Important Soft Skills to Have as a Data Scientist

Data scientists are one of the most sought out hires today. They sit between the goals of the business and the map to get there. The nature of data science jobs require scientists to not only be technically astute but also possess the necessary soft skills to help them excel in their roles. These soft skills go a long way in ensuring the day-to-day and overall success of data science projects. Well-rounded data scientists are able to critically analyze situations, make decisions and communicate the results effectively to stakeholders.

Below, I have highlighted some relevant soft skills a data scientist should have to achieve success:

Communication skills

Part of your duties as a data scientist would be to communicate your findings, verbally or in writing, or even give feedback to clients and stakeholders on the progress of your analysis and approach. It is important that you are able to communicate your insights from your data science projects in a clear and understandable way to people who have little to no technical knowledge. How well you communicate might be a defining factor for how successful you are as a data scientist.

Detail orientation

One critical skill needed for dealing with data is attention to detail. It may be difficult to excel as a data scientist if you tend to have the habit of glossing over things and overlooking details. The majority of the interesting insights you would find in data would only come about by being detail-oriented and looking at every single possibility or outcome.

Empathy

The goal of data science is to draw insights from data in order to solve problems and drive positive change. At the center of these problems are often people. As a data scientist, you need empathy to understand and reason with the people directly affected by the problem you may be trying to solve. Understanding what matters to the stakeholders, helps you understand what variables and insight matter most to be able to actually drive the change you want to make.

Interpersonal skills

Data science is almost always applied in domains and that means that you would interact with a plethora of people. While communication may facilitate the transfer of knowledge between people, interpersonal skills focus on the relationships you have with people. This is extremely important because running a data science project requires the assistance of people in different fields. Gaining access to new data, ideas, funds or resources can be achieved just through strong bonds with people.

Critical thinking

Gathering, analyzing and making sense of data is not as easy as it seems. There are points where at each stage in the data science process, you may have to make decisions. What data can I use? What is the right model to use? What is the right visualization to use to tell the right story? All these are critical decisions that need to be made to be able to achieve desired results. It may surprise you how one wrong decision can throw a whole project off. At each point in the process, critical thinking would guide you and your team towards success.

Intellectual curiosity

Data comes in all shapes and sizes and never comes prepared on a silver platter. The results you might want to arrive at may not be obvious with the data you have; however, with enough manipulation, you might be able to arrive at the desired results. To be able to achieve this, it is important for a data scientist to be intellectually curious. In any situation, continue to ask what-if and challenge yourself to explore different avenues. You may be surprised at the outcomes you would arrive at.

A business mindset

One main goal of data science is to leverage business data to reach a particular goal. It is imperative, therefore, as a data scientist to have a good level of business acumen. Understand how the business runs, understand what the goals of the business are, understand what the processes of the business are and understand what the demands of the industry are. Understanding all these things would place you in a better position to be able to look at data and focus on the parts of the data that are important to the specific business or industry you are in. This way when you present to stakeholders of a business, you present more than just numbers — you present a means to achieve their business goals.

Teamwork

Most Data scientists find themselves working with software engineers, managers, business owners and most importantly end-users and customers. Teamwork is a very important skill to have as a Data scientist because you will almost never work in isolation or alone, you can bet on that. You would need to learn how to work with people from diverse backgrounds and with a diverse set of skills. You would need to build various skills such as tolerance, learning to give constructive feedback, transparency amongst others, if you are to succeed as a team player.

Logical reasoning

When it comes to data science, thinking logically is paramount. It really is all about the numbers and facts. To be able to draw accurate insights from data, you need to stick to insights that the data you have produced. You should not infuse your personal desires into the results and make conclusions that are contrary to the results the data itself produced. Stick to the facts because they tell the real story.

All of the above are essential soft skills that can help any data science succeed in their role. Understanding that data science projects are intrinsic to business processes, emphasizes the need to develop your non-technical skills. Even if applied in a research setting, you would need many of the above skills to be able to succeed in your research. As you develop your technical skills, ensure that you develop the skills you need to actually apply them in the real world.

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