Data science role hierarchy — 

Data science role hierarchy — 

The levels of a data scientist include four levels starting with a junior data scientist, data scientist, senior scientist, and principal data scientist. Depending on the industry and size of the company, some levels may have sublevels.

For example, a Level 2 data scientist sometimes may be broken down into data scientist I and data scientist II positions, with the second having slightly more seniority and higher pay.


The Four Career Levels of a Data Scientist:

Level 1 - Associate or Junior Data Scientist: A junior data scientist is an entry-level position. They work under the mentorship of Level 2 and 3 data scientists testing new ideas, debugging, and refactoring existing models. A Level 1 data scientist should be skilled in Python, R, research, SQL, and data analysis.

Level 2 - Data Scientists: This level is achieved typically after 1 to 3 years of experience as a Level 1. A Level 2 data scientist should be an expert in Python, R, research, SQL, data analysis, machine learning, analytical skills, teamwork, and communication skills.

Level 3 - Senior Data Scientists: Level is typically achieved after 3 to 5 years as a Level 2. A Level 3 should not just be tech-savvy and business-savvy but also understand the overall business picture, have expertise on the best types of data analytics technologies, prevent fraud, and maintain budgets.

Level 4 - Principal Data Scientist: This position is the most experienced member of the data science team with ten or more years of data science experience and is considered the final authority for all other levels of data scientists.

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