Different Data Science Roles Explained (by a Data Scientist)
#DataScience #KenJee #DataScienceRoles
In this video I explain the different data science roles that exist under the broader data science umbrella.
Visuals By The Data Professor. Check out his channel here: https://www.youtube.com/channel/UCV8e2g4IWQqK71bbzGDEI4Q
Before explaining these, it is important to understand the data science life cycle.
1) Data Collection
2) Data Cleaning
3) Exploratory Data Analysis (EDA)
4) Model Building
5) Model Deployment
The difference in the positions is largely based on which part of the data science life cycle that they cover
Data Scientist – Generally covers the whole lifecycle. Needs the broadest array of skills.
Data Engineer – Mainly covers the data collection and cleaning phases
Data Analyst – Mainly covers the data cleaning and exploratory data analysis phases (can be flexible towards collection or model building)
Machine Learning Engineer (MLE) – Usually focuses on model building and model deployment.
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