The dataset hr_data.csv contains sample of candidates that we part of a recruitment process of particular client of ScaleneWorks. ScaleneWorks supports several information technology(IT) companies in India with their talent acquisition. One of the challenge they face is about 30% of the candidates who accept the jobs offers, do not join the company. This lead to huge loss of revenue and time as the companies initiate the recruitment process again to fill the workforce demand. ScaleneWorks want to find out if a model can be build to predict the likelihood of a candidate joining the company. If the likelihood is high, then the company can go ahead and offer the jobs to the candidates.
Cost of predicting “Not Joining” as “Joining” (FPs) cases is 3 times more than predicting “Joining” as “Not Joining” (FNs)