Teacher job satisfaction has emerged as a critical factor influencing teaching effectiveness, employee retention, and overall institutional performance in early childhood education. Despite the implementation of various human resource practices, many institutions continue to rely on generalized management approaches that fail to address the diverse needs of teachers. Additionally, although large volumes of teacher-related data are generated through institutional processes, they are often underutilized due to the absence of structured analytical frameworks. This study aims to address this gap by adopting a data-driven approach to analyze teacher job satisfaction and its impact on organizational outcomes.

The research employs a quantitative and analytical design using both primary and secondary data sources. Primary data was collected through a structured questionnaire administered to 130 teaching staff, while a larger dataset comprising 41,188 records with 21 variables was used for in-depth analysis. Various statistical techniques, including descriptive analysis, exploratory data analysis, correlation, and hypothesis testing, were applied to identify key factors influencing satisfaction and their relationships with performance indicators.

The study contributes to the field of Human Resource Management by providing a structured, data-driven framework for improving talent management practices. It highlights the importance of integrating HR analytics with involvement-based strategies to enhance employee well-being and achieve sustainable organizational success.

 Keywords-

Strategic Talent Management ,High involvement work practice, teacher engagement, Employee retention, Pedagogical involvement, organizational performance. Educational data analytics, workforce development, Digital tools in education.