Roles in Data Science
Understand the essential roles in data science such as data engineer, data analyst, ML engineer, and MLOps engineer. Learn how each contributes to data collection, analysis, modeling, deployment, and maintenance within the data science pipeline to support effective decision-making.
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Data science is a diverse field that uses different methods to uncover valuable insights from data. It includes various roles, each playing a part in turning raw data into useful information. There are four important roles within the domain of data science: data analyst, ML engineer, data engineer, and MLOps engineer. Each position plays a crucial role in the data science process, from problem definition to model deployment and maintenance.
Data engineer
Data engineers are the architects of the data science pipeline. Their primary responsibility is to ensure that data is collected, stored, and processed effectively. This involves building and maintaining data infrastructure, data pipelines, and databases. Data engineers play a pivotal role in the data collection and data cleaning phases. They design systems to extract data from various sources, transform ...