Welcome to our interview series, where we introduce you to developers of all levels from all walks of life. Prepare to be inspired!
Today we meet Sara Kimmich, a data scientist and a developer. She tells us how and why she got into the world of coding and why Inception isn’t completely unrealistic!
What’s your position in your company? What’s your day to day like?
I just joined a mid-sized tech firm where I focus on machine learning and backend analytic development. Day to day, my life is 40% code, 30% documentation, 15% internal meetings, 10% client-facing, and 5% ducking Nerf gun fires from coworkers. This is a great way to destress when you’re code won’t compile!
Can you tell us about how you got into code, and why you chose this career path?
How we can use computers to build useful things has always been interesting to me. The earliest memory I have of actually hands-on coding was a Coding Camp. I attended it over the summer when I was in seventh grade. I was the only female in a camp of 30, and I have to admit that environment set me off from coding spaces for a while.
Fast forward to college. I was studying neuroscience and I found coding at the center of one of my main obsessions: understanding human consciousness. Consciousness is a complex thing, and you have to find ways to classify both behavior and biological brain states in new ways.
That passion carried me through to a PhD. My goal was to see if we could change people’s brain states without their knowledge (incepted neurofeedback – yes, just like the DiCaprio movie). The world is information, and code gives us a way to understand it.
I can’t say I really ‘chose’ this career path: I just keep chasing the things that excite me.
How did you become a data scientist? Did you choose data science intentionally?
I didn’t choose to become a data scientist – I was just wanted to keep working on challenges that require analytic creativity. Data scientist is my formal role. I self-identify as an avid Stackoverflow enthusiast.
What is your favorite part of being a data scientist?
The thing I love the most about data science is that it lets you look objectively at the things you are analyzing. You can use machine learning to test your hypotheses, or generative algorithms to let your data read a hypothesis back to you, in a way.
When you find a surprising result from a data set, there’s something really satisfying about that. This might be weird to say, but I love that feeling. I love when data gives me different results than I expected. It knocks you down a peg and lets you realize the world will always be more complex than your understanding of it, and that’s where the adventure is.
You built Online Brain Intensive, a free online platform where people can learn to analyze large sets of brain data. What sparked the idea and how did you bring it to life?
I am lucky to be in a community of people who are passionate about the Open Web. We believe that making tools and data accessible to everyone is fundamental to a free and progressing society. That might sound like a soap box pitch, but when you put it into practice, incredible things can happen.
In bringing these principles to computational neuroscience, I wanted to make sure that anyone, anywhere could learn the fundamentals of accessing, curating and analyzing openly available brain data sets. I am a forever optimist. I don’t think the best neuroscientist is locked in an ivory tower. They might be might be a high school student, a farmer, or a stay-at-home parent. As long as they’ve got the internet they should be able to objectively test their ideas on real data.
If we can achieve that radical change in the creation of new knowledge from data that’s already in the world, there’s a huge range of potential for what data driven medical progress can look like in the 21st century. I’m pretty passionate about it, but I never could have made it happen without a whole team of incredible experts that who volunteered their time to empower over 750 students in the first year.
How do you engage students in an online program like Brain Intensive? What’s the key ingredient to making sure students can apply their knowledge?
The most important thing for me was that this wasn’t a ‘course;’ it was a pathway to doing real work. It was important to me that every student had the opportunity to get one-on-one interaction with these experts (via Slack).
This turned out to be the key to making Online Brain Intensive a major success: we did more than teach people. We fixed bugs in developer software, we improved documentation for the whole field.
It was a tour de force of collaborative coding that I think has had a lasting impact on the field.
What advice would you give to women in academia who want to want to learn to code?
Never Code Alone.
Learning to code is literally learning a new language – you can’t learn Spanish or Mandarin by talking to yourself. If helps so much to work with one or two other people, even if you are all starting to learn from scratch.
Don’t be afraid to ask for help, even from strangers on the internet. The longer you code, the more you figure out that everyone is learning all the time. ‘Experts’ are just the people who are great at asking questions instead of getting blocked.
When I can’t solve a bug, I… sigh as loudly as I can in an attempt to unsubtly catch coworkers’ attention and see if they’ve got ideas. 80% success rate.
My favorite programming language is… Python, hands down. Closure seems cool too for web dev but has a major learning curve.
Dream company to work for… Wikimedia (the non-profit that supports Wikipedia). Anyone who’s touched the internet has been impacted by the world that they do and keep doing, and I would love to be a part of that. I also love Comic Relief: A Just World Free from Poverty – the cloud platform they have to support real-time donations across three continents is just insane and I would love to work on that problem some day.