What is the difference between a Data Scientist and Machine Learning Engineer?

A machine learning engineer is required to be more skillful in software engineering, data management and information architecture as compared to a data scientist. While there is substantial relation between the two roles; the key difference lies in the focus area of these two positions. A machine learning engineer focuses on data management, coding, setting up the architecture & application design. Data scientist, on the other hand, deals in analysing of data, identifying trends and patterns and churning out valuable insights in business.

A machine learning engineer is a software engineer who specialises in building software applications that involve machine learning, usually as it is applied to predictive analytics. A machine learning engineer will usually have some kind of degree in computer science with a focus on machine learning and/or artificial intelligence.

A data scientist is a multidisciplinary professional with a very strong grasp of statistics, business, data modeling, data visualisation and machine learning, usually as it’s applied to data mining.