Data science is an incredibly in-demand profession. It plays a key role in a variety of sectors, including marketing, healthcare, entertainment, and security, and is an occupation that requires a lot of skill and patience.
Data scientists utilize a range of important skills, often acquired through comprehensive training and educational programs. Below, we’ll take you through some of the skills you’ll need as a data scientist, and why it’s important to develop these skills as a priority.
Data visualization isn’t simply the ability to imagine how data looks, it also refers to the art of transforming complex numbers and information into various charts and resources that can be used for a multitude of purposes.
For example, you may need to take a pool of data from company sales over the past year and transform it into a board meeting-friendly pie chart or graph. It’s important to simplify complex data into a format that the average person can understand and work from.
Data visualization skills help not only directors and board members but also researchers, students, marketers, and salespeople. Many of us learn visually and prefer consulting graphics or videos to poring through walls of text.
Therefore, if you have a knack for simplifying and representing data in a way that’s visually appealing and digestible, you’re already on your way to a successful career as a data scientist.
Simple communication skills are a must when working in data science, as you’ll be working with a variety of people across a range of different industries.
For example, you may need to communicate information to many different departments of a company. The way you present data to marketing will be much different from how you present it to engineering.
Communication skills are always important when working in teams, and even though data science may often be solitary work, there will be times when you must collaborate with others. For work to be completed efficiently, it’s important to communicate effectively and to set expectations early on.
Nearly all data science jobs will require you to translate and transform data for different audiences. A degree from Baylor University gives you the chance to know what to expect in a variety of data science roles through an engaging and diverse curriculum.
Critical thinking is more than just being able to solve complex problems at short notice. What’s perhaps most important is being able to look at problems from an objective standpoint. You’ll need to be able to take practical approaches to resolve data-based conundrums, which will mean removing emotion and prior bias from your problem-solving.
This also means you’ll need to think on your feet. What programs or tools are required to solve the problem? Do you need to bring in support from elsewhere in your company? Are the datasets you’re using necessarily enough to help resolve your issues?
It’s safe to say that critical thinking is a virtue, not just a skill. Analyzing and solving puzzles independently and objectively framing them within the scope and endgame of your project is a talent that will help you find myriad jobs down this career path.
Communicating what data says is one thing. What about cleaning it up? Data wrangling is all about ensuring the information you have to hand is suitable for processing. This requires an exceptional eye for detail – for example, you must be able to spot errors in complex data sets.
Many businesses and organizations suffer from “data hygiene” problems. They may have thousands of duplicate records on customers or members, for example. Data may be neutered wrong, filed wrong, or simply outdated.
As a data scientist, you’ll need to quickly spot errors and potential hygiene issues ready for clean-up. You should also have some skills using database systems and programs, so you can easily organize information into digestible units.
Data wrangling is also a skill that will help you drill deep into the specificities of your role. For example, the data you come to work with may not be “dirty,” simply irrelevant. Therefore, the ability to quickly discern what’s relevant and superfluous will help you work efficiently and with a high degree of accuracy.
Knowledge of programming languages is a huge benefit in data science. However, there’s also an inherent skill behind programming, and that is being able to discern where problems are occurring amid a mass of seemingly endless digits and actions.
If you are laser-focused in your ability to spot errors and fix dataset problems, you’ll likely succeed as a programmer as well as a data scientist. Programming skills allow you to quickly adapt to changes and frequently test code without getting frustrated.
Businesses will look for data scientists who are unflappable in their approach to number crunching – those who are willing to keep trying new ways to solve problems and who won’t be deterred by disappointments or interruptions along the way.
The ability to learn multiple programming languages and use them effectively for different purposes will, too, prove highly useful in terms of finding roles in data science.
Data science is a varied field that carries a huge range of exciting challenges. While you may not yet know which data science course to take, there are at least a few skills and attributes you can sharpen before enrolling.
Above all, as a data scientist, you’ll need to be calm in the face of complex problems and puzzles. You’ll need to communicate clearly, and must always be willing to learn from mistakes. Apply yourself well, and you’ll have incredible prospects and job security for life.