Google is a massive company that employs tons of data scientists, so let’s see what Google uses for their data science teams. Now, the process of me finding this information was fairly basic, I went to their career page, searched for Data Science positions, and noted the most frequent languages, packages and tools I saw them use:
Let’s go ahead and get into it!
Starting off, one of the most important things with data science is the programming side to it, these were the programming languages I saw them require the most:
This is a no brainer, tons of companies use Python as it is one of the most popular programming languages out there. This language has a ton of packages available for it for data science as well, this is probably the most important language Google uses for data science.
Next up we have R, another very popular statistical language used by Google. R’s main ability is data processing / data manipulation, there are also tons of packages available for this language as well!
Another very important language that Google uses is SQL, this is definitely the building blocks of alot of data science related projects. SQL allows us to essentially build / talk to databases, so if you’re planning on applying to Google, you will need to know this language.
Finally we have MATLAB, a fairly popular programming language used at Google as well. Here’s the thing, I think MATLAB is super important, but the barrier to entry is fairly high due to the license that’s required to code with this, I did notice that many of the data science positions didn’t really require this language.
Machine Learning Packages
Next up we have the machine learning packages, there were really only 3 that I saw as requirements for data science positions at Google.
The first package is a no brainer, TensorFlow was actually built out by Google themselves, so it only makes sense that they require knowledge with this package.
Next up we have SciKit-Learn, another very popular machine learning package. Personally, I saw a ton of data science positions require some experience with this specific package.
Lastly we have PyTorch, a machine learning package actually developed out by FaceBook. Out of al three of these packages, I saw PyTorch mentioned the least, but it was mentioned enough to get on this list.
Lastly, there were some tools I saw that Google used for their data science projects that you might need to learn as well.
First off we have Hadoop, a very popular collection of utilities that makes managing big data a bit easier. Without a doubt, this is one of the most important softwares you could probably learn for data science.
Next up we have Spark, this is a analytics engine that makes handling big data a bit easier. From all of the Google data science positions, Spark was mentioned quite a bit.
Lastly we have Apache Hive, this is a data warehousing software that gives a SQL-like interface. Similar to Spark, there were several data science positions that required knowledge with this specific software.
There you have it! Those are some of the programming languages, packages and tools that Google uses for data science, do you currently use any of these? I would love to hear your thoughts about this!
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Thanks so much for reading!