5 Key Skills of a Data Scientist

If you’re thinking about moving into the booming field of data, don’t be caught off guard when considering what skills you should have under your professional tool belt. Since data science is a newly celebrated territory, here are a few key skills to help clarify what you’ll need to be successful in the field. You can also check out our post on the Top 5 Resources for Aspiring Data Scientists to see the type  of tools data scientists can use for help. 

The ability and desire to solve problems and think analytically.

If you don’t have intellectual curiosity, then the field of data science might not be for you. Many people might think joining this field solely for the moolah could be the ticket to a life of luxury, but if you’re not passionate about intellectual expansion and critical thinking, then you should cross data science off your list of potential careers.

Finesse in the communication department.

Once you’ve learned the jargon, you’ll quickly realize that your non-data science colleagues aren’t quite able to speak your language. Being able to translate technical information into non-technical terms is crucial to efficiently create solutions to problems while working with a team.  

You think like a data scientist.

Employers look for individuals who maintain higher-level thinking and are able to see beyond the problem itself. Don’t be surprised if you’re asked data-driven problems during an interview. A skilled data scientist will have intuition about which data sets are important and which pieces of information will be useful for coming to an insightful, concise solution.

Basic understanding of mathematics and statistics.

As a data scientist, you’ll have to analyze and interpret large sets of data. More importantly, your analysis will be used to determine what to do with the data and which techniques you should (or should not) use to approach the problem.

You have a keen eye for details.

Data science isn’t a “that’s good enough,” sort of profession. You’ll be sifting through lots of tedious bits of information, and many times the data can be messy or difficult to work with. It’s incredibly useful to be able to spot imperfections in data and then correct it.

Afraid you’re lacking in one of these areas? Don’t worry. Each skill will continue to strengthen with practice and an ambitious attitude. While data science requires a multitude of other, more technical skills (see our data science curriculum for more information) having these core competencies can put you well on your way to landing the dream job or that promotion.