It wasn’t too long ago that Caitlin Whitlock was working retail at IKEA. She had a college degree in exercise science that she wasn’t using, and she wasn’t sure what she wanted to do in the long-term. Now, she’s working as a data scientist at Amazon, teaching Alexa to better understand human speech.
How did she get there? A lot of hard work, including a lot of time on Dataquest.
Caitlin’s post-college position is actually pretty common. Only 27 percent of college graduates work in a field related to their degree. But luckily for Caitlin, her job at IKEA involved some doing some occasional data work in Excel, and she quickly discovered that she enjoyed it. She decided to make a career switch and pursue a second Bachelor’s degree focused on data analysis at the University of South Florida (USF).
Studying Offline, Learning Data Science Online
Caitlin saw success relatively quickly. While she was studying at USF, she moved from IKEA to a job as a data analyst. But then, a school presentation she gave in front of the university’s board of directors went so well that she was offered a job as a junior data scientist at Tech Data by one of the board members. There was only one problem: Caitlin’s degree, which was focused more on accounting, financial analysis, and tangential topics like business law, hadn’t actually prepared her to do data science work.
“USF’s program really didn’t go into any sort of predictive analytics, or anything like that,” she said. “My job was as a junior data scientist, but my degree really didn’t prepare me for that at all.”
Forced to learn on the fly, Caitlin went looking for data science learning materials online. When she found Dataquest, she realized it could be valuable, and convinced her bosses at Tech Data to get her a subscription.
“I like the way Dataquest is set up,” she said. On other platforms, she was wasting a lot of time searching for the specific information she needed, but because of Dataquest’s paths, it was easy for her to learn what she needed in a logical sequence. “I found Dataquest and it was pre-curated and super awesome,” she said.
She also liked how Dataquest’s answer-checking provides immediate feedback at each step so that it’s easy for students to know whether they’ve gotten things right. “The other platforms, like EdX or like even Coursera to a certain degree, they don’t grade anything,” she said. “They don’t tell you how you’re doing. You’re kind of flying blind. I like that Dataquest gives you feedback.”
Moving to Amazon
At Tech Data, Caitlin put a ton of time into studying on Dataquest. “I was doing it a lot,” she said. “I was spending most of my day actually on [Dataquest].” That was a great learning opportunity, but it was also reflecting a bit of a problem with her job: Tech Data didn’t seem to know how to best make use of her data science skills.
Recognizing the problem, Caitlin started looking for a new position. Within a couple months, she had landed a job at Amazon working on Alexa and relocated from Tampa, Florida to Boston, Massachusetts.
Applying to Amazon was intimidating, she said. “It was a terrifying experience to go through the interview. I basically crammed as much on Dataquest as I could beforehand, and that ended up actually really helping.”
Because Amazon doesn’t like sharing the secrets behind its AI assistant Alexa, Caitlin couldn’t share too many details about her current role. But she said that in the big picture, what she does is help teach Alexa how to better understand people.
“It’s a little like a niche area of data science, in that it has very little to do with numbers,” she said. “We do a lot of natural language stuff. But I can’t say too much about how we do things.”
Advice for Aspiring Data Scientists
If you’re studying on Dataquest, Caitlin said, it’s important to both work through the guided projects and to branch out on your own in search of new challenges.
“I’d definitely say to keep with all the assignments that [Dataquest] puts together,” she said. But she encourages students to come up with their own unique projects to work on, too. “It’s great to go through the curated assignments and get those correct,” she said, “but you can do predictive analytics on freaking anything, and that practice really helps.”
And when you’re ready to apply for jobs, Caitlin said, don’t sell yourself short! “Honestly, apply for any job, period,” she said. “If you don’t think you’re going to get it, apply anyway. I have seen a lot of people just not apply for things because they’re intimidated.”
It’s also important to be open to relocating, she said. “I did move from Tampa, Florida to Boston, Massachusetts [for the Amazon job]. I think sometimes it’s necessary to move, especially in a field that’s as new as data science.”