What is the key skill that the best data scientists have?

Here are some examples of variables which can be engineered:Example of an analytical database created to feed a behaviour score model that predicts customer default.STATE: Personal information feature — indicates the province/state where the customer livesAGE: Personal information feature — indicates customer’s age, calculated at the observation pointGENDER: Personal information feature — indicates customer’s genderMOB: Months on Book — months since the customer signed in until the observation pointAVG_LIMIT: Average percentage of limit use in the 12 months of observationMAX_LIMIT: Maximum percentage of limit use within the 12 months of observationPURCHASE_TOTAL: Total purchase amount within the 12 months of observationDPD_OP: days past due at the observation pointMAX_DPD: Maximum days past due within the 12 months of observation..May be negative if all invoices were paid in advance.AVG_DPD: Average days past due within the 12 months of observation..May be negative if all invoices were paid in advance.BEFORE_DUE_QTY: number of invoices paid before due within the 12 months of observation.GOOD_PAYER: Target — indicates if the customer wasn’t late with his/her invoices for more than 30 days within the 6 months of the performance window.6..It’s show time!Now we are finally talking about building a model!.You can now apply everything you learned in data science courses..Your analytical base was designed and is ready for action — in this case, data treatment and applying models.The simplest solution would be applying a logistic regression using the variables created above in order to predict the GOOD_PAYER target..The model will return a value within 0 and 1 for each customer, indicating the probability of him/her being a good payer.Remember to always interpret the result correctly:The score will indicate the probability that a certain customer won’t be late with his payments for more than 30 days within the next 6 months.Did you like it?Was this article useful for you?.Share!.Did I say anything stupid?.Correct me!.Want to add something?.Leave a comment!. More details

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