Scientists and engineers (data and otherwise) have always been like cats and dogs, oil and water. A simple web search of “scientists vs engineers” will lead you to a lengthy debate about which group is more prestigious.
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In the slow process of developing machine learning models, data scientists and data engineers need to work together, yet they often work at cross purposes. As ludicrous as it sounds, I’ve seen models take months to get to production because the data scientists were waiting for data engineers to build production systems to suit the model, while the data engineers were waiting for the data scientists to build a model that worked with the production systems.
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