This white paper serves as a practical career guide for aspiring data scientists and professionals transitioning into the field. It outlines the foundational technical skills required, including programming (Python, R, SQL), mathematics, statistics, machine learning, data engineering, and visualization. The guide emphasizes the importance of soft skills such as communication, collaboration, and the ability to translate technical insights into business impact. Drawing on interviews with practicing data scientists, it highlights non-linear career paths, the value of continuous learning, and the role of open-source tools and communities. The paper also provides guidance on gaining real-world experience through internships, personal projects, and open-source contributions, positioning data sci

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