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Your Career Path from Learning Python to CEO

Python is a popular programming language and one of the most sought-after skills in today’s tech industry. Find out what career paths open up to you if you know Python well!

The Python programming language has an extensive variety of applications in web development, mobile and game development, data science, and Artificial Intelligence. It’s also a relatively easy language to learn. People who have never programmed before or want to step into IT choose Python. As a result, its dominance keeps increasing; Python is preferred by tech giants like Google, YouTube, Netflix, Facebook, IBM, and many others.

All this adds up to a language that is definitely worth learning. If you are new to Python, I recommend starting with our Python Basics track. This is a set of three online Python courses to get you started in writing code and thinking like a programmer. Plus, our interactive console lets you test your code in real time and achieve effective hands-on learning.

Once you take the first step into learning Python, there are different career paths that await you. All these paths are in demand and will likely continue to be. Their initial steps are similar, but as you move up the career ladder, different paths require different specializations. There are also other skills that come into play on your way from zero to CEO.

In this article, we will discover just two of the promising careers you can pursue after learning Python. We will be going over the positions based on a vertical career ladder. Although the titles might slightly differ depending on the company, the job description reveals the expected skills going up the ladder.

Data Science

Let’s start with one of the hottest fields in recent years: data science. Python is by far the most desired language in the data science ecosystem, where new tools are almost always compatible with Python first. Furthermore, Python has a rich selection of third-party libraries that facilitate data science workflows. Check out this article that explains how data scientists use Python for more information.

Career Path after Learning Python

A typical career path for data scientists looks something like this:

  • Internship: This step is quite similar to an internship position in most professions. In this position, you learn by completing simple tasks. A basic understanding of Python (as well as other data science tools and programming languages) is enough for this role.
  • Junior Data Scientist / Data Scientist: At this level, you will need an understanding of Python’s data structures. You should be able to write simple scripts and debug code. You are likely to spend lots of time with Python’s data analysis and manipulation libraries, such as Pandas and NumPy, so knowing them is important as well.
  • Senior Data Scientist: Now you'll have a solid understanding of Python’s advanced features, such as decorators, collections, exception handling, and so on. You should be able to write entire scripts and have hands-on experience with orchestration tools like Airflow and Docker.
  • Lead Data Scientist / Data Science Manager: From this point on, soft skills (as well as very strong technical skills) become very important. Good communication and organization skills and being able to lead technical teams are crucial to this kind of role.
  • Head of Data Science: You will be leading an entire team of data scientists, analysts, and engineers. Your tasks will probably not be assigned to you by someone else. You’re more likely to be defining business problems and outlining data-based solutions.
  • CTO/CEO: If you work at a company that mainly focuses on data science and analytics, you can reach a C-level position. With enough experience and ambition, you can even start your own company and become a CEO.

You can follow a similar career path if you start as a machine learning engineer or data engineer. For instance, an experienced data engineer can work well as the head of data science or can start their own company.

If you choose this path and start to apply for jobs, this article will help you interview for a job in data science.

Software Development

Being a software developer or engineer is not only a lucrative and interesting profession, it also offers the possibility of becoming a CEO someday. Below is a typical career path for a software developer or engineer. It can be applied to a career in any programming language, but our focus here is Python.


  • Internship: A working knowledge of Python’s basics and an understanding of programming in general are usually enough to get an internship in this field.
  • Junior Software Developer/Engineer: You will need to be comfortable writing and reading Python scripts. Depending on the company you work for, you may need to be comfortable working with some Python frameworks. For instance, if you are in web development, you will probably need to work with Django and Flask. Streamlit is a more recent app framework that’s rapidly gaining popularity. If this career interests you, check out our list of Common Interview Questions for Junior Python Developer Jobs.
  • Software Developer/Engineer: In most cases, you will need a couple of years of professional experience to take the junior out of your title. The tasks are similar to what juniors do, but a mid-career software developer needs less supervision and takes more responsibility.
  • Senior Software Developer/Engineer: To become a senior Python developer, you will need several years’ professional experience with frameworks and very strong Python skills. You will be designing, testing, and developing new features. You should also possess leadership and team management skills, as you will mentor or guide junior developers.
  • Principal Software Engineer: When you become a principal software engineer, your job is not limited to one programming language and is more about guiding design processes. As stated in this ZipRecruiter article on principal engineer roles, “You guide the software design process and inspect software programs to make suggestions for improvements. Principal software engineers also process complex data and may need to enforce software design, development, and maintenance requirements.”
  • VP of Engineering / Director of Engineering: At this level, both your technical and leadership skills should be exceptional. Your main task will be building teams that will design, create, and test the software systems and products your company needs.
  • CTO/CEO: This is where you lead an entire company from a technical or executive point of view.

Job titles might vary by company, and there might be some other roles in between the ones listed above. Moreover, you do not have to follow a strict order of steps in your career ladder. The point here is that Python is a great language to start your career in IT, software development, or data science. It has the potential to help you climb the career ladder.

Learn Python and Start Your Journey

These are just two of the very promising career paths available to skillful Python programmers. A quick Google search is enough to see the high number of open positions. If you plan to build a career in these fields, Python might be the best investment you can make. You can start your journey up the career ladder with our Learn Programming with Python track. It introduces you to the fundamentals of programming, so you do not need to have any prior experience with IT. This track consists of 5 fully interactive Python courses, carefully organized and presented for beginners.

Career Path after Learning Python

Even if you are not going to be working in any of these fields, learning Python will provide you with a high return on investment. Python is not only for professional programmers; it can improve your daily admin work by automating tedious tasks. You can also use Python to grow your business. If you are still undecided, here is a comprehensive article on why you should learn Python in 2022.

The next question that naturally comes to mind is how to learn Python. There are a ton of resources out there. Although it seems like a good thing to have such a rich selection of materials, it can be a disadvantage if not used wisely. Find a carefully designed and well structured course if you want an efficient learning experience. And remember to practice what you’re learning by writing actual Python code – something that all courses feature.

Take a look at the jobs you can get when you learn Python and start learning today!