“Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it” — Dan Ariely

Type A Data Scientist v.s. Type B Data Scientist

• Type A Data Scientist: The A is for Analysis.

  This type is primarily concerned with making sense of data or working with it in a fairly static way. The Type A Data Scientist is very similar to a statistician (and may be one) but knows all the practical details of working with data that aren’t taught in the statistics curriculum: data cleaning, methods for dealing with very large data sets, visualization, deep knowledge of a particular domain, writing well about data, and so on.

• Type B Data Scientist: The B is for Building.

  Type B Data Scientists share some statistical background with Type A, but they are also very strong coders and may be trained software engineers. The Type B Data Scientist is mainly interested in using data “in production.” They build models which interact with users, often serving recommendations (products, people you may know, ads, movies, search results).

I wish I had known this earlier. In fact, as an aspiring DS(출세지향주의 데이터 과학자), it is very useful to keep this distinction in mind as you make career decisions and choices.

personally, my background is electronic automation & semiconductor engineering, so i would like to be DS as type B based on coding

Some notes about a nice ariticle from Medium which is for aspiring data scientists and people who are completely new to the field