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In the era of big data, the rapid growth of data science has revolutionized how organizations collect, analyze, and utilize data. However, this surge in data-driven innovation brings significant challenges, particularly regarding data privacy and ethical considerations. As individuals increasingly share personal information through digital platforms, safeguarding their privacy becomes paramount. Data breaches, misuse of sensitive data, and algorithmic biases can harm individuals and society, raising urgent ethical concerns. This paper explores the fundamental principles of data privacy and ethics in data science, emphasizing the need for transparent, accountable, and fair practices. The discussion includes privacy-preserving techniques, such as anonymization and encryption, and examines ethical frameworks like fairness, accountability, and transparency. Addressing these considerations ensures that data science can harness its potential while safeguarding individuals' rights and societal values.