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The minimal difference that helps you understand what Data Scientist and an ML engineer would do in their day-to-day work. Data Science is the generic term, that fuses data and science in a right proportion. Data Science is the art of dealing with problem-related to contextual data which may be structured or unstructured. Fortune companies started consuming actionable insights from their data lake and so big data comes into the picture and the opportunities to handle those data are challenging. Data Scientist deals with data engineering, statistical modeling, and convey their findings through beautiful charts. Wherein ML engineers are responsible for delivering the outcomes of the model predictions and the engineering behind them. They write services to encapsulate the models, provide security for them, take care of deployment and if required optimize their performance and so. That's how data scientists and ML engineers differ in their work in nature.
The minimal difference that helps you understand what Data Scientist and an ML engineer would do in their day-to-day work. Data Science is the generic term, that fuses data and science in a right proportion. Data Science is the art of dealing with problem-related to contextual data which may be structured or unstructured. Fortune companies started consuming actionable insights from their data lake and so big data comes into the picture and the opportunities to handle those data are challenging. Data Scientist deals with data engineering, statistical modeling, and convey their findings through beautiful charts. Wherein ML engineers are responsible for delivering the outcomes of the model predictions and the engineering behind them. They write services to encapsulate the models, provide security for them, take care of deployment and if required optimize their performance and so. That's how data scientists and ML engineers differ in their work in nature.