Chris Brace has always had a passion for the unknown.
From a young age, he found himself creating his own instructions for moving toys, class assignments, and everything in between.
His curiosity led him to his role as an Associate Data Engineer with Pandata—and for this article, we sat down with Chris to learn exactly how.
As a kid, I was always asking questions and using what I learned to tinker with motors and gears.
For a while I was really interested in planes and thought I’d be a pilot or an aerospace engineer. But instead, I ended up at Case Western pursuing psychology, philosophy, computer science, and cognitive science.
I always like to joke that I picked up as many fields of study as I have hobbies!
After graduating from Case Western, I started as an IT Development Program Associate with a large manufacturing company.
I wasn’t there too long, as I wanted to work with AI and machine learning. I remembered I had met Hannah at a Big Data Meetup before starting my career and decided to apply on a whim. The rest, as they say, is history.
No two days—much less weeks—look the same, so it’s difficult to describe a typical week.
However, I spend most of my time on project work. This involves checking in with clients and providing support and guidance to solve a specific challenge their business is facing. Right now I’m helping a client work through challenges in their business process.
In data science, there’s always something new going on. It’s a lucky day if I use the same skillset twice! My job is never boring, but the variation in client work can sometimes make it difficult to stay organized in this industry.
I’d have to say my favorite data science project thus far has been working with the Cleveland Museum of Art to create interactive dashboards for artwork viewership. I wrote the web scrapers in addition to the interface and calculation code that tied several tools together to ultimately understand the viewership of publicly available works. Getting to see the project from beginning to end was incredibly cool.
A lot of people seem to assume AI is all about extracting mysterious results from a tiny, data-filled black box. In reality, it’s a tool—and just like a hammer or a drill, it has a defined set of uses. To really thrive, artificial intelligence and machine learning have to become a natural part of our clients’ processes.
At Pandata, we’re consultants and advisors first, data scientists second. We’re all about opening up the process of designing and developing AI solutions, and making sure our clients understand what’s going on.
It really is all about education. We do our best to explain our technology in terms anyone can understand. It also helps when our clients know machine learning is about saving time and building efficiency—there’s no evil intent or hidden purpose.
Machine learning used to be based on expansive models that were difficult to conceptualize, so I’m definitely looking forward to the rise of the explainability model.
Staying at the edge of technology is key to building models the general public can trust and understand.
Know what’s possible and respect what’s not.
The data science industry is all about remaining humble and constantly seeking improvement—which is why I’m grateful for all the effort that’s already gone into the field.
Chris Brace’s journey is just one of the many unique backgrounds that make up the Pandata team of expert data scientists. If your organization feels ready to work with the Pandata team to design and implement the right AI solution, schedule an AI Exploration Session with our team.
In this session, we will discuss your current needs, and dive deeper into ways your organization can implement human-centered AI and machine learning solutions to accelerate your business goals.
Contributor – Nicole McCaffrey, COO/AI Translator at Pandata. Contact Us