Julia Lintern talks about what ultimately drew her to data science and what she’s planning next.
By Natasha Awasthi (Product Manager & Writer)
When was the last time you met a structural aerospace engineer? It’s surely rarer still to find one who has also launched two fashion labels, dabbling in hat design and puppetry along the way.
Julia Lintern is a creative and a scientist all in one. Having earned two degrees in Mechanical Engineering and then Applied Mathematics, she worked in aviation for more than five years, designing solutions for damaged airplanes. All the while, she indulged her artistic passions by juggling creative gigs on the side.
In 2002 she left her job at Delta Air Lines in Atlanta to study Fashion Design at FIT, working part-time as a costume designer and milliner. She launched her fashion label Molly Spinach in 2004 and her Lia Lintern line in 2009.
However, the appeal of becoming a Data Scientist lured her away from the studio and back into the world of aerospace once more. What was it that sparked her interest in data science?
“Life and mathematics are my inspiration and data science is an application of them both,” replies Julia Lintern. For the past decade, the Brooklyn-based mechanical engineer at JetBlue has tamed information from flight recorders, pilot reports and more to compute the risk of component failures in aircrafts.
With her newly acquired skills, including Natural Language Processing, she hopes to train these binary, continuous and handwritten troves to reveal their secrets. Over coffee we charted her journey to becoming this number-crunching breed of scientist.
What was it about Data Science that hooked you?
Julia: In January 2014, I read a Data Science job description and thought, ‘Hey, that’s me.’ As someone with a degree in Applied Mathematics, I’ve always felt that mathematicians have been sidelined. The convergence of mathematics, ease of access to volumes of data and computer engineering has changed that.
Please brag about your data science repertoire.
Julia: Machine Learning, Probability Theory, Statistics, Data Visualization, Regression Analysis, Time Series, Python, R, Mathematica, Django and D3.
What were your baseline skills when you started and how did you build up the balance?
Julia: My undergraduate degree is in Mechanical Engineering and this spring I completed a two-year part time degree in Applied Mathematics. So I was comfortable with the math but I needed to work on my coding skills.
When you get stuck, what resources do you go to?
Julia: Stack Overflow!
Tell us about your fantasy project.
Julia: My dream project is to trace the trajectory of news and address questions like: what variables affect its life? Let’s take the example of the kidnapped girls of Nigeria. Based on data from news, blog entries, social media, etc. I would create a map that shows how and why such a big story disappears.
Are there moments when you are especially psyched?
Julia: When I see beautiful data visualizations with maps: for instance, this one in The New York Times.
Tell us about experts you admire and follow.
Julia: Meghan Smith and Reshma Saujani.
Any rituals we should know about?
Julia: I like projects outside my comfort zone. I am incredibly inspired by the Kaggle competitions and the community. It’s a great way to throw myself into the Machine Learning fire.
What makes someone a rock star Data Scientist?
Julia: Obsessive curiosity. You have to be at the cutting edge of many different fronts.
To focus on the stories to tell, you have to know what issues are current. To get to the right answers, you have to keep your finger on the pulse of advances in computing tools and applied mathematics.
What’s your next adventure?
Julia: Until 2008 I ran a custom tailoring business alongside my full-time job. Now I want to find a way to bring the beauty from fashion and numbers together.
How do you indulge your creativity alongside work?
Photo credits: Natasha Awasthi