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How to Become a Good Data Scientist?


There is no one who does not want to make a success out of his or her life. We all harbor dreams of slowly but surely climbing the ladder of success with hard work as well as dedication. If you think that your calling lies in becoming a data scientist then you should not shy away from putting in your all and work tirelessly towards your goal. People assume that it requires excellence in a number of fields but actually it is not so. Given here is a comprehensive list on how to become a data scientist.

how become data scientistSkill Requirements to Become a Data Scientist:

1. Learn about matrix factorization:

Matrix factorization or matrix decomposition as it is known is used in a number of different kinds of fields, including this one where a data scientist skills and knowledge in matrix factorization is constantly put on the test. You can opt to take a Matrix analysis course which is often known by numerous other names such as Numerical Analysis, Applied Math Course, Matrix Computation, Applied Linear Algebra or also a linear algebra course, all these courses offer the same matter.

2. Learn about basic statistics to help you:

Needless to say that numbers and statistical data form an important part of any company in this day and age to know how much their profits have been as well as how much progress they have been able to make. Though data scientists are expected to have an array for skills and abilities yet, when it comes to statistical analysis they do not necessarily have to carry in-depth knowledge of it. However basic knowledge in statistics is a prerequisite for you to become data scientist.

3. Develop your artistic skills:

artist skillsDo not be fooled, being a data scientist doesn’t imply that you will have to be good at drawing or be a skilled artist, rather you should have the ability to put forth your data in a more interesting manner rather than in boring words. For example a more palatable and good way to put forth your analysis could be in the form of diagrammatic representations or graphical forms which will really help you grab a lot of eyeballs, gain appreciation and be understood by all even those who are not data scientists.

4. Business acumen is rather necessary:

If you aspire to become a data scientist in the corporate world then you should ensure that your business acumen is on point or you might find yourself being taken for a ride by a number of people. This does not mean that you become cunning or selfish, rather it makes you shrewd to deal with various people in the business world who are always on the prowl to victim anyone who seems like easy prey and willing to trust easily.

5. Having a very curious bend of mind:

Intellectual curiosity is one of the main things when it comes to how to become a data scientist and a good one at that. If you are lacking in this curiosity then chances are your analysis will be at a very superficial as well as primary level without delving deeper into things. It is this depth as well as detail which will give you the chance to excel and set yourself apart from the others who do not go to the very crux of the matter when it comes to the analysis which they give.

6. Development of your communication skills:

communication skillCommunicating in this case does not mean that you must have the gift of the gab; rather it means that you should be able to get your ideas across in a very clear and comprehensive manner such that others are able to understand what you are trying to say without any trouble at all. If you are able to make a breakthrough but unfortunately are not properly able to get your point across then chances are that your work may not get the appreciation and the attention it ought to.

7. Learn to work as a team player, as it is important:

When being a data scientist it is of paramount importance to learn to work as a team player. Being individualistic and trying to do things your own way is a good thing yet that does not mean that you are not open as well as receptive to what others are saying. While carefully paying attention to what your team members are saying or sharing ideas, you too could gain a wealth of insight when it come to being able to handle data in a more efficient as well as proficient manner.

8. Constantly work on your comprehension skills:

Having good comprehension skills is one of the basic things when it comes to being a good data scientist. However even if you are lacking in this particular field, then do not worry as there are plenty of ways to work on it. This skill will help you to conclude about various data which is put forth before you. The faster you are able to grasp things, the more beneficial it will be for you.

9. Education is very important before applying for a job:

It is a well known fact that data scientists are very highly educated people. Statistics show that roughly eighty eight percent of all data scientists have a master’s degree and over forty six percent have PhD’s. The most common fields of study for data scientists include Mathematics (With thirty two percent students), Computer Science (with nineteen percent) as well as Engineering (sixteen percent). Yet, one should remember qualifications do not guarantee that you will excel in the field.

