As many tech-centric fields are, data science is ever-changing, and so are the niches within the occupation. COVID-19 didn’t affect data scientists as much as some other industries, but for many their work had to be conducted from a remote office setting, and that trend in and of itself created new demands for data scientists who specialized in web and cloud-based technologies.
As a whole, the big data industry was worth just under $140 billion in 2020 and is expected to grow to $229 billion in 2021. With numbers and growth like that, it’s no surprise that many individuals are pursuing careers in data science. Standing out can be difficult if you only check the so-called “required” boxes of getting a bachelor’s in data science and having an internship under your belt, and adding these skills to your repertoire can be the difference.
A master’s degree in data science is, of course, one way to do this and is a good idea for both new graduates or individuals looking to make lateral moves within the industry. In addition to advanced education, polishing these 5 skills can set you apart from the stiff competition within the ever-changing field of data science.
“New” Programming Languages
“R” you aware that in the last five years the programming language Python has eclipsed R as the most widely used in data science? More than half of data scientists use Python every day, so if you have yet to become a master in the language, the time is now. R is still relevant, as well, and an ability to use both is all-but necessary. SAS is the third most frequently used language in data science, and if you need a new study and are well versed in R and Python, SAS should be the pick.
Advanced AI (Machine Learning)
Artificial intelligence is also one of the fastest-growing sectors of data science, and industries from sports to healthcare are utilizing AI more and more to streamline their processes. Machine learning is an aspect of AI that, as the name would suggest, involves programming machines so they can “learn” as they go. A common-use example would be when a shopping website offers someone other products because “people who bought what you’re buying also bought these.” The computer has “learned” what to recognize similar purchases.
An aspect of data science that was exemplified by the pandemic and relative stay-at-home orders, cloud computing, is the process of storing and sharing information on a “cloud” server that can be accessed from anywhere by people with the right credentials (even from a smartphone in many cases). The cloud computing market is expected to more than double in the next four years, from $371 billion last year, to $832 billion by 2025. With that in mind, being able to showcase expertise in cloud computing is a surefire way to stand out.
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Though not related to the job, the digital world is causing business communications to be a lost cause for many individuals entering the workforce. Even most 25-year-olds have had a smartphone since they were children, and while that implicit familiarity with tech certainly has its advantages when it comes to data science, it has proven detrimental to some in regards to person-to-person communications. Polishing up on things like eye contact, professionalism, and general office etiquette could make them the deciding factor for two otherwise-equally-qualified candidates.
Innovation is always in high demand in a field that moves forward as quickly as data science is right now, and being an expert mathematician shows employers that you have potential to really help out on the development side, ultimately helping set your entire team ahead of whatever curves may be next in data science.
This list is not exhaustive, and creative minds can find their own ways to stand out by staying informed on industry standards and trends, and taking a few chances on yourself!