6 Python Career Paths to Consider in 2025
Consider these well-paid and fascinating career paths as you continue your Python journey.
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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.
professional certificate
Google Data Analytics
Get on the fast track to a career in Data Analytics. In this certificate program, you’ll learn in-demand skills, and get AI training from Google experts. Learn at your own pace, no degree or experience required.
4.8
Beginner level
Average time: 6 month(s)
Learn at your own pace
Skills you'll build:
Spreadsheet Software, Data Management, Data Analysis, Business Communication, General Statistics, Business Analysis, Data Visualization, SQL, Data Cleansing, Developing a portfolio, Creating case studies, Metadata, Data Ethics, Spreadsheet, Data Collection, Data Calculations, Data Aggregation, Rstudio, R Markdown, R Programming, Presentation, Tableau Software, Sample Size Determination, Data Integrity, Decision-Making, Questioning, Problem Solving
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.
professional certificate
IBM Data Science
Prepare for a career as a data scientist. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from IBM. No prior experience required.
4.6
Beginner level
Average time: 4 month(s)
Learn at your own pace
Skills you'll build:
Data Science, Generative AI, Predictive Modelling, Data Analysis, Model Selection, Data Visualization, Python Programming, Pandas, Numpy, Dashboards and Charts, Matplotlib, dash, Relational Database Management System (RDBMS), Cloud Databases, Jupyter notebooks, SQL, regression, Clustering, SciPy and scikit-learn, classification, Machine Learning, CRISP-DM, Data Mining, Methodology, K-Means Clustering, Github, Jupyter Notebook, Data Science Methodology, Rstudio, Deep Learning, Big Data, Quering Databases, Data Generation, Interviewing Skills, Resume Building, Career Development, Job Preparation
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.
professional certificate
IBM AI Engineering
Get job-ready as an AI engineer . Build the AI engineering skills and practical experience you need to catch the eye of an employer in less than 4 months. Power up your resume!
4.5
Intermediate level
Average time: 4 month(s)
Learn at your own pace
Skills you'll build:
Deep Learning, PyTorch (Machine Learning Library), Transformers, LLMs, Neural Networks, Keras (Neural Network Library), Artificial Intelligence, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Artificial Neural Network, Tensorflow, Supervised Learning, Regression Analysis, Artificial Intelligence (AI), keras, Machine Learning, Unsupervised Learning, Natural Language Processing, Generative AI, PyTorch functions, Positional encoding and masking, Text Mining, Applied Machine Learning, Language transformation, Generative pre-trained transformers (GPT), Bidirectional Representation for Transformers (BERT), Data Manipulation, Predictive Modeling, Computer Vision, Data Processing, Scientific Visualization, Verification And Validation, Data Import/Export, NLP Data Loader, Hugging Face Libraries, Tokenization, Jupyter, PyTorch, Large Language Models, Scikit Learn (Machine Learning Library), Classification And Regression Tree (CART), SciPy and scikit-learn, classification, Dimensionality Reduction, regression, Matplotlib, Feature Engineering, Random Forest Algorithm, Statistical Modeling, Statistical Machine Learning, Clustering, Machine Learning Algorithms, Python Programming, Activation functions, Softmax regression, Convolutional Neural Networks, Performance Tuning, Hugging Face, Instruction-tuning, Reinforcement learning, OpenAI, Proximal policy optimization (PPO), Direct preference optimization (DPO), ChatGPT, Time Series Analysis and Forecasting, Generative Adversarial Networks (GANs), Convolutional Neural networks CNN, Reinforcement Learning, TensorFlow Keras, Retrieval augmented generation (RAG), In-context learning and prompt engineering, Application Frameworks, LangChain, Open Source Technology, Chatbots, Vector databases, Application Development, TensorFlow, Linear Regression, Logistic Regression, Gradient Descent, Statistical Methods, Databases, Gradio, User Interface (UI), Document Management, Generative AI applications, Data Storage, Unstructured Data, Vector database, Generative AI for NLP, Machine Learning Methods, N-Gram, PyTorch torchtext, Word2Vec Model, Sequence-to-Sequence Model, Pretraining transformers, LoRA and QLoRA, Fine-tuning LLMs
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.
professional certificate
Microsoft Cybersecurity Analyst
Launch your career as a cybersecurity analyst. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from Microsoft. No prior experience required.
4.7
Beginner level
Average time: 6 month(s)
Learn at your own pace
Skills you'll build:
Cloud Computing Security, Network Security, AI in Cybersecurity Analysis, Threat mitigation, Penetration Test, Computer Security Incident Management, Compliance techniques, threat intelligence, Encryption techniques, Information Security (INFOSEC), Cybersecurity, Record management, Data Management, Cloud Architecture, Cybersecurity planning, Computer Architecture, Operating Systems, Cloud Computing, Cybersecurity strategies, Asset Management, Access Control, Threat Model, Security Analysis, Regulatory Compliance, Event Management, Security Response, Security Testing, System Testing, Identity governance, Enterprise security, Access Management, Authentication Methods, Computer Network, Network Monitoring
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.
professional certificate
Meta Back-End Developer
Launch your career as a back-end developer. Build job-ready skills for an in-demand career and earn a credential from Meta. No degree or prior experience required to get started.
4.7
Beginner level
Average time: 8 month(s)
Learn at your own pace
Skills you'll build:
React.js, Back-End Web Development, Cascading Style Sheets (CSS), User Interface (UI), Hypertext Markup Language (HTML), Web Development, Front-End Web Development, Bootstrap (Front-End Framework), JavaScript Frameworks, Responsive Web Design, HTML and CSS, Web Design and Development, Full-Stack Web Development, Databases, Server Side, Software Testing, Version Control, Unit Testing, Git (Version Control System), Web Applications, API endpoints, Application Development, Authentications, Django (Web Framework), Database Management, User Accounts, API Design, Restful API, MySQL, Scalability, JavaScript, Production environments, Virtual Environment, HTML, Application Programming Interface (API), Cloud Computing, Command-Line Interface, Github, Software Development, File Management, Software Versioning, Software Configuration Management, Linux Commands, Bash (Unix Shell), Unix Commands, Linux, Software Development Tools, Computational Thinking, Algorithms, Computer Science, Computational Logic, Pseudocode, Data Structure, Programming Principles, Data Structures, Technical Communication, Software Visualization, Problem Management, Communication, Extensible Markup Language (XML), Filtering and ordering, Performance Tuning, Data Validation, Development Environment, Authorization (Computing), Authentication and authorization, JSON, Debugging, REST APIs, Serializers and deserializers, Software Documentation, Web Servers, Application Frameworks, Design a web application, Database Development, Data Modeling, Application Security, Maintainability, Build a data model, Computer Programming, Object Oriented Programming (OOP), Integrated Development Environments, Cloud Hosting, Application Programming Interfaces (API), Test Driven Development (TDD), Python Programming, Database Design, Query Languages, Database (DBMS), Data Integrity, Database Management Systems, Relational Databases, database administration, NoSQL, SQL
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
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.
course
Programming for Everybody (Getting Started with Python)
This course aims to teach everyone the basics of programming computers using Python. We cover the basics of how one constructs a program from a series of ...
4.8
Beginner level
Average time: 18 hour(s)
Learn at your own pace
Skills you'll build:
Computer Programming, Computer Programming Tools, Critical Thinking, Problem Solving, Programming Principles, Python Programming, Software Engineering, Theoretical Computer Science
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