By day, I’m a data scientist. I spend most of my time looking at tables, graphs, and numbers; running statistical analyses; and solving business problems with predictive analytics and machine learning. While those are the typical daily tasks, you might be surprised that my job also involves quite a bit of writing.
Yes, even data scientists need to be able to write effectively.
But I don’t just mean technical manuals, white papers, and reports. This goes beyond the basics of technical writing. I also have to translate my findings into blog posts or reviews for critical stakeholders and even those who have next to no experience with the data.
Thankfully, I studied psychology in college. Through my undergraduate and graduate career, I learned how to explain my findings in layman’s terms, and because I also love writing, this allowed me to combine my analytical thinking with my creative side.
You might ask – why is writing important for data scientists? Isn’t there someone else who takes care of that stuff?
You’d think that all copywriters handle data write-ups, but you’d be surprised to find that copywriters also need to communicate with the data engineers and data scientists to tell a brand’s story. I admit I have a bit of a competitive advantage when it comes to these tasks. Because I studied the elements of storytelling for my fictional pieces, I’m better able to apply them to my data analyses.
For instance, as I lay out my coding notebook for my analyses, I also keep track of what I’m doing by taking notes. At first, it’s just commented in the code so that I know the transformations and calculations, but later I expand this to full markdown which involves headings, paragraphs, bullet points, and more.
Why do I take the time to do all this?
Because if the person making the company’s decisions - whether that’s the CEO, the Chief Business Officer, or another executive – isn’t engaged by my findings or doesn’t fully understand what I did, then essentially the whole project was useless.
When I approach my final data write-ups, I try to keep some key points in mind. Below, I’ll go over some of my major Dos and Don’ts:
Data science and creative writing aren’t as different as people might think. I say that as someone who practices both skills regularly. Even though the majority of my day job focuses on technical communication, having a background in creative writing and employing the help of an agile copywriter can take a data science project to the next level.
If you’re looking to hire a writer who is skilled in turning your data into a meaningful message contact us today.
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