Victoria Guzik, Data Scientist
It was near the end of her undergraduate studies that Victoria Guzik learned she had a problem.
“My undergraduate education is actually in neuroscience,” she says, “but I realized that they don’t really let you do neuroscience with an undergraduate degree. That’s the sort of thing that requires going up into the PhD level.”
She wasn’t sure about graduate school, but as she reflected on her studies, she realized there was something she was sure about. “One of the things that I really loved about my undergraduate education was the grounding in statistical methods and the use of data analysis,” she says.
She decided to pursue that further, and that’s how she found Dataquest.
Learning with Dataquest
“There was that whole movement, back around when Nate Silver had his 15 minutes of fame, where suddenly we weren’t statisticians anymore, we were all data scientists,” she says. “So I did some research into this fancy new term for what I was already doing, and Dataquest came out as the recommendation for where to go to get that much needed grounding in Python and R, and the more in-depth programming knowledge that you may not get in an undergraduate curriculum.”
So Guzik started working through Dataquest’s data science courses. “I really loved [the] platform,” she says. “I had looked into a couple of the others, and I found that they were much too handhold-y and fill in the blank relative to Dataquest’s method.”
Starting a New Career
“I worked through the projects on Dataquest, I worked through the lesson paths, and I kept up with the new content over the year or so that I was a subscriber,” Guzik says. “Eventually I put that I was open to recruiters on LinkedIn.”
That’s all it took.
A recruiter messaged her, and she followed up. “They ran me through some programming questions, which I was able to answer to their satisfaction. And then they asked for some examples of my prior programming work and I gave them my GitHub. I pointed out a couple of projects that were specifically focused on what they seem to prioritize in a data analyst,” she says.
“That job offer doubled my income overnight,” she says.
Advice for Data Science Learners
If you want to follow in Guzik’s footsteps, she has three pieces of advice.
First: “Absolutely look to Dataquest first before [you] look to any other source,” she says. “I think it’s the best value for your time and your money in terms of the skills that you develop and the timeline you develop them on.”
Second: “Always make sure to not just do the projects just to do them, but to make sure to really understand them and incorporate them back into a business context,” she says. “Go back and explain your code in your notebooks. Don’t just treat [the guided projects] as homework. You want to put as much care and as much effort into those projects as you would into a project that you’d be presenting for work. Companies really respond to that.”
Third: “As important as it is to have those technical skills,” she says, “you really need that deep understanding of how to take data and analysis and turn them into actionable insights for a business.”
That’s a big part of why she recommends Dataquest, she says. “I really think that Dataquest and their project model not only provides those hard programming skills, but also teaches you how to apply them in meaningful ways.”