately lead to the company steering towards the wrong path.
Once the analytics phase of the work is completed, the next step is to visualize the results. These visualizations will be used to communicate effectively with the decision-makers. It is vital that the visualizations are comprehensive enough for all the management team to fully-understand the information in front of them. Poor visualization can result in miscommunications – also resulting in the company moving in the wrong direction.
Having a full understanding regarding operations within your chosen industry places you at the front of the crowd. Not only is this a useful skill to have at the interview stage, but it also equips you with a similar mindset within the decision-makers of the company – different industries have different approaches to business problems. Understanding a corporate identity makes you a data scientist worth listening to.
Big Data Academy offers programs that provide a platform to becoming a successful data scientist. The courses teach both the technical and non-technical aspects that are required of you to join a data driven company.
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