Jobs You Can Get When You Learn Python

You learn and practice Python – everything to improve your day-to-day work or to help you change jobs. Well, the science itself is fun, but ultimately, all of these efforts have to pay off. In this article, I propose five types of positions to consider for when you have learned and mastered Python. Ready for a change? See which one might be for you.

You've probably heard a lot about why you should learn Python, and about how it is one of the fastest-growing programming languages in the world. Most of the market research shows that there is a growing demand for people who know Python, so if you spend your effort learning it and are good at it, you won't run out of jobs to look for. You don’t believe it? My friend Rebecca wrote an excellent article in which she gathered arguments for why you should learn Python in 2021. There, you will find statistics and research results that confirm my words.

Still not convinced? Just visit any site with job postings - like LinkedIn, Indeed, or Monster. You will find a lot of openings for various positions. But which one do you choose?

It all depends on what suits you best and what you want to do. Maybe you are into creating applications, or maybe you are a fan of data processing and analysis. Either way you choose, you can safely use Python.

I’m going to describe five different types of positions below. There are many more options, so I chose the ones for which Python would be the basis for the job or at least would be one of the main aspects of the job.

1. Python Developer

This is one of the first positions that come to mind with learning Python. As a Python developer, you will be creating apps. That means writing code. If you choose this career path, you will primarily solve problems for your company and its clients using Python. You will build or modify software that makes the work easier and more effective for others.

Depending on the focus, your position may simply be called a programmer, mobile application developer, web developer, etc. In all cases, you will be using Python. A Python developer may also be responsible for other tasks associated with the development of software applications. For example, you may also be responsible for product documentation and other tasks within the process of implementation.

Initially, you will almost certainly be a part of a development team. Over time, as you gain more experience, you will have the opportunity to work more independently.

The pay for Python developers usually depend on the skill level. A junior Python developer, someone just entering the programming world with little experience in writing code and a few projects in his/her portfolio, can earn about $60,000. A senior Python developer who knows the secrets of Python and other languages will earn up to $110,000 a year (Glassdoor.com). Pretty good.

2. Data Analyst

These days, data is the basis for running a business. Every company collects them, but not all of them know how to use them well. Data analysis can give a company an edge over the competition and allow it to make better strategic decisions. Python is great for this.

As a data analyst, you will be responsible for compiling reports and conclusions from the metrics gathered in databases. Although it sounds very serious, it is actually a very interesting and increasingly popular activity. It was once associated with mostly staring at charts; now analysts are an extremely important element of the company.

In addition to analytical skills and coding in Python, presentation skills are also useful, since the reports will have to be presented to the management of the organization.

A data analyst using Python has an average earning of about $67,000 per year. If you are experienced and good at it, you can earn up to $100,000 (Glassdoor.com) . Even the simplest analysis shows that it pays off.

3. Data Scientist

This is a slightly different approach to data. While data analysts produce metrics and reports, data scientists work more broadly and more deeply with data. In this position, you will create predictive and classification models and will forecast trends that may affect the company's development in the future. Using your knowledge about data analysis, statistics, and model building, you will inform the business of various scenarios and set the foundations for its strategies. Data scientists are often also responsible for conducting A/B testing and for analyzing the results of implemented solutions.

Most large companies employ data scientists. Their services are in great demand, so you can expect pretty good salaries. But be careful – for this role, you need to know a lot and need to continue to learn to stay relevant in this rapidly changing profession. You have to build up a powerful skill set. But it's worth it, because it is a very lucrative and interesting job that almost guarantees employment stability. There is still a shortage of these experts in the market.

Let me give you an example – do you use Netflix or Amazon to watch movies and TV series? Have you noticed that these platforms make recommendations on specific productions that you might like? They are based on algorithms that use data collected about you and about your preferences on an ongoing basis.

There are also models that tell Facebook what ads to show you. Someone has to develop and manage this. Data scientists work on these algorithms and try to figure out what's best for the audience.

A good data scientist must have a good portfolio. Check out this article in which you will find 11 Tips for Building a Strong Data Science Portfolio With Python.

What kind of pay can you expect as a data scientist? As Glassdoor points out, you can earn $113,000 on average. The best will earn up to $150,000. Sweet! Imagine the money – don't you feel like learning Python right away? If so, I recommend our Python Basics track. This is the best start in the programming world.

4. Data Engineer

For everything a data scientist develops, the data used must first be collected and processed by someone. This is where data engineers come to the rescue. Their task is to create an appropriate structure for data acquisition, storage and processing. The enormous amounts of data coming from everywhere have to be gathered into formats that can later be easily analyzed. Data engineers also create data pipelines and flows, and they make sure that the processing of big amounts of information is performed correctly and as efficiently as possible.

The cooperation between data engineers and data scientists can also extend beyond providing the input data for analysis. A data engineer may help implement the models created by data scientists. As a data engineer, you may also be responsible for the deployment of data science products, including AI and machine learning models, in the production environment.

The work of data engineers does not benefit only the data scientists. The data analysts and the business analysts who compile insights may also use data prepared by data engineers to suggest appropriate actions on a daily basis.

To become a data engineer, you can definitely start with Python. Over time, your skillset will grow and expand with tools for Big Data (e.g. Apache Spark), SQL, and scripting languages like Bash that facilitate process automation.

These advanced skills lead to very good pay. According to Glassdoor, data engineers can expect annual salaries averaging $103,000. Advanced experts can get over $158,000 a year for their work.

5. Python Freelancer

This category is much wider. Since Python programming doesn't have to mean working for just one organization, many Python developers choose to earn their living through accepting remote projects from different clients.

There are tons of sites where you can find opportunities on a per-project basis. Usually, you have to log in and create your profile. I recommend UpWork.com, Freelancer.com, or Indeed.com. Make sure to prepare a good portfolio – the potential client doesn't know you. It is by reviewing your completed projects that the client will judge whether or not you are qualified.

Pay attention to learning Python, because every line of code, every completed course, and every exercise or project makes you a better programmer. That’s a big part of how you will be able to accept larger projects for more money as a freelancer.

Want to know more about it? Read the article “How do you Become a Successful Freelance Software Developer?”. There are tons of great tips and tricks to help you in your career.

Get Python Jobs!

So, that’s a compilation of five job types that use Python. There are many more! Not just that, Python is often required for other IT positions. For example, to get a job as a database administrator, it is often helpful if you could code in Python.

Python can also be useful in your day-to-day work, even if you do something else. For example, maybe you are a marketer or a finance professional. If you work with databases and need to process data efficiently and easily, Python will definitely work.

Made the decision to learn Python? See what you need to do to learn Python quickly and painlessly. Wondering what working with Python will look like in practice? Well, you will first need to demonstrate your skills during an interview, so here you will find 15 common Python interview questions. Check to see if you know everything you need to know.

My friend Magda described a typical day in the life of an IT team. Imagine yourself in a team like this. Pretty cool, if you ask me! Coffee, coding, jokes, and good pay. What more could you want? Learn Python now!