5 jobs you can get with Python skills

Thanks to its utility across cloud, data science, machine learning, and AI, Python is one of today’s most valuable programming languages you can learn. In fact, Python was Pluralsight’s third-most-popular topic in 2025, and it’s one of the top languages to learn this year according to our 2026 Tech Forecast.

Here are some of the in-demand roles that you can land with Python skills, as well as what specific Python skills you may need to develop.

 

Why learn Python?

Python is this in-demand for a reason: it’s a highly versatile and yet easy-to-learn programming language. As you’ll see in the examples below, that versatility makes Python a useful tool across a spectrum of tasks, from software and web development to automation, artificial intelligence, and data analysis. Learning Python can open up opportunities across many types of career in technology.

But once you get past the fundamentals, it can be challenging to know which intermediate and advanced Python skills to focus on. That all depends on the role you’re pursuing. So let’s get into those.

Machine learning engineer

Machine learning engineers are the builders of AI and machine learning solutions at an organization. Sometimes considered a subset of software engineering, ML engineers specialize in designing, training, and deploying machine learning models.

Python expertise is absolutely essential for machine learning engineers. They employ skills like:

• Data processing and analysis using NumPy and Pandas
• Building and training machine learning models using libraries like TensorFlow, PyTorch, and Scikit-learn
• Data visualization using tools like Seaborn or Matplotlib

Learn more about what you need to become a machine learning engineer here!

Data scientist

At the simplest level, data scientists solve business problems using data. They accomplish this by analyzing often-complex and high-volume data, running experiments, and building predictive and prescriptive models to empower an organization to make more informed decisions and reveal valuable insights.

A data scientist may use Python to:

• Clean and sort raw data using Pandas
• Work with large datasets and mathematical operations using tools like NumPy for calculations
• Visualize data using tools like Plotly, Seaborn, or Matplotlib
• Build predictive models using tools like Scikit-learn

Learn more about what you need to become a data scientist here!

Back-end developer

Back-end developers ensure all our flashy websites and apps actually function. They focus on the server-side logic, designing APIs, handling database integrations, and managing authentication. 

Python is a powerful tool for enabling back-end developers to:

• Build web applications using frameworks like Django, Flask, and FastAPI
• Build APIs, which includes creating endpoints, handling HTTP requests, working with JSON data, and more
• Work with databases like PostgreSQL, MySQL, MongoDB, and SQLite
• Protect APIs and prevent vulnerabilities with authentication and security best practices
• Test and debug applications using PyTest

Learn more about what you need to become a back-end developer here!

DevOps engineer

DevOps engineers bridge the many gaps between software development and IT operations, supporting communication and facilitating efficient delivery across the entire software development lifecycle.

DevOps engineers may use Python in various ways to streamline operations and break down silos, including:

• Automating repetitive tasks
• Automating cloud management, often alongside tools like Ansible, Kubernetes, and Terraform
• Integrating into CI/CD pipelines to automate building, testing, and deployment
• Monitoring and alerting, parsing logs, collecting metrics, and triggering alerts

Learn more about what you need to become a DevOps engineer here!

Cybersecurity analyst

Cybersecurity analysts (sometimes also known as cyber defenders or SOC analysts) are at an organization’s front line of defense. They evaluate alerts to determine their risk, and more senior analysts will actively handle incidents and manage security tools. 

While Python skills likely won’t be what gets you a security analyst role, this role often benefits from using Python to:

• Automate repetitive security tasks, like collecting systems logs, scanning networks, and security checks
• Analyze logs and process data, often using libraries like Pandas
• Inspect network traffic and detect anomalies using tools like Scapy and Socket
• Integrate with security tools like Splunk, Elastic, and threat intelligence APIs

Learn more about what you need to become a cybersecurity analyst here!

Conclusion

Demand for Python skills isn’t going anywhere, and, fortunately, there’s a wide breadth of role types that leverage those skills. Research the roles that most align with your interests and career goals, and start learning to fill the gaps you have.