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This question is about what a data scientist does, what a software engineer does, and data scientist.
Data Scientist vs. Software Engineer
A data scientist is a tech professional that uses algorithms and statistics to draw insights from data, while a software engineer is someone who uses programming and engineering skills to design software.
A data scientist is a tech professional that aims to get insights from structured and unstructured data. They also write high-level code with Python or R, and they often use BI tools for data analysis and visualization. Data scientists are considered builders.
They are tasked with analyzing and understanding specific business problems, feature engineering, developing, selecting, and tuning models. And then generating insights to present to stakeholders.
A software engineer designs, develops, maintains, tests, and evaluates computer software and other software products. Their tasks include implementing technical designs, improving and maintaining existing code base, reviewing code changes, writing new codes for application, identifying issues with the software, and coordinating the installation of the software for clients.
Here are the key differences between a data scientist and a software engineer:
They can use different software programs to perform the functions of their roles
Software engineers have more fundamental software skills
Data scientists interface with stakeholders directly
Software engineers generally communicate with their peers and full stack developers
Data scientists use their skills sift through and interpret data
Software engineers focus on the creation, testing, and maintaining of software
On average data scientists have higher salaries than software engineers
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