Because data science is a popular topic right now, a common illusion arises:If there is data stored somewhere, all we need to do is hire a data scientist..He/she will certainly extract something from the data and then turn it into something valuable for us.Well, if your company’s current situation somehow relates to the description above…I’m sorry..You probably don’t really need a data scientist..At least, not yet..Let’s explore a hypothetical scenario where you hire a data scientist.Hypothetical scenario: hiring a data scientistMost data scientists I see in the job market are actually just analysts who have learned Python, R, pandas and scikit-learn in MOOCs..They took part in some Kaggle competitions and have little professional experience..And they are eager to demonstrate their knowledge in the “real world”.It’s the sexiest job of the 21st century..Nobody wants to create dashboards and reports anymore, everyone wants to work with artificial intelligence.If you post a job searching for a data scientist, tons of candidates will show up and you will probably face the following situations:Your interviews, tests and screenings will successfully select a data scientist with some machine learning engineering qualities..He/she will have good programming skills and theoretical knowledge of several algorithms and their applications.You will show him/her your “data stored somewhere”..And then will give him/her an open problem to work with..Something like: we would like to reduce default risk, or we need to increase the sales.He will try to use the data, applying models and algorithms to respond to the problem you proposed..And will probably fail.Then, you’ll start giving him tasks that should be directed to a business intelligence analyst, like designing a dashboard to track the daily sales or doing some backoffice tasks automation.After a while, your data scientist will be frustrated.. More details