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Python Developer vs. Data Scientist: What Are the Differences?

Learn about the two careers and review some of the similarities and differences between them.

Python developers and data scientists are in high demand due to the current popularity of data science and the Python programming language. Both of these roles require a high level of technical skills and experience. If you’re interested in working in either field, it’s important to understand the key differences between these two job titles. In this article, we discuss the similarities and differences between Python developers and data scientists, and we provide tips for choosing the right career path for you.

What is a Python Developer?

Python Developers create and maintain back-end architecture for web-based applications. They design efficient and scalable Python applications by utilizing libraries and frameworks. In addition to being skilled in Python, they must also have a strong understanding of HTML, CSS, and JavaScript. Python Developers are responsible for managing server-side logic and ensuring that the front-end and back-end of the application work well together. They also collaborate with other developers, designers, and QA analysts to ensure that the final product meets all the requirements.

What is a Data Scientist?

Data Scientists use their mathematical and statistical skills to analyze complex data sets to find trends, patterns and relationships. They use this information to develop predictive models that can be used to make decisions about future events. Data Scientists often work in fields such as finance, healthcare, retail and manufacturing. They may also work for government agencies or nonprofits. Data Scientists typically have a background in mathematics, statistics or computer science. They must be able to effectively communicate their findings to non-technical audiences.

Python Developer vs. Data Scientist

Here are the main differences between a Python developer and a data scientist.

Job Duties

One of the major differences between a data scientist and a software developer is the type of job duties they have. A data scientist typically has several job responsibilities, including conducting research, analyzing data, developing algorithms and modeling data. These professionals use their skills in Python and other programming languages to create programs that assist them with their work.

A software developer, however, usually focuses on creating and maintaining computer programs. They may also troubleshoot issues users have while using the programs and provide support to help users navigate the systems. Additionally, developers often monitor changes in technology and make adjustments to their programs as needed.

Job Requirements

Python developers and data scientists typically need at least a bachelor’s degree in computer science or another related field. However, some employers may prefer candidates with a master’s degree or higher. Additionally, both Python developers and data scientists should have strong programming skills and be able to use various software programs to analyze data.

Work Environment

Python developers typically work in an office setting, either for a company or as freelance consultants. They may also work from home on occasion if they’re freelancing. Data scientists often work in an office environment and spend most of their time working with data to find patterns and create algorithms. This means that data scientists usually have more structured schedules than python developers.


Both Python developers and data scientists use the Python programming language to build software and analyze data. However, their focus and responsibilities differ, resulting in the need for different skills.

Python developers typically build web applications and create user-friendly interfaces. As a result, they need to have strong front-end development skills, such as HTML, CSS and JavaScript. They also need to be able to work with databases, so they can store and retrieve the data used by their applications. Data scientists, on the other hand, use Python to analyze data and look for trends and patterns. They need to be able to use statistical methods and have a strong understanding of mathematics. Additionally, data scientists need to be able to communicate their findings to non-technical audiences, so they need to have strong writing and presentation skills.


The average salary for a Python developer is $102,448 per year, while a data scientist earns an average salary of $118,822 per year. Both of these roles may see their salaries vary depending on the type of work they’re doing, their location and their experience level. Both types of professionals may earn other benefits as part of their compensation package.


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