How To Ask The Right Questions As A Data ScientistTo Define a Problem StatementAdmond LeeBlockedUnblockFollowFollowingDec 7Before we talk about how to define a problem statement by asking the right questions as a data scientist, let’s try to understand why asking the right questions is so important.Long story short, when I first started my first data scientist internship, I was very excited with the project and just wanted to get my hands dirty as soon as possible, without a clear understanding of the big picture.I understood the problems that I was trying to tackle..Only after two weeks of data cleaning and analysis did I realize that I made a wrong assumption of the data — all because of my lack of understanding of the problems and data.This is my little story.And I believe asking right questions and defining problem statements are some of the challenges faced by many beginners in data science (including me).You see..I hope that this would re-define or help in your method in some ways to approach these challenges.Let’s get started!How to define a problem statement by asking the right questions?(Source)Admit it or not, defining a problem statement (or data science problem) is one of the most important steps in data science pipeline.A problem well defined is a problem half-solved— Charles KetteringIn the following part, we’ll go through the four stages to define a problem statementAll questions should be geared towards this direction to gain a better understanding of a project before formulating a problem statement.1..Period.Short but not sweet.It is our task to help them frame the problem into a data science problem statement by really putting ourselves in their shoes and see things and problems from their perspective.In other words, we need to have empathy.Ask questions that can help you gain a better and deeper understanding of the problem as stakeholders have domain knowledge in the problem.. More details