Life & Work with Lauren Burke

Today we’d like to introduce you to Lauren Burke. 

Hi Lauren, so excited to have you with us today. What can you tell us about your story?
I’ve always loved math and solving problems. When I was younger, I remember being so interested in the world around me, always wanting to explore and asking tons of questions to understand how things worked and why. I went on to study math, taking a few of the more analytical computer science classes along the way. Then a few internships in statistical and text analytics helped me to figure out that I was mainly interested in the applied side of math and finding ways to use it to solve real-world problems. 

At my alma mater, The College of Wooster, we complete an Independent Study project over our senior year on a topic related to our major. I had taken a Machine Intelligence course and wanted to bring some of what I’d learned into my project. I chose to look into optimizing a large-scale road trip through every US National Park, which led to me researching and learning to apply a few more machine learning algorithms. It was a challenging but rewarding experience that cemented my interest in predictive analytics and introduced me to techniques I’d use again in my data science career. Now five and a half years later, I’m still excited every day about the work I do as a Data Scientist! 

After graduating, I volunteered at the second Women in Analytics Conference, just two days into my first Data Scientist role. It was an amazing experience, and I’ll never forget the welcomeness and support I felt as a new grad attending my first analytics conference. The community is one of the core reasons I chose to reach out about joining the WIA Team. We’ve continued to grow that community, and this summer will host our seventh event after rebranding to the DataConnect Conference. 

Over the years, I’ve continued to get involved with organizations in the data science space, like the Midwest Big Data Hub and sci-kit-learn, and support others that foster enthusiasm for STEM, including COSI, TECH CORPS, and STEMifyGirls. 

Can you talk to us a bit about the challenges and lessons you’ve learned along the way? Looking back, would you say it’s been easy or smooth in retrospect?
In any tech field, including data science, you see fewer women and an even lower number in leadership roles. I’ve been the only woman in the classroom, team, and meeting at times. That’s one reason I’m drawn to organizations like Women in Analytics. WIA, in particular, not only highlights women’s impact and contributions to the field but allows you to become part of a larger community of people happy to share their interests and support. 

A more personal challenge was figuring out what kind of career I wanted to pursue. After my sophomore year, I knew I liked studying math and wanted to find a job that allowed me to use those skills, but I wasn’t aware of the options out there. Nearing the end of my senior year, I still had no idea data science existed! Finally, one day I was filtering for jobs by the required skills and came across a posting for a “data scientist” role that seemed to check all the right boxes. The rest is history! 

Can you tell our readers more about what you do and what you think sets you apart from others?
I’m a Data Scientist at CoverMyMeds, a healthcare technology company. To me, data science is at the intersection of math, statistics, and computer science with a focus on creative problem-solving. At the core, it involves finding patterns in data and extracting meaningful insights that can influence decisions. In a business sense, that usually means answering stakeholders’ questions, making predictions, and effectively communicating the results. 

For the past year and a half, I’ve been in a more product-focused role where my work involves building out systems and models that help understand user needs, inform decisions, and enhance product features. One reason I like working in the healthcare tech space is the ability to positively impact the patient’s experience. After moving into my new role, I had the opportunity to lead a large-scale project from start to finish. After months of research, collaboration, coding, testing, and automation, we’ve finally seen the results of everything coming together. Measuring the impact of this project was a great feeling, knowing all of the work that went into it. 

Is there a quality that you most attribute to your success?
Curiosity! It is so key in data science. Asking the right questions, diving deep into exploring the data, and looking at a problem from different angles. Being curious also means constantly thinking about the what-ifs and what to look into next. Then, being open-minded and flexible enough to change your approach if it doesn’t work out the first time. 

Contact Info:

• Website: https://laurburke.github.io/
• Linkedin: https://linkedin.com/in/lauren-e-burke/
• Twitter: https://twitter.com/lauren_e_burke
• Other: https://womeninanalytics.com/podcast 

Image Credits
Captured by Kaitlin
COSI
Shinji Kim