Machine learning engineers build, implement, and maintain machine learning systems in technology products. They focus on machine learning system reliability, performance, and scalability. This career path requires you to have expert-level programming skills and deep knowledge of machine learning algorithms.
Data engineers design, build, and maintain data architectures for large-scale applications. They manage the entire data lifecycle: ingestion, processing, surfacing, and storage. This career path requires strong software engineering skills
Data Scientists perform sophisticated empirical analysis to understand and make predictions about complex systems. They draw on methods and tooling from probability and statistics, mathematics, and computer science and primarily focus on extracting insights from data. They communicate results through statistical models, visualizations, and data products.
Data Analysts use tools such as Excel, Tableau, SQL, R or Python to use data to answer specific questions. Analysts must have a deep understanding of their organization’s data. This career path requires you to be able to visualize data in ways that help guide major business decisions.
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