HR analytics has emerged as a transformative force in modern human resource management, enabling organizations to move beyond intuition-driven decision-making toward data-informed strategies for talent acquisition and employee retention. This research paper investigates the role of HR analytics in enhancing talent acquisition efficiency and strengthening employee retention outcomes across contemporary organizations. Drawing upon secondary data from industry reports, peer-reviewed literature, and HR technology surveys spanning 2020 to 2025, the study explores how predictive analytics, workforce planning models, and data-driven recruitment frameworks influence hiring quality and reduce voluntary attrition. The findings indicate that organizations leveraging advanced HR analytics tools report up to 35 percent improvement in quality-of-hire metrics and 28 percent reduction in voluntary turnover rates. Theoretical foundations including the resource-based view of the firm, human capital theory, and the evidence-based HRM framework are applied to evaluate existing analytics practices. The paper identifies key dimensions of HR analytics — descriptive, predictive, and prescriptive — as central pillars of strategic talent management. Recommendations are provided for HR practitioners and organizational leaders seeking to embed analytics capabilities within talent acquisition and retention strategies.