Briana Brownell knows a thing or two about data science. Before founding the data analytics and machine learning firm Purestrategy.ai, she worked with a variety of companies from startups to Fortune 500 firms on marketing and analytics. She’s also worked on a variety of cool data science and machine learning projects, doing things like teaching a computer to write a Shakespearean sonnet and trying to trick handwriting recognition AI.
As the founder at PureStrategy.ai, she’s in a position to both do data science and hire data scientists with some regularity. And when she spoke with Dataquest, she said that there’s one skill prospective applicants can use to set themselves apart when applying for data science jobs: communication.
Communication is a critical skill in almost any position, but Brownell said it’s particularly crucial in data science. Data scientists are tasked with writing code and creating complex models, but at the end of the day, all of these technical skills are applied to solve business problems, and the solutions that they suggest are only valuable if the data scientist is capable of communicating them to everyone else at the company.
In your job applications, then, you should emphasize that you not only know how to analyze data, you know how to communicate it with a team.
How to show communication in a data science resume
Obviously, you can say that you’re a great communicator. But everybody says that, so it’s not going to set you apart. And to demonstrate your communication skills in person, you’d need to have already been asked to interview.
Thankfully, there’s a way you can demonstrate your communication skills even earlier in the process. Brownell told Dataquest that she looks for two things on a resume to assess communication skills: examples of successful cross-departmental collaborative projects, and mentions of business metrics.
Examples of successful cross-departmental collaborative projects are pretty self-explanatory. Having a few of those on your resume proves that you’re capable of effective communication in a real-world business environment.
Mentioning business metrics is a less direct way of demonstrating communication skills, but Brownell said that to her, it demonstrates a candidate who understands the role that data science plays in a larger company and who is capable of translating data science results (which only a data scientist might understand) into business metrics and outcomes, which anyone familiar with the business should be able to understand.
Communicate your passion in the interview
Once you’ve gotten an interview, your communication skills (or lack thereof) are going to be more easily evident to the interviewer. But there are still some ways you can help ensure you perform well, and one is making sure you’ve got a passion project to talk about.
Brownell said that asking about a candidate’s favorite project was among her favorite job interview questions, because it gives interviewees “a chance to shine.” If your interviewer doesn’t give you that opportunity, manufacture it for yourself. Chances are you’re going to be more articulate, enthusiastic, and engaging when you’re talking about a project you really care about.
And if course, in your interview, you can also echo the same communication touchpoints highlighted in your resume. Talk about collaborative projects where you worked with members of different teams at your previous job. Even if you don’t have relevant previous experience, you can still talk about your own data science projects from the perspective of meaningful business metrics to demonstrate you know how to turn your code into actionable, layman-understandable intelligence.
There is, of course, a limit to how far communication skills can get you. They’re not a replacement for technical know-how. Without the coding chops required to do the job, even great communication skills probably can’t save your application. But if you’ve got the technical stuff down, revising your resume to emphasize your work in the context of collaboration and to highlight business metrics and results will help you stand out.
(Don't quite have the technical skills down yet? Start learning valuable data science skills right now.)