Lyudmil Stamenov
sommario
This project focuses on developing a predictive model using real hiring data from AKKODIS to
explore and address salary stereotypes and potential biases in recruitment processes. The objective
is to analyze historical hiring data to identify patterns that may indicate bias related to salary
offers (RAL) and develop models that promote fairness and transparency. By leveraging machine
learning techniques, we aim to detect underlying trends that may not be immediately visible through
traditional analysis. The findings from this study can help organizations implement data-driven
policies to mitigate bias and ensure equitable salary distribution.
prodotti