MisrFinTech is looking for a machine learning engineer to build a model that predicts the likelihood of loan default among customers. The goal is to assist financial analysts in identifying high-risk applicants and improving the loan approval process with data-backed insights.
Requirements:
Strong experience in classification models (Logistic Regression, Random Forest, XGBoost)
Familiarity with financial datasets and risk assessment
Ability to manage imbalanced datasets and perform proper feature selection
Experience with Python libraries like Scikit-learn, Pandas, and LightGBM
Understanding of fairness in financial models and regulatory concerns
مراحل الوظيفة
Deliveries
Clean dataset with preprocessing steps explained
Classification model with explainable results (feature importance, SHAP optional)
Evaluation metrics: Precision, Recall, F1-score, ROC-AUC
Jupyter notebook with end-to-end solution
Optional: Streamlit dashboard showing live predictions