Qualities of Data Scientist

The impotent qualities of a data scientist are curiosity, extremely argumentative, and judgmental.

The most important one is curiosity because if you are not curious you would not know what to do with data. Judgmental because if you have not preconceived notions about things you would not know where to begin with and where to go.Argumentative because if you have this skill then you can argue on your results and you can modify them and now you learn from the data which leads you to a better result.

The other Qualities which a data scientist needs is the comfort and flexibility with some analytic platforms; some software, some computing platform, but that's secondary. The most important thing is curiosity and the ability to take positions. Once you have done that, once you've analyzed .then you've got some answers.

The last quality of a data scientist is the ability to tell a story. Once you have your analytics and your tabulations, now you should be able to tell a great story from it. because everything is worthless if you are not able to explain your findings. your findings will remain hidden, remain buried, nobody would know. Your position in this field largely depends on the ability to tell stories.

The starting point for acquiring the qualities or skills of a data scientist is to decide in which field you are interested and in which field you want to be a data scientist for example lets say you are gaining skills in IT  field and you want to be a data scientist in the health field then in the health field data scientist a different type of skills are required so first decide it and also what is your competitive advantage.

Your competitive advantage is not necessarily going to be your analytical skills .your competitive advantage is the understanding of any field in which you can far away from the other crowd maybe it's film, music, computers, art, etc. Once you figured out this then you can start acquiring your analytical skills. What platforms you have to learn and learn those platforms, those tools would be specific to the industry you are interested in. And then once you have got some proficiency in the tools, the next thing would be to apply your skills to real problems, and then tell the rest of the world what you can do with it.