In present times, becoming a data scientist is much more expeditious by attending a couple of online courses and obtaining some certifications. However, to be successful in the data scientist role, one has to focus on critical skills that take data scientists to new heights in their career.

Able to convert the business problem to data-driven solution:

Understanding the problem statement and turning into a data-driven solution is primary responsibility for any data science role, particularly for a skilled data scientist. In most of the cases, end-user doesn’t know what problems can be solved by advanced analytics vs what cannot be solved, and it is data scientist responsibility to make business teams mindful of what can be achieved.

Think like Subject Matter Expert in respective Domain:

One of the essential areas any data scientist should focus on is domain knowledge. As a data scientist, one has to deal with data in a more meaningful way to transform complex data into valuable insights & actions, and this can be achieved only with thorough domain knowledge. Having reasonable control of domain knowledge is very important in asking the right data to solve the problem and handling the data in a more precise way.

Continuously ameliorate programming skills:

Excellent programming skills are utmost important to be called as ‘Data Scientist’ unless one chooses to be in managerial roles. Mastering coding skills remains shot in the arm for a data scientist to handle any problem that can be solved using advanced analytics techniques. I have listed some of the links to improve coding skills and helps in getting hands-on individual’s choice of programming language. Although there are many automated machine learning solutions out there, none of them can replace the need for programming based data science roles. One another way to hone programming skills that require for data science roles is participating in hackathons as this allows competing with fellow data scientists and help an individual to identify areas to focus

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