6 Essential Competencies that Separate Junior Data Scientists from Seniors
In 2021, 365 DataScience conducted a study of thousands of LinkedIn profiles to analyze trends in the data science field. Notably, less than 2% of individuals have stayed at the same job for over 5 years, and the median time spent at a job for a data scientist was 1.7 years. This turnover rate is a concern in the industry, with many data scientists citing “lack of role clarity” as a top challenge.
If you’re facing ambiguity in roles within your team, creating a competency framework can provide clarity and structure. This framework outlines the behaviors and skills necessary for different levels of expertise, separating juniors from senior data scientists.
A competency framework defines the behaviors that are essential, valued, recognized, and rewarded within specific roles or seniority levels. By implementing this framework, you can establish clear expectations and paths for growth within your data science team.
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