These are the data science programming languages that Apple uses

Welcome back! I’ve been talking about programming languages that massive companies use, now let’s talk about the data science programming languages that Apple uses! The process of me finding these languages was very simple, I went to their career page and noted the most frequent languages I saw as a requirement for their data science positions:

The most popular languages I saw were: Python, R, SQL, Java and Scala, they also required experience with Tableau, Spark,AWS and Hadoop. If that’s all you wanted to know then you’re welcome 😉, otherwise let’s get into more details 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.


Java is a very popular language used in tons of companies across the world, Apple is one of those companies. This language is an object oriented language with a large community behind it, so if you plan on learning this language, you will have a large community to help you. I imagine Tesla uses this language for their Android applications, so if you plan on developing for any of their Android apps, it might be best to know 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.

There you have it, those are most of the common languages I saw required by Apple 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 for reading!

Data Scientist / Engineer

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