In a world that strongly depends on data, demand for Data Scientists and Machine Learning Engineers has sky rocketed; leaving the job market eager to specialize in the fields of Data Science and AI without really understanding what it takes to become a Data Scientist or an ML engineer. — In order to provide clarity on this, we will begin with defining what a “Data Scientist” really is. Prior to the boom of Big Data and the internet revolution, a “Statistician” was in fact what we call today a Data Scientist. Statisticians work with formulas and data to help solve problems in different industries and sectors — they analyze data and apply mathematical and statistical techniques to help solve real-world problems. With the boom of the internet, statisticians who were capable of adapting to the changes and the fast pace of technology were then called “Data Scientists”.