10. Make sure you have sound technical knowledge:

sound technical knowledgeThe most important part on how to become a good data scientist is having sound technical knowledge. So whether it is Python Coding (Most widely used coding language such as Java,C/C++ or Perl) , Hadoop Platform (having a working knowledge on how to work with Hive or Pig), SQL Coding or Database (Being able to write and execute any queries in SQL) and even working with unstructured data, you should be able to tackle the data in an satisfactory as well as professional manner.

11. Follow the dictates of your own mind rather than following the herd:

If you are not convinced with the analysis which has been done by another individual then do not shy away from working on the data on your own. This is one of the basic things on how to be a data scientist. Do not blindly follow the herd, rather take matters in to your own hands and try to set things right. By doing this you silently communicate to the rest of your team mates as well as your seniors that you are a hard worker who will not blindly accept what is being told rather delve into things yourself.

12. Learn to fall in love with data and letting it speak to you:

Falling in love with data is one of the primary things when it comes to becoming a data scientist. If you do not love data and if you feel over whelmed then you will never be able to do well. Rather you should let the data speak for itself and never proceed on hypothesis. Never blindly believe anything if the data does not categorically point at the fact. Falling in love with data and letting the data become a part of your system will really help you make an incredible breakthrough.

13. Keep exercising your mind at all times to keep it active:

Being a data scientist may not involve a lot of physical or field work, yet it involves a lot of mental activity. So even if by chance you are not working on any data science projects at a given time, you should ensure that you keep exercising your brain either by solving algorithms or even by doing simpler things like puzzles or brain teasers. Doing this is bound to help you in the long run as well. If you let your brain get lazy or inactive when you throw no challenges its way, then things are bound to get tough for you.

14. The top data science degree programs across the globe:

As it has been mentioned, being educated is very important when it comes to being a data scientist. There are some important skills which do come naturally to people, yet most of the science skills must be acquired with education, some top data science degree programs across the globe include, MS in Data Science in Ney York University, MS in Data Science in the University of St. Thomas or even Professional Master of Information and Data Science in UC Berkeley.

15. Start your own data science blog to gain valuable feedback on your data analysis:

start your own blogIn today’s technological age, almost everyone has their own blog, which is based on where their interests lie and what it is that they like doing. If dealing with data is something that excites you then what you can do is start your own blog and then post the results of your data analysis. This is a great way to help you reach out to other like-minded people. In addition to this another added benefit of doing this is that you can get valuable feedback for your work, which will help you improve.

16. Learn to think on your feet and find solutions swiftly:

To be a good data scientist, a basic prerequisite you need to have is the ability to be able to think on your feet. If you would like to excel in this field then being a slow and lacking in common sense is not going to take you very far. Owing to the fact that data scientists have to manage a truck load of data, they cannot afford to be slow workers who cannot get their jobs done fast. However this does not imply that in the attempt of trying to get your job done at a quick rate you end up giving sub standard erroneous work.

17. Having an exceptional degree of clarity of thought:

The primary part of having a job as a data scientist is being able to deal with a mammoth amount of data and not only sorting it out but making sense of the entire thing. If you are someone who easily begins to fret when a great amount of mess information is put forth before you then perhaps this might not be your calling. The job description of the data scientist is such that the individual must have immense clarity of thought so as to deal with all the data without feeling daunted or pressurized.

18. Decide on the type of company you would like to be a part of:

When becoming a data scientist you ought to think long and hard about the kind of company you would like to be a part of. There are three main types of companies to choose from, firstly those companies where being a data scientist is synonymous with being a data analyst, secondly there are those companies that are looking for persons to set up a data infrastructure for them, and finally those companies who treat their data as product. When you gain experience you will understand where you exactly belong.

There is no career path that is a cake walk. For any path which you choose to follow, you should always be prepared for anything that comes your way. However if you do love what you do and have genuine interest in the field than it will certainly not feel like a burden to you, rather you will enjoy your work and take each day as a new adventure waiting to be explored. So rather than waiting for success to come your way without even putting in an ounce of effort, get up and write your own destiny.