Top 3 Skills Needed to Become a Good Data Scientist

Top 3 Skills Needed to Become a Good Data Scientist

As an aspiring Data Scientist willing to start his career it is very much important to have prior knowledge of the concepts related to Data Science and also other prerequisites should be satisfied. Most of the Data Scientist fails to get placed in good companies due to the lack of these prerequisites and then suffer depression and anxiety.

As a Data Scientist, you are the backbone of any data-oriented work and you should be able to diagnose the right kind of issues that the data is suffering from irrespective of any type of complexity in the data. The way you think the same reflects in your work so you should be very careful while handling real-world cases.

Currently, Data Science is the hottest topic out there and companies are investing huge amounts of money on data so the employability of this sector is huge provided you have the required skills. So, today I will be discussing the top 3 skills that are needed to become a successful Data Scientist as per my view. So, let’s get started:

3 Skills Required

  • Technical Skills: This is the first and foremost skill required to become a good Data Scientist. By technical skills I mean having coding skills with many top trending programming languages like R, Python, Scala, etc., having mathematical and statistical skills that are in-depth understanding of various statistical terms like regression, distributions, sampling, etc., having the knowledge of multiple data visualization tools like Tableau, PowerBI, etc., having knowledge of Relational as well as Non-Relational Database Management Systems like MongoDB, MySQL, PostgreSQL, etc. With all these skills in your kitty, you can probably say that you are a good Data Scientist and can apply in top tier companies. These skills are the key to land in these companies because when we are talking about data then statistics and coding is a must.

 

  • Data Understanding Skills: This is one of the most important skills that every Data Scientist should possess if he wants a handsome salary along with additional perks. For a Data Scientist, data is their God and it helps them earn their daily bread and butter. So, data handling skills should be there within him/her. By data handling, I mean that he/she should be able to understand the underlying answers within the data and should be able to detect every possible point of the data which is of utmost importance. Data understanding skills can also be extended to feature engineering skills as well because in feature engineering a Data Scientist tries to collect the important features that are required and neglect the unwanted ones. Also, a Data Scientist should be that efficient that he can explain the data in the form of a story to help the intended public understand the meaning of the same.

 

  • Good Leadership Skills and Problem Solver: As a Data Scientist you should be confident enough regarding your work and should always stay motivated and explorative. As we know that the field of Data Science is very vast and the more we dive in it the more we get to know many important things. So, being a Data Scientist you should try to explore things and not just remain stagnant. You should have good problem-solving skills because these skills help in building leadership qualities. Companies always hire those candidates who are smart enough to tackle any kind of situation rather than hiring only highly educated ones. Yes, education is an integral part of getting a job but it is not the only thing that one should possess. You should be self-driven towards your work and should always think out of the box to create something innovative. These qualities will help you in getting placed in the top tier companies.

Conclusion

In the end, I would like to conclude that, try to learn the in-depth intuition behind every concept that helps in Data Analytics and then implement the same in the real world. Also, keep these 3 things in hand as these will help you create wonders in the field of Data Science.

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