Santandave961/naija-salary-ai

# NaijaSalary AI - Nigerian Salary Estimator A data science web application that estimates monthly salaries for tech professionals in Nigeria using Random Forest and SHAP explainability. Built with Python and Streamlit, deployed on Streamlit Community Cloud. --- ## Live Demo Click here to view the app --- ## Overview This project builds an end-to-end machine learning pipeline that estimates what a tech professional should earn in the Nigerian job market based on their role, experience, industry, location, and education. It goes beyond a simple prediction by using SHAP (SHapley Additive exPlanations) to show exactly which factors are driving the salary estimate up or down. --- ## Model Performance | Metric | Value | |--------|-------| | Algorithm | Random Forest Regressor | | Estimators | 200 trees | | Max Depth | 8 | | Train/Test Split | 80% / 20% | | Explainability | SHAP TreeExplainer | --- ## Features - Salary estimate in NGN with low and high range - Annual salary equivalent - SHAP chart explaining why the model gave that estimate - Salary by Job Title chart - Salary growth curve by Years of Experience - Salary by Industry comparison - Overall Feature Importance chart --- ## Input Features | Feature | Options | |---------|---------| | Job Title | Software Engineer, Data Scientist, Product Manager, Data Analyst, DevOps Engineer, UI/UX Designer, Backend Engineer, Frontend Engineer, Cybersecurity Analyst, ML Engineer, Business Analyst, Mobile Developer | | Industry | Fintech, Banking, E-commerce, Telecoms, Healthcare | | Location | Lagos, Abuja | | Education | BSc, MSc, MBA | | Company Size | Small, Medium, Large | | Experience | 0 - 20 years | --- ## Tech Stack - **Language:** Python 3 - **Framework:** Streamlit - **ML Library:** scikit-learn - **Algorithm:** Random Forest Regressor - **Explainability:** SHAP TreeExplainer - **Data Processing:** pandas, NumPy - **Visualisation:** Matplotlib --- ## Project Structure ``` naija-salary-ai/ app. …