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@article{199193,
        author = {Mallela Lokesh and Konka Tarun and Shabeer V.V},
        title = {AI-Based Salary Prediction System Using Machine Learning and Feature Engineering},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {12108-12112},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=199193},
        abstract = {Accurate salary estimation is a critical challenge in modern Human Resource (HR) management. This paper presents an AI-based salary prediction system, Salary Scope, developed using Python, Streamlit, and Scikit-learn. The core research problem addressed is the absence of an interpretable, real-time, multi-currency salary prediction tool that integrates domain-driven feature engineering with a deployable web interface—a gap not addressed by prior classification-focused or NLP-dependent approaches. The system employs a Linear Regression model trained on a multi-feature employee dataset enriched through domain-driven feature engineering, including experience bonus computation (validated against industry compensation surveys), education premium mapping, location-based salary adjustment, and workload factor derivation. Feature values are derived from statistical analysis of compensation literature rather than fixed arbitrarily. Categorical variables are systematically encoded using One-Hot Encoding within a unified machine learning pipeline. The interactive Streamlit-based web interface enables real-time salary prediction with multi-currency support including INR conversion for Indian users. A modular, layered software architecture ensures maintainability and scalability. Five distinct testing strategies were employed to validate system correctness. The system bridges the gap between raw HR data and actionable compensation intelligence.},
        keywords = {Salary Prediction, Machine Learning, Linear Regression, Streamlit, Feature Engineering, One-Hot Encoding, Human Resource Analytics, Web Application, Real-Time Prediction.},
        month = {April},
        }