The Importance of Communication for Data Science Careers By: Nour Abi-Nakhoul April 19, 2022 Estimated reading time: 2 minutes. It’s widely known that those interested in a data science career need to have logic and problem-solving skills. The so-called hard skills are important to a data science career, as you’ll be working with large sets of information. What’s less obvious is that data analysts and data scientists also need to pay attention to soft skills. Aspiring data analysts who neglect soft skills to favour only working on their logic, math, and problem-solving will end up with an incomplete skill set. Effective communication is a fundamental skill for those who work with data. To be genuinely proficient data analysts, they need to be effective communicators. Read on for some of the reasons why communication is such a fundamental skill for those aspiring towards data science careers. Communicating Data Science Results Skillfully Those that work in data science careers are stuck in a difficult bind. They have advanced knowledge of subjects that will go over the heads of those who aren’t versed in data. They need to find a way to communicate data findings to others in a legible and meaningful manner. Both speaking and writing skills are important to this career. Data analysts and data scientists need to be cognizant that they don’t fall into what’s known as the curse of knowledge. When a person has the knowledge, it becomes difficult for them to imagine what it’s like to not have that knowledge. They might then communicate with others in a way that assumes the other person will understand them, and not make necessary efforts to communicate in simple, clear terms. Data analysts and data scientists need to ensure they know how to communicate data science knowledge to audiences that aren’t versed in data. Cross-departmental knowledge transfer is important, so it’s key that those who work with data can communicate insights and analyses in simple, clear terms that don’t overwhelm the audiences with technical details and jargon. Working With Others Effectively as a Data Analyst or Data Scientist As a data analyst or data scientist, you’ll spend a lot of time working alone with a computer, poring over datasets and algorithms. But you’ll also frequently find yourself working with others. It’s common to work alongside other analysts or scientists as part of a team, especially when working on large projects or handling big datasets. Beyond this, you’ll also frequently work with other teams of people who don’t work with data. It’s important to be a good communicator in order to work effectively with others. Communication is a two-way road, and it’s key to be a good listener as well as a good speaker. Learn to speak and write clearly and concisely in a way that communicates your meaning effectively. When listening to others, provide them with your full attention to absorb the information they’re relaying properly. Above all, it’s important to conduct all communication with empathy and understanding of the other person’s position. Disagreements will inevitably arise, and you must ensure that you work towards compromise in a level, empathetic way. Holding Attention with Data Presentation Skills Data analysts and data scientists will occasionally have to present their findings to colleagues or clients with presentations. In these moments, clear and effective communication is central. You will need to be able to present complex analyses to others in a short window of time, without rushing, and getting your key points across profoundly. During presentations, you should leave out any unnecessary details to avoid over-complicating things. Render your presentation as concise and streamlined as possible. Explain your points in clear, simple terms, without using technical jargon that your audience won’t understand. Don’t rely just on slides, but instead use those visual aspects to enhance the explanations you’re verbally providing. Being able to create accessible and attention-grabbing data visualizations is an important skill to have, one that’s useful during presentations. Lastly, it’s important to relax and be comfortable while presenting to others. Projecting ease and confidence will make your audience more attentive to you, and make them more comfortable in turn. This will help your audience feel able to bring up questions, concerns, and requests for more detail. Want to launch your data career? Sign up for the Data Analytics or Data Science Program today and transform your career. Data Science Program Data Analytics Program Got more communication tips for data science careers? Share this post on your social network and tag us! Tweet this post Share on Facebook Share on LinkedIn