What is the key difference in focus between a Data Scientist and a Data Analyst regarding expected outcomes?

Data Scientists focus on predicting what will happen using machine learning algorithms, while analysts often focus on describing what happened using existing tools and reports.

The fundamental distinction between a Data Scientist and a Data Analyst lies in their temporal focus and methodological approach. A Data Analyst primarily uses established tools and reports to look backward, aiming to describe or summarize past performance, trends, or events within the available data. In contrast, the Data Scientist employs more advanced statistical modeling and programming skills, often leveraging machine learning algorithms, to construct predictive models designed to forecast future outcomes or behaviors. This difference mandates a stronger mathematical background for the Data Scientist role, often leading to higher compensation compared to general software engineering or analysis roles.