5 Types of Jobs That Use Python

If you want a new job in tech, we’ll come out right now and say it: Python is a great language to learn. It’s versatile, in-demand, and Python skills are remarkably easy to acquire. In fact, it’s one of the easiest programming languages_{Is Programming Hard? Make It Easy with Python} to master. Learning Python is so fruitful in terms of landing tech jobs that the question, “What job can you get with Python?” might be better asked as “What jobs in tech don’t benefit from a knowledge of Python?”

All right, we’re getting excited and hyperbolic, we know. But the core fact remains: industries as diverse as healthcare, entertainment, and artificial intelligence all use Python. It’s flexible and powerful, and careers in Python are remarkably stable.

So let’s get into it. Here are five jobs you can get knowing Python as well as the ins-and-outs of how these jobs use Python.

Python Developer

What they do

As the first entry in our list of jobs that require Python, this likely comes as no surprise. We’re also putting this first because it’s the fuzziest role. “Python developer” can change based on industry and specialization. People in these positions can find careers in numerous industries where they tackle diverse tasks — web development, software development, AI engineering, the list goes on. Python developer job postings also tend to blur the lines among different, more specific Python-focused roles, so this can be a source of confusion when you start looking for jobs that use Python. 

So what do Python developers do? It varies — make sure you read job descriptions in detail to see if the company’s looking for someone with a background in data science or someone more focused on software engineering.

How they use Python

Here’s your favorite answer: it depends. If you end up focusing on web applications, you might use Python to build the app’s server-side logic and handle other back-end tasks. If you land a job more akin to that of a data engineer, you might apply Python programming to tasks such as data ingestion (yum) and transformation.

This will also differ depending on your industry. A developer in healthcare_{From Nursing to MedTech: How To Switch Your Career} will apply their Python skills differently when compared to someone working for a music streaming service_{From Tourism Sales to Data Science at Spotify: TripleTen Grad Rachelle Perez Lands a Career in Tech}, for example. Even if the know-how matches, the on-the-ground application of, say, data analysis and visualization skills, will express itself differently.

Salary estimate: 

$123,073 (Indeed)

Data Analyst

What they do

Nowadays, companies collect mountains of data. But in its raw state, it’s unusable. That means that a data analyst_{Data Analysis Career Guide for 2023: Tasks, Skills, and How to Become a Data Analyst} goes to where it’s all stored (databases, spreadsheets, surveys, etc.) and pulls all the information together. Then, once they have it all, they need to clean it (e.g., get rid of duplicates and cut out bad entries) and preprocess it so that it is standardized for the next step: visualization. Once the data is visualized, an analyst can dig into it to come up with recommendations on whatever they’ve been tasked with analyzing.

How they use Python

Even starting from data collection, Python is present. Data analysts can use it to automate interaction with data sources. From there, they can also apply it to clean the data thanks to Python libraries such as Pandas_{Why Data Analytics Is Impossible Without Pandas}. And guess what: it can also be used to assist in visualization: Matplotlib_{Matplotlib: What It Is And Why Should You Use it} and Seaborn are Python libraries that make these tasks easy. In short, data analysts can find themselves using Python in nearly every stage of their work.

Salary estimate: 

$82,000 (Glassdoor)

Machine Learning Engineer

What they do

In terms of jobs that use Python, this one might be getting the most interest recently. It’s easy to see why (and it’s not just because of the entry-level average salary of $129,334). They’re at the frontiers of computer science today. Day-to-day, they often do similar things to data analysts; collecting and processing data. But then they take this to a new level by using this data to train models and algorithms that can undertake analysis and produce results independently. Yup, we’re talking about AI.

How they use Python

As you might guess, in the initial phases of handling data, machine learning engineers apply Python just like data analysts do. But then, once things differentiate, they implement Python libraries like scikit-learn for machine learning tasks, and if they go even further, they use PyTorch for deep learning. Basically, they use additional Python capabilities to help computers make increasingly complex decisions.

Salary estimate: 

$161,554 (Indeed)

DevOps Engineer

What they do

It’s sort of in the name — these techies bridge development with operations. That means they connect the software team (the people writing the code) to the IT team (the people who take that code and deploy it). They make this simpler by automating workflows and infrastructure as well as maintaining continuous integration and continuous deployment (CI/CD) to ensure quick software releases and quick updates. In short, they play the role of glue among diverse tech teams.

How they use Python

All that automation? That’s where Python comes in. It’s great at configuring servers, powering deployment pipelines, and managing infrastructure. In fact, it can even be used to enable infrastructure as code thanks to tools like Ansible, which allows complex changes to occur without overwhelming manual intervention. Naturally, it is also a key language in which CI/CD processes are written.

Salary estimate: 

$126,026 (Indeed)

Web Scraping Specialist

What they do

Here’s a truism: companies need data. They need it for business intelligence. They need it for market research. And websites are troves of data; that’s where these workers come in. They retrieve and parse data from websites. Then, like with the previous data-heavy roles, they clean it, preprocess it into formats primed for analysis, and store it. This also often entails data management — i.e., making sure that the data retrieved doesn’t run afoul of privacy and legal considerations.

How they use Python

Using Python libraries such as Beautiful Soup and Scrapy, they extract information from HTML content, where the core information of a website is usually presented. If it’s more difficult to parse, e.g., if the site is built of dynamic content, they’ll use Python in combination with Selenium, another library. Then, once they have this data, they’ll use Python to store the data in a unified place — a CSV file or a database, for example.

Salary estimate: 

$113,000 (Glassdoor)

Land a Python career

If one of these professions has caught your eye, you already know the first step: mastering Python. And in only 8 months, you can learn it top to bottom in our Data Science Bootcamp. But don’t take our word for it — check out the testimonial on how one of our grads mastered Python with us_{Changing His Career, Not His Company: Gor Mikayelyan’s TripleTen Story}.