“Microsoft has incompatible versions of CSV files between its own applications, and in some cases between different versions of the same application (Excel being the obvious example here).” Eric S. Raymond We have all been there: you are assigned an exciting new data science project, you talk to your enthusiastic clients, generate grand ideas and visions, can’t wait to sit down and write the first lines of code and then it happens.
Whether you have your next data science interview lined up and don’t know what questions you should ask when it is your turn or you are preparing for a day of work shadowing and want to make the most of it. In any case, you don’t want to waste your chance to ask the right questions and get a good picture of what you can expect from your potential future job.
If you are a data scientist or plan on becoming one, you probably know this short sensation of unease in your stomach every time you see somebody on the internet claim that data science is ripe for automation. Just yesterday I read the following question directed at a data scientist in a discussion on Hacker News: Can you please describe what part of your job CANNOT be automated?