With the demand for data science talent growing, more and more professionals are taking up the course seeing the lucrative market. Yes, there is a need for more data scientists to fill the shoes, but with people skills, of course. Data science is not a particular field, nor is it relegated to a particular line of business or industry. It is a combination of several disciplines that emphasize on evaluating data and determining the best solutions based on them. Thus, a data scientist can make an impact just about in any industry and in any organization.
If you are heading down the path of becoming a data scientist or are a burgeoning data scientist, you must know that there are aspects outside the technical curriculum that you need to focus on. That is, there are data science skills that exceed disciplines. You must know these skills if you want to grow as a data scientist.
With that in mind, we have prepared a list of five strong people skills that you need to learn if you want to thrive as a data scientist.
Let’s get started.
#1 Time Management Skills
It is not all about how you manage your time, but other people’s calendars as well. Well, nobody is asking you to become a personal assistant to other people. However, the thing is, when people are flooded with information, their attention span gets shorter. And to make it worse, excessive use of social media worsens people’s attention span. It becomes difficult to get people to commit. Holing people accountable can literally save your career and, ultimately, the business. You can send out meeting invites, reminders, and new invites when the employees miss their appointments. Nobody will pay you extra for this, but if you want to be a good product manager, you will have to keep your team members on their toes.
#2 Behavioral Science Skills
Some people collapse under pressure, while others thrive. Have you ever wondered how and why? While some businesses resist any change, some embrace innovation. Why? What we are trying to say is that you need to understand that the science of learning is making its way into mainstream training for employees. There are a number of fields that influence employee learning. You have to introduce a culture of learning in your organization with real-world applications. Based on the latest behavioral science findings, the learning programs focus on the following key principles:
- Create deep learning
- Target learners who are ready
- Give support
- Measure the learning
- Dodge multi-tasking
- Establish relevance
- Let learners to teach
- Create time to apply the training
#3 Communication Skills
Since we are living in a globalized world, it is quite common to work in a diverse environment. In such multicultural cases, you can’t assume that everybody is able to speak English fluently. You need to develop your skills in switching up your vocabulary, depending on who you are speaking to. This is something that most data scientists lack. This is viable for both social as well we technical aspects. For example, if you want to get insight from the engineering department, you must understand their terminologies. It is not just about the language; it is all about how you communicate with your team and customers in a way that they understand everything. Communication is not just about conveying your message, but it is also about how you receive a message.
#4 User Experience Skills
UX skills or user experience skills have become paramount in today’s business world. Whenever dealing with businesses and people, you need to understand their experience. The goal is to get insights into your customers, colleagues, and partners to ensure that everybody is on the same page. For this, you have to ask a lot of questions. Not everyone will tell you everything they know, and thus, this route has its limitations. You have to walk in their shoes and try to understand what they are feeling. Understand the people you design and build for, indirectly or directly. It always pays off if you can gain a contextual, holistic understanding of being a data scientist.
As a data scientist, you always have to set your priorities straight. Because you are bombarded with a plethora of questions all the time, which can be answered in several different ways, you need to determine which of these questions are worth answering. Moreover, you also need to determine how much effort is worth putting into answering those questions. If you are able to implement this discipline in your team, you can teach them how they can prioritize their thinking and preferences.
These are the top five people skills that every data scientist needs to learn if they want to succeed. You cannot gulp all these skills overnight. It takes patience and a lot of time. We recommend that you start implementing some of these disciplines and see how it goes.