Saying there are a ton of programming languages out there feels like an understatement. If you are looking to begin a career in data science, it is important to realize that not all of the options will provide you with the same amount of value from a career perspective.
By choosing the best programming languages for data science, you can make sure you have the skills necessary to excel in the field. If you aren’t sure which ones deserve your attention, here is what you need to know.
Python Leads the Pack
When it comes to the data science field, Python is the programming language more employers want to see on a candidate’s resume. In comparison to some other options, Python is highly versatile and scalable, making it a more attractive option for a wider range of projects.
Since Python is more general, it can be used in more situations. This leads many tech pros and companies to favor this language, as flexibility and adaptability are often highly coveted.
Plus, more data science professionals are relying on Python. In fact, over the past two years, data scientists and analytics professionals have been forgoing alternatives to use Python more often, leading to a significant amount of growth from a userbase perspective.
Consider R as Well
While Python is one of the most sought-after languages for data science roles, that doesn’t mean you should ignore R. It isn’t as scalable as Python – something many data scientists cite as a drawback – and is a more specialized language, but it is firmly present in many data science platforms. As a result, hiring managers may favor candidates who bring both to the table, even if they don’t list Python and R in the vacancy announcement.
Plus, you should not be surprised if you encounter R during your data science career even if your current or next employer does not task you with programming in R. While it isn’t as prevalent as Python, it still has an audience and is present in many existing applications.
If you learn R after getting a grip on Python, you are particularly well equipped to excel in the field and could increase your earnings potential in the data science field. Gaining experience in both is ideal, especially if you want to be seen as a top candidate by hiring managers.
However, if you only have the time and resources available to learn one, Python is the wiser choice. After all, you can always learn R down the road, giving you a chance to add something new to your repertoire when the need arises.
If you would like to find out more or are seeking out a new data science position, the staff at The Squires Group can help. Contact us to speak with a member of our knowledgeable team today and see how our data science career path expertise can benefit you.