The Evolution from Data Scientist to Manager
Switching to the managerial position from the data scientist position poses a lot of differences in terms of duties. Data scientists are primarily responsible for working on the data and building models, whereas managers are involved in the whole data science process, being responsible for driving decision-making, defining goals, overseeing project resources, and bridging the gap between the technical and business worlds. This evolution requires a concern for both the technical as well as the exercise of management skills.
How to become Data Scientist Manager?
Data science management, or data science administration, is a term used to describe the process of organizing and effectively managing the data that is to be used in making informed decisions.
Data science has emerged as an important field in recent years; it plays a role in decision-making and business transformations. Due to the growing demand for a shifted approach in business organizations to have data-driven decision-making, a data scientist manager has become a crucial position. Besides the technical competencies, this position also involves understanding and coordinating with team members and, most importantly, leading multiple projects while aligning the outcome with stakeholders’ expectations.
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