You're in the midst of a job search. You know that you're a suitable individual for the position. What makes you confident about it?

That's simple: you have all of the professional skills required for the position, from course certification to industry knowledge as well as technical skills. But your competition may also have such skills!

The question is: do you possess the soft skills that hiring managers are looking for?

Employers want employees with soft skills that cannot be taught at the workplace but are required for grabbing suitable jobs.

The workplace is no longer about who completes the task first; instead, it is about who can bring more profit to the organization.

This blog explains the role soft skills play during the recruitment for data science role.

The Significance Of Soft Skills In Data Science

“Stanford Research Center, Harvard University, and Carnegie Foundation discovered that 85% of job success driven from impressive soft skills and 15% driven from technical skills”

In a competitive job market, data science is among the most sought-after fields, and consequently, there is a huge competition for jobs.

Being an evolving field, data science includes both technical skills with soft skills like problem-solving abilities and effective communication skills. While technical skills including programming, machine learning, and statistics are vital, soft skills are quite critical to get success in the field.

To become eligible for data science jobs, expressing complicated technical concepts in a manner that non-technical stakeholders can grasp is crucial. This includes the ability to present facts concisely and explain the consequences of the data to the audience.

Furthermore, data science projects often need collaboration with various team members, and the ability to operate successfully in a team is essential. This involves the ability to listen to and consider other people's ideas, as well as the ability to direct and manage a team.

In short, the importance of soft skills in data science cannot be underestimated.

In-Demand Soft Skills to Succeed As Data Scientist

The field of data science is growing remarkably and there is a huge demand for data scientists. Thus, you should know the necessary data science skills to learn. Developing these abilities will help you stand out from the crowd, as well as unlock the door to future opportunities.

Essential skills that you should develop to be a successful data scientist.

1. Effective Communication 

The skill that is highly demanded in the organization is effective communication. Data scientists in business must be skilled at data analysis and know how to clearly explain their findings to both non-technical and technical audiences. 

This crucial skill promotes data literacy throughout an organization and increases data scientists' ability to leave an impact.

2. Business Acumen

Every industry has its own set of goals, datasets, and limits. For data scientists to be successful, they should first gain know-how of the business in which they are using their expertise.

Before understanding the significance of data, a data scientist should also have a good understanding of data visualization.

Though few metrics, such as profits and conversions, are present across industries, several key performance indicators (KPIs) are extremely specialized. This data constitutes the industry's business intelligence, which is utilized to comprehend where the company is and the past trends that have led it there.

3. Proactive Problem Solving

You can't be a data scientist unless you can find the solutions to problems. That’s exactly what data science is all about. Being a successful problem solver, on the other hand, is as much about finding the root cause as it is about knowing how to solve a problem.

In the data science role, Problem solvers swiftly identify difficult situations that are not seen, and then immediately work on an idea of how they will address it and what approaches will provide the right answers.

4. Critical Thinking

Critical thinking is a vital skill that may be required in any profession. It's quite crucial for data scientists since, in addition to finding insights, you need to frame questions correctly and comprehend how the results stay relevant to the business.

When dealing with data interpretations, it's equally critical to assess situations objectively before creating an opinion.

5. Intellectual Curiosity

Data comes in a variety of shapes and sizes, and it is never served on a silver platter. The expected results may not be clear with the data you have; yet, with enough manipulation, you may be able to achieve the desired results.

In data science jobs, a data scientist must be intellectually curious to accomplish this. In any situation, keep asking what-if questions and pushing yourself to try new things. You may get amazed at the results you would receive.

Conclusion

The soft skills mentioned above are necessary for any data scientist to succeed in their job role. Understanding that data science projects are fundamental to business operations underlines the importance of honing your non-technical abilities.

When applied in a research setting, you would need these skills to be successful. As you build your technical skills, ensure that you also have the potential to apply these skills in the real world.