Welcome back! I’ve talked about some of the most popular programming languages that massive companies use, now let’s talk about the data science programming languages that Amazon uses. The process of me finding these languages was pretty easy, I went over to their career page and noted the most popular languages that were required in their data science positions:
The most popular languages I noticed were: Python, R, SQL, Scala, C / C++ and MATLAB, they also required experience with: AWS, PowerBI, Tableau, GPU programming and machine learning packages (Tensorflow, Pytorch, etc.). If that’s all you wanted to know then that’s it, otherwise let’s go into more detail about these languages!
Starting off, Python is by far one of the most popular programming languages right now, it’s used for tons of different things, one of these things is data science. Some data science positions were hybrid data science / software engineering positions, Python is a great balance of both of those cases. Most of these positions required experience, under their Nice to have column, with Pandas and Numpy, these are very popular data processing packages with Python.
Next up we have R, one of my favorite programming languages. This is a statistical language, I personally feel like R is my go to language for Data Science, it does suffer from one specific area, machine learning. Although R has a few machine learning packages (Tensorflow), most of the documentation / tutorials out there rely on Python, so this means that a majority of companies will end up using Python instead of R, should this sway you away from learning R? Absolutely not, many companies still rely on R programmers to process data.
Next up we have SQL, this is technically a query language, but it’s still a very valuable language to learn. This is not a substitute to any other language on this list, you must learn SQL and a combination of other languages on this list. This language essentially allows you to create and manage databases, this is essentially where our data is stored. To keep it simple (and to motivate you to learn this), I would probably say that every single data science position i’ve ever seen has required some knowledge of SQL (or NoSQL, MySQL, etc.). Basically, you have to know SQL in order to become a data scientist, luckily for you, it isn’t extremely hard to learn this language.
Scala is another pretty popular language focused around object oriented / functional programming. This language is pretty much built off of Java, but it still has some features that maybe better to a Data Scientist than Java. Also, a huge tool that’s used within the Data Science / Data Engineering community is Apache Spark, this tool is built on Scala. Since Amazon also required experience with distributed computing, it’s no surprise they mention Scala as a requirement.
MatLab is another popular programming language that’s used for a lot of different data processing projects. I definitely haven’t created anything super crazy with this language personally (besides some linear interpolation projects), but I do understand the value that this language holds. This language is great for data analysis, algorithm development, building desktop / web apps, and one of my favorite features of this language was coding in the cloud, it allow me to not necessarily have the MATLAB software installed on my personal machine but I was still able to code / compile within a web browser (just like Google Colab).
C and C++
Lastly, C and C++ are very popular languages that i’m sure everyone knows about. C is one of those languages that many software engineering positions (even some data science positions) are going to require it regardless. C++ is another very popular language, this language was originally known as “c with classes”. Since it’s origination, it’s pretty much been it’s own language. You can build out a lot of different things with both C and C++: Games, Applications, Operating Systems, etc.
There you have it, those are most of the common languages I saw required by Amazon for their data science positions. Like I mentioned before, even though the programming languages are important, the frameworks and technologies they require are very important to the positions as well.
if you have any suggestions, thoughts or just want to connect, feel free to contact / follow me on Twitter! Also, below is a link to some of my favorite resources for learning programming, Python, R, Data Science, etc.
Here are some of my favorite courses, books and so much more. Most of these are affiliate links which help me create…
Thanks so much for reading!