Faces Of NPR is a weekly feature that showcases the people behind NPR, from the voices you hear every day on the radio to the ones who work outside of the recording studio. You'll find out about what they do and what they're inspired by on the daily. This week's post features Data Scientist Malorie Hughes.
The Basics:
Name: Malorie Hughes
Job Title: Data Scientist
Where You're From: Phoenix, Arizona
An Inside Look
You're a Data Scientist here at NPR. What does that mean? What does your day-to-day look like?
I spend a lot of my time doing statistics, building models that measure the impact of some decision—a release schedule, donation or ad campaign, a new podcast or radio show—on outcomes such as downloads, audience growth, reach, engagement, retention, and external podcast rankings.
In my day-to-day I fall ever deeper in love with RStudio, drink coffee, read white papers, search Stack Overflow, build dashboards, try new models, plan research projects, organize my life with sticky notes, react abruptly and loudly to unexpected errors and executions in my code, attend a Tiny Desk, admire my tiny plants.
How did you get started here? What advice do you have for someone who wants a job like yours?
I sought it out. When I finally escaped school in 2014, I thought "NPR *must* have a data scientist." I periodically checked the careers page with no luck. I believe it was April of 2017 that I came across the job posting. My cover letter read something to the effect of "THIS JOB IS MY BIRTH RIGHT." Luckily I'd been recently consulting for media and entertainment companies, which must have helped me stand out in the pile of resumes. I was invited to the first round of phone screenings, and the rest is history.
My advice: For the most part, I work independently in this role, so the most important requirements are self-drive, an addiction to detail, and a relentless desire to learn. But, whether working independently or on a large data science team, these qualities are essentially prerequisites to gaining the technical skills you need on day one. I'm sure it comes as no surprise, but those technical skills include, but are not limited to, mathematical logic, statistics, computer science, and the ability to code quite well in (at least) one language. Don't stress over the R versus Python debate—choose a language that speaks to you and chat it up until you're fluent. The hardest language to learn is your first.
What are some projects you're most proud of that you've worked on?
From a methodology perspective, a study I did (and continue to update) for Hidden Brain is my proudest work. The model set-up is analogous to a clinical trial with varying treatment dosages, where the "patients" are Designated Market Areas, the "treatment" is the number of stations airing a radio show, and the endpoint of interest is digital downloads. Doing this requires combining a very wide range of data sources, including Nielsen rankings, station broadcast schedules, location data, digital podcast downloads, and population estimates.
In terms of impact, I formalized a cross-promotion strategy to help determine which podcasts to promote on one another. I built the strategy into a suite of dashboards that are in regular use, and I think that's pretty cool.
What is something you've learned about NPR listeners from your research?
Many engage in listening behavior that tells the story of their daily routines—work commutes, breaks from the news, podcasts while preparing dinner, NPR One and chill on lazy Sunday afternoons. Holidays throw off their routine, which I choose to believe is due to BBQs, parades, camping, and vacations.
NPR listeners are many, they are passionate, empathetic, and driven to learn. But I knew that before I got here.
What's on your desk?
Plants, a Veridesk, and a giant monitor.
Favorite podcast?
Hidden Brain and Wait Wait... Don't Tell Me!
First thing you do when you get to the office?
Click my way to Inbox Zero.
Favorite places in Washington D.C.?
All music venues, Rock Creek Park, Union Market, and anywhere I can take my dog.
What do you love about public radio?
I remember it from childhood. I remember Car Talk and Wait Wait and the soothing sound of Robert Siegel's voice. Public radio enjoys a freedom and has earned a responsibility unmatched by private news and media companies. The employees are here because they love it, because they are compelled to contribute, because they have their own memories of the invaluable role public radio has had on their lives and a shared goal to delight and inform others. Public radio has a mission I can stand behind, and I'm honored to be a part of it.
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