This project is to predict the probability that a data scientist will still work for a company or look for a new job, and analyze which factor could affect a data scientist to make a final decision.
Performed exploratory data analysis, data cleaning, treated data imbalance (75% dominant category), and built Logistic Regression, Lasso Linear Regression, Decision Tree, Random Forest, GBM models in R to predict the probability that a employee leave the current company (best model decision tree with MSE_test 0.1495 and AUC of 0.602).
The analysis and business implication will help companies to design strategies to retain employees. Here is a potential business recommnendation for a 50-99 company in less developed cities, it needs to consider provide them with some incentives or bonus. In addition, more team building is a good way to bond the current employees.
