6 Python Career Paths to Consider in 2025

Written by Coursera Staff • Updated on

Consider these well-paid and fascinating career paths as you continue your Python journey.

[Featured Image] A young businesswoman, who knows python, is giving a data analytics presentation of the business plans and strategies to improve feedback and customer experience.

Learning Python is an incredibly useful skill if you want to pursue a tech career in 2024. Python is one of the most popular programming languages in the world—in fact, it was the third most commonly used programming language among developers worldwide in 2023 [1]. 

This language powers the programs behind Netflix’s recommendation algorithm to the software that controls self-driving cars. It’s used to develop many different programs and isn’t specialized for any specific problems. Python’s versatility and beginner-friendly nature make it one of the most widely used programming languages today.

Let's take a look at six potential careers that requires Python.

What types of career paths can I pursue with Python skills?

Because Python is a general-purpose language, it can be used across data science, software and web development, automation, and machine learning. It is used to develop websites, software, and applications, as well as in data analysis and task automation. Even those who aren’t developers, like scientists, accountants, and product managers, can use Python to organize finances, code research data, and more.

Simply put, Python is used to write programs that solve problems in web development, software testing, automation, data analysis, and machine learning.

6 Python career paths to consider

Here, we cover six career paths you can consider that require Python expertise.

1. Data analyst

Data analysts collect, clean, and interpret data sets to solve problems. They can work in industries like business, finance, medicine, government, and technology. Data analysts might answer questions such as:

  • What type of customers should we target in our next marketing campaign?

  • What patterns in behavior are linked with fraud? 

A data analyst may use Python to develop predictive models and produce data visualizations. Most commonly, they’ll use a combination of Microsoft Excel or Google Sheets, SQL, and Tableau to analyze data. Advanced data analysts will use libraries like NumPy or Pandas, and machine learning tools like TensorFlow or PyTorch. No matter your focus as a data analyst, your Python skills will be put to good use.

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Google IT Automation with Python

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Read more: Python or R for Data Analysis: Which Should I Learn?

2. Data scientist

Data scientists solve business problems by using data to answer them. They often solve these problems by developing predictive models for forecasting and theorizing based on large data sets. 

A data scientist finds patterns and trends in data to reveal insights and inform strategy. They use programming languages like Python, R, SAS, and SQL to analyze data, creating algorithms and models to forecast outcomes. Data scientists use Python to develop machine learning techniques that can, in turn, improve the product or service at hand.

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IBM DevOps and Software Engineering

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Software Engineering, Python Programming, Application development, Web Application, Flask, Artificial Intelligence (AI), CI/CD, Continuous Integration, Continuous Development, Infrastructure As Code, Automation, Software Testing, Test-Driven Development, Behavior-Driven Development, Test Case, Automated Testing, Kanban, Zenhub, Scrum Methodology, Agile Software Development, Sprint Planning, Software Architecture, Agile and Scrum, Software Development Lifecycle (SDLC), Openshift, Docker, Kubernetes, Containers, Cloud Native, agile, Devops, TDD/BDD, Observability, Telemetry, Monitoring, logging, Tracing, Representational State Transfer (REST), Cloud Applications, Microservices, serverless, Open Web Application Security Project (OWASP), security, Cloud Computing, Hybrid Multicloud, Iaas PaaS Saas, Data Science, Data Analysis, Numpy, Pandas, Distributed Version Control Systems (DVCS), Git (Software), Github, open source, Cloning and forking, Shell Script, Bash (Unix Shell), Extract Transform and Load (ETL), Linux, Linux Commands

3. Machine learning engineer

Machine learning engineers research, build, and design the artificial intelligence (AI) responsible for machine learning and improving existing AI systems. This career path requires knowledge of Python and other programming languages, statistics, communication, collaboration, and project management.

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HTML, UI/UX design, JavaScript, Cascading Style Sheets (CSS), React, Version Control, Github, Bash (Unix Shell), Web Development, Linux, Web Development Tools, HTML and CSS, Responsive Web Design, Front-End Web Development, User Interface, React (Web Framework), Application development, Web Application, Web Design, Accessibility, User Experience (UX), Data Structure, Computer Science, Algorithms, Communication, Pseudocode, Test-Driven Development, Object-Oriented Programming (OOP), Unit Testing, Debugging

Read more: 9 Best Python Libraries for Machine Learning

4. Cybersecurity analyst

Cybersecurity analysts protect computer networks from cyber attacks and threats. They take actions to prevent attacks, defend against cyber threats, and respond to security breaches when they occur. This career path plays an important role in protecting an organization’s data and personal information. 

Cybersecurity professionals frequently use Python to assess and define against such threats, often using it to create models for natural language processing (NLP) or automating tasks. Cybersecurity analysts might use Python to build NLP and AI models that protect networks and software against breaches, theft, loss, or unauthorized access.

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Meta Back-End Developer

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5. Back-end developer

One of the most popular career paths for those with Python skills is back-end development. Back-end developers work on server-side software, which comprises everything that you can’t see on a website or application. They take appropriate measures so websites perform correctly and promptly, focusing on the symbiosis of databases, application programming interfaces (APIs), servers, architecture, and back-end logic. They must be familiar with languages like Python to build a website or app's structure and ensure the back-end performance is responsive to front-end user requests.

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IBM Full Stack Software Developer

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Generative AI, Django (Web Framework), Object Relational Mapping (ORM), Relational Database (RDBMS), SQL, Back-End Applications, Web Development, JavaScript, Web, Cascading Style Sheets (CSS), Openshift, Docker, Kubernetes, Containers, Cloud Native, Node.Js, Full Stack Development, Web Application, Cloud Computing, Hybrid Multicloud, Devops, Iaas PaaS Saas, Data Science, Data Analysis, Python Programming, Numpy, Pandas, Career, Software Engineer, Coding Challenge, interview Preparation, Full Stack Developer, Distributed Version Control Systems (DVCS), Git (Software), Github, open source, Cloning and forking, Software Engineering, Software Architecture, Agile and Scrum, Software Development Lifecycle (SDLC), React (Web Framework), Front-end Development, User Interface, Server-side JavaScript, back-end development, Computer Science, express, Application development, Flask, Artificial Intelligence (AI), Representational State Transfer (REST), Cloud Applications, Microservices, serverless, Software Development, Code generation, AI prompts

Read more: Being a Python Developer: What They Can Do, Earn, and More

6. Database administrator

Database administrator is another career path ideal for those looking to apply their Python skills. This role is responsible for setting up the database structure and applications behind the scenes according to a company’s needs, such as database security or documentation, data storage, or system administration. Database administrators ensure the company’s data and networks are secure, organized, and accessible.

Read more: Your Database Administrator Career Guide

Is Python the right language for me?

Not sure if you should learn Python or another programming language? Take a look at these reads to compare and contrast:

- Python vs. C++: Which to Learn and Where to Start

- Python vs. Java: Which Should I Learn?

- Ruby vs. Python: Pros, Cons, and Where to Start

- MATLAB vs. Python: Comparing Speed and Syntax

- Python vs. C#: Which Language Is Best for AI?

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You can learn the basics of Python in two to six months, depending on how much time you devote to learning. 

Start advancing your Python skills today

Prepare for a career that utilizes Python by advancing your skills with Coursera. Consider enrolling in the Python for Everybody Specialization offered by the University of Michigan. In this program, you'll learn how to develop programs and gather, clean, and visualize data using Python. Upon completing this Specialization, gain a shareable certificate to include in your CV, resume, and LinkedIn profile.

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Updated on
Written by:
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