These are the Data Science programming languages that Google uses in 2021

Welcome back! We’ve been talking about the most popular programming languages that massive companies use, now let’s go into more detail about the specific data science programming languages that Google uses in 2021. I do want to preface this whole article with this statement: programming languages are a very important piece to data science, but you will still need to understand the different packages, libraries, mathematical components and softwares that these companies use as well, with that being said let’s get started!

The Languages

In order for me to find these languages I went over to Googles career page, searched up their data science positions and noted the most common languages I saw:

these languages were: Python, R, SQL, SAS and MATLAB, they also required experience with: Machine learning (Tensorflow, Keras, Pytorch), Pandas, Spark, Google Data Studio and Tableau. If that’s all you wanted then you’re welcome 😉, otherwise let’s get into more details of these languages!

Python

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, with Pandas and Numpy, these are very popular data processing packages with Python. Below is a section from their career page mentioning experience with Python:

R

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. Below is a section from Google’s career page mentioning experience with R:

SQL

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). 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. Below is a snippet from a Google data science position mentioning experience with SQL:

SAS

Next up we have SAS, another statistical language / software used heavily in data science. This language is used in many different companies including Google, the main disadvantage to this language is that it does require a license (similar to MatLab), because of this there is a smaller community behind this language compared to R and Python, I also saw that there are less tutorials and documentation on SAS than those other languages as well. Regardless, there were a few positions at Google that did prefer experience with using SAS:

MATLAB

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 allowed 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). Below is a section from a Google data science position mentioning experience with Matlab:

There you have it, those are most of the common languages I saw required by Google 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.

As Always

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.

Thanks so much for reading!

Data Scientist / Engineer

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