This data analysis project develops a predictive model to estimate salaries in the field of Data Science and Artificial Intelligence. Using advanced machine learning techniques, the system analyzes factors such as experience, geographic location, technical specialization, and work modality to generate personalized salary estimates.
- 🎯 Personalized Salary Prediction: The model predicts salaries in USD based on multiple professional profile variables.
- 🌍 Comparative Analysis: Compare salaries across different regions, experience levels, and specialties.
- 📈 Interactive Visualization: Dashboards and graphs to display salary trends and projections.
- 🎓 Career Recommendations: Personalized suggestions to improve salary prospects.
- 💻 User-Friendly Web Interface: A Streamlit application that makes interaction with the model easy and intuitive.
-
Data Cleaning and Preprocessing
- Transformation of categorical variables
- Creation of derived features (work-life balance index, automation risk index)
- Salary normalization by cost of living and experience level
- Segmentation by region and industry sector
-
Exploratory Data Analysis
- Identification of salary trends by specialty
- Correlation analysis between technical variables and compensation
- Regional and experience-level difference analysis
- Evaluation of the impact of work modalities (remote, hybrid, on-site)
-
Model Development
- Evaluation of various algorithms (Linear Regression, Random Forest, Gradient Boosting)
- Hyperparameter optimization using grid search and cross-validation
- Feature selection to improve model accuracy
- Performance evaluation using RMSE, MAE, and R² Score
-
Application Deployment
- Development of an interactive interface with Streamlit
- Integration of the optimized predictive model
- Generation of personalized career recommendations
- Visualization of salary projections
The project is deployed as an interactive web application using Streamlit, making complex data insights accessible to all users regardless of their technical background.
- Interactive Dashboard: Visual exploration of salary trends with dynamic filters
- Personalized Salary Predictor: Input your professional profile to get tailored salary estimates
- Career Path Analyzer: See how different career choices affect compensation
- Technology Stack Analysis: Discover which skills are most valuable for your role
- Salary Growth Projections: Visualize potential earnings over a 5-year period
👉 Launch the Data Salaries App to explore the interactive salary prediction tool.
- Implementation of more advanced feature selection techniques
- Incorporation of temporal data for long-term trend analysis
- More precise segmentation by specific industries
- Integration of emerging skills data and their impact on compensation
- Model enhancement to reduce RMSE and increase R² score
- 🐍 Python: Core for data analysis and model development
- 📊 Pandas/NumPy: Data manipulation and processing
- 🤖 Scikit-learn: Machine learning algorithm implementation
- 📈 Matplotlib/Seaborn: Data visualization
- 🌐 Streamlit: Development of the interactive web application
- 📦 Pickle: Model serialization
This project demonstrates how advanced data analysis can provide valuable insights into salary trends in the Data Science field. The developed model serves as a tool for professionals seeking salary references and for organizations aiming to establish competitive compensation structures.
This project is licensed under the MIT License - see the LICENSE file for details.
- ✅ Commercial use
- ✅ Modification
- ✅ Distribution
- ✅ Private use
- ❗ No liability or warranty
The MIT License is a permissive license that allows you to freely use, modify, and distribute this software, both in private and commercial applications, provided that the original copyright notice and permission notice are included in all copies or substantial portions of the software.