Data science as one of the greatest jobs in the contemporary technology market is considered a highly technical role more often. However, Ronald Van Loon, Director of Adversitement and an influential AI  leader, says data science is not only about statistical, mathematical, and technical work. The nature of data science-related tasks and activities also requires an individual to possess a certain vision, imagination, and creativity. These attributes incite professionals to seek answers for questions and explore their problems.

One needs to have the right passion and willingness to pursue data science and they must realize that they can't forge a strong career foundation based on hard skills (programming, mathematics, and statistics) alone. For their substantial career, soft skills are equally crucial. This has been proven by a Google research as well.

The Necessity of Soft Skills

Gaining soft skills in today's highly competitive and ambitious market is itself is a challenge. These skills cannot be taught like a hybrid skillset with other hard skills. For example, as noted by Forbes, computer science disciplines that tend to focus solely on programming and hard skills; or liberal arts curricula that foster critical thinking and creativity, but often leave graduates with non-linear career-paths.

As the aftermath of the Great Recession of 2008, most Humanities fields have experienced declining numbers in declared majors according to data from the Department of Education. There is a misconception that technical studies offer more employment options, and according to a recent poll from Harris Insights & Analytics, more than 60% of students aged 14 to 23 look for a college degree to offer financial security as a chief benefit.

Combined with the misconception that employees naturally pick up soft skills, this has led to a general overemphasis on STEM-related concentrations.

The answer is certainly no.

Top Soft Skills that Can Make Thrive in Data Science Field

Most of the market trends, insights from top business leaders, and industry data depict that as soft skills are of equal importance, therefore they should not be overlooked. The futuristic leaders, workers, and executives will need to have a hybrid skill set to foster in the extremely tech-oriented world.

Here are some of the most required soft skills, according to Tableau, that every data science professional should possess.

Critical Thinking

With critical thinking, data scientists can objectively analyze questions, hypotheses, and results and understand what resources are critical to solving a problem. They can also look at problems from differing views and perspectives.

Critical thinking is a valuable skill that easily transfers to any profession. For data scientists, it's even more important because, in addition to finding insights, you need to be able to appropriately frame questions and understand how those results relate to the business or drive the next steps that translate into action.

Effective Communication

Through this, data scientists can explain what data-driven insights mean in business-relevant terms and communicate information in a way that highlights the value of the action. They can also convey the research process and assumptions that led to a conclusion.

Effective communication is another skill that is sought just about everywhere. Whether you're in an entry-level position or a CEO, connecting with other people is a useful trait that helps you quickly and easily get things done. In business, data scientists need to be proficient at analyzing data, and then must clearly and fluently explain their findings to both technical and non-technical audiences.

Problem Solving

One can identify opportunities and explain problems and solutions with Problem Solving skills. Using such attributes, data scientists will have the know-how to approach problems by identifying existing assumptions and resources and put on their detective's hat and identify the most effective methods to use to get the right answers.

One can't even begin to be a data scientist without the skill or desire to solve problems. That's precisely what data science is all about. However, being an effective problem solver is as much a desire to dig to the root of an issue as it is knowing how to approach a problem to solve it.

Intellectual Curiosity

Through the skill of intellectual curiosity, data scientists can drive the search for answers and dive deeper than surface results and initial assumptions. This enables them to think creatively with a drive to know more and constantly ask "why" — because one answer is usually not enough.

A data scientist must have intellectual curiosity and a drive to find and answer questions that the data present, but also answer questions that were never asked. Data science is about discovering underlying truths and successful scientists will never settle for "just enough," but stay on the hunt for answers.

Business Acumen

In today's highly competitive world to have an edge against their competitors, companies must ensure their data scientists understand the business and its special needs and realize what organizational problems need to be solved and why. They can translate data into results that work for the organization.

Data scientists perform double duty: not only must they know about their own field and how to navigate data, but they must know the business and field in which they work. It's one thing to know your way around data, but data scientists should deeply understand the business—enough to solve current problems and consider how data can support future growth and success.