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Top 3 Reasons Public Speaking Can Help You in Data Science

Understand your audience, answer questions, and ask for feedback

Photo from Michal Czyz on Unsplash
Photo from Michal Czyz on Unsplash

When I was in college, I participated in Toastmasters. I spent two years working on my presentation skills, learning how to speak in front of people, and getting feedback on my work. At the time, I did not anticipate the impact it would have on my current position. Learning to communicate effectively is a valid and critical skill in data science and engineering. Recently, I signed up again to Toastmasters. I wanted to share why I decided to sign up and how public speaking can benefit your career.

If you don’t already know, Toastmasters is a public speaking club. This club allows you to practice your public speaking skills, improve your Communication, and build leadership skills. But you may be thinking, why do I need to improve my speaking skills in a data science role? There are three areas I find public speaking skills beneficial in my daily work: participating in technical and non-technical discussions, impromptu questions, and providing feedback.


Technical and Non-Technical Audiences

For the past two years, I have spent time in many meetings, and in them, the audience varies from technical to non-technical individuals. One area of public speaking that I often focus on when practicing is learning how to adapt my content to different audiences. A non-technical audience is often my stakeholders. When I meet with them, they want to know the status of work on the project, projected timeline, and any blockers inhibiting my work.

When I first started practicing my speaking, I focused on delivering technical presentations to non-technical audiences. Toastmasters was an excellent venue for this as most of my audience was non-technical from different backgrounds. This environment gave me a great place to talk and receive feedback on what went well and what was confusing.

The more you present to non-technical audiences, the better you determine the level of information that is appropriate to present. Aside from non-technical audiences, the other type of individuals I often present to are technical individuals in a different field. I am in Data Science, but I often present to data engineers, software engineers, electrical engineers, and more.

When presenting to other technical folks who may not be in the same field as me, I can add more detail and discuss the work’s technical aspects. As I am working with those technical folks, I tailor my conversations to relevant work. With data engineers, I can understand why my data looks the way it does or how I can fix the issues I am facing in the ground truth dataset. While with software engineers, I can ask how to improve our codebases and processes.


Impromptu Presentations

In Toastmasters, there are three types of speaking engagements: planned speeches, evaluations of others’ speeches, and impromptu table topics. Of the three table topics are 1–2 minute speeches on a given topic that you are presented with right then and there. At that point, you need to think on your feet to answer the question quickly and concisely.

Table topics are my favorite of the three to practice because they help significantly in data science. After presenting a demo or a presentation to different audiences, I open the floor to questions and comments. At this time, I am presented with something similar to a table topic where I have to develop an impromptu answer in a short period. I often get questions such as:

  • Is the method used here the best way, or could you have used this other method to arrive at the same answer?
  • Why did you use this metric instead of another one?
  • Was that parameter the best one to use? Could you have considered this other one?

These questions may be things you have already considered in your analysis, or they may not be. Answering them concisely and quickly in a meeting is beneficial to keep the discussion moving. And if you don’t have an immediate answer? It is okay to say you will investigate that further and get back to the person.


Feedback

Now that you can present to different audiences and answer impromptu questions, let’s discuss the most challenging part of Public Speaking: getting and giving feedback. I have struggled with one aspect, and I feel like many individuals understand how to get and give feedback. If you have been keeping up with my articles, then you may have read how I spent last year asking for feedback often from my colleagues and mentors.

I was taught to provide feedback through my Toastmasters club experience, and I have found it very valuable. After I learned to give feedback to others, I began asking for feedback to understand what I was doing well, where I needed to work on, and what did not go well that I can challenge myself to change. This area of communication can be hard to master. You want to be able to provide feedback without sounding rude or condescending to someone. But, it can be a valuable tool once learned.

If I am not asking for feedback, then I am often providing it. Some examples of areas that I get asked for feedback on include:

  • Code Reviews – Colleagues often look for feedback on their code during code reviews. They want to know what areas they could improve or where they need to change to conform to the group’s coding standards.
  • Project Output – If I am not in a code review, then I am looking over the output of someone’s analysis. During these calls, they want information about what was unclear in the analysis or what action items need to be added before the work can be approved.
  • Presentations – Often, on my team, someone will create a PowerPoint slide set and ask for advice on them. We find ourselves speaking to other teams, both technical and non-technical, often. When I provide feedback on slides, the presenter wants to know if the content is appropriate and at the right level for the audience, they are presenting to. The more you work with different audiences, the more you will understand how to provide feedback on presentations being written for those people.

Providing feedback may be something you struggle with, but you can help your team by providing valuable insights with practice.


Final Thoughts

It may not seem like an essential skill at first, but public speaking is critical for working in data science and engineering. Often, you will find yourself in meetings, demos, or conferences in which you need to present your work clearly and concisely. Three areas I focus on when practicing my public speaking include:

  • Learn how to adapt my content to different audiences that include technical and non-technical individuals from varying fields.
  • Develop the skills to answer impromptu questions quickly and concisely. If you don’t know the answer, say you will note down the action and get back to them when you do.
  • Practice giving feedback and asking for feedback on your work. Learning to provide useful feedback to your team is a valuable skill to have, especially when participating in code reviews, analysis output discussions, and presentations.

These areas have been beneficial in my career as they have helped me understand how to communicate effectively and present my work. Data science is not just a technical career but one that requires a lot of discussions.

How have you worked to improve your communication skills? Do you also see public speaking as a critical skill in data science?


If you would like to read more, check out some of my other articles below!

Top 3 Lessons Learned in my Journey to Become a Data Scientist

Remote Work Can Make it Hard to Stand Out as a Strong Data Scientist

Why Taking Notes on Your Accomplishments Can Help Your Career


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