Choosing the right Data Scientist is not straight forward!


Big Data’s epoch is moving at a faster rate. There is no stopping too to the growth of data across enterprises. However the main challenge here is how to make sense of this exploding data. This where the data scientist is assuming a significant role. Now how enterprises can choose the right data scientist? What are the factors one need to look into while choosing his data scientist?

A data scientist should have the ability to choose right technology to analyze data. He should have proper knowledge to understand different technology options and also primarily should have the ability to solve wide range of problems using available data. They should be having valuable knowledge and insights to make use of abundant data in a useful manner. It is crystalline clear that the need of the data scientist is moving at a rocket speed. The future of business is uncertain. It involves risks and has to make crucial decisions about the future. So firms have to incorporate data scientist into their business model. Before selecting a data scientist we have to keep some of the characteristics about him.

We need to ensure that we can afford to hire one. A data scientist could cost a company $100000 per year. If one cannot afford to hire an expensive Data Scientist, we can also consider the possibilities to encourage some of existing employees to grow into the role of data scientist, though it is a tough proposition. While selecting the data scientists, one should look for a professional who have got the ability to have a deeper understanding of the industry so as to make useful data models. Curiosity along with a potential to transform data into an output make a candidate being distinguished from others.He should poses strong communication skills. A data scientist should be nimble to alter their methods so that it suits with a particular industry. By asking to develop a sample presentation based on a specific set of data, we will get an idea about their real vision, in-depth insights and understandings. Last but not the least, a Data scientist should possess strong statistical know how and logical capability to deduce logic for coming out with successful data models.


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