The Magic of Analytics
Cindy Kelford uses her OMS Analytics magic as a decision scientist for Walt Disney® Resort.
After completing the Georgia Tech Online Master of Science in Analytics (OMS Analytics) program, Cindy Kelford went from full-time mom to decision scientist at The Walt Disney Company, where she utilizes data on projects for Walt Disney World® Resort.
Q: You made quite a career transition! What attracted you to Disney and what does your position as a decision scientist with Walt Disney World® Resort entail?
I went to Magic Kingdom® Park for the first time right after starting OMS Analytics. Walking around the park with my new coursework fresh on my mind, I was thinking that the entire program could be taught using Disney Parks case studies alone. And now I work on projects for Walt Disney World!
I focus mostly on forecasting (ensemble models, generalized linear models, etc.), but I also work closely with those who run simulation, optimization, visualization, and data engineering for the parks.
The broad array of skills I learned from Georgia Tech helps me collaborate with teammates who focus on different disciplines so that we can gain valuable insight from each other’s work. With so much collaborative work across the company, there is a lot of room for developing new skills and having different focuses at Disney.
I work for the Decision Science team within the Disney Decision Science + Integration organization (DDSI). DDSI serves as a centralized decision science resource for all of The Walt Disney Company, working with many Disney lines of business including Parks & Resorts, Studios, and Media Networks to help them make better and/or more efficient decisions.
Q: What do you like most about your job?
My favorite part of my job is problem-solving. I find it rewarding to take data that has been collected under one set of circumstances and think through how we can utilize, transform, and supplement it to predict future behavior that will likely operate under a different set of circumstances.
Q: After raising three children, what led you to return to college and pursue a master's in analytics?
A: While I graduated with a B.A. in Mathematics, I ultimately did not make that a career. I chose to stay home when I had kids, but the desire for a fulfilling career never left me. When my youngest child entered elementary school, I was able to focus on what I wanted to do.
My husband recommended I explore data science degrees since it would be a good fit given my math background, love of logic puzzles, and even my volunteer work where as treasurer, I was using databases to forecast expenditures.
Q: Why did you choose Georgia Tech?
A: I needed a degree that was marketable, online, affordable, and flexible enough to accommodate my family’s schedule. Georgia Tech has a stellar reputation for its online programs, so I knew I would be getting a great education.
Coming from a theoretical mathematics background, it was important to me to learn the underlying theory of analytics — not just how to run models, but what the models are doing “under the hood” and why they were developed.
After doing my due diligence and exploring my options, Georgia Tech was the obvious choice. As it turned out, OMS Analytics’ focus on underlying theory and hands-on application for learning program models allowed me to shine in my interview with Disney.
Q: How has your transition into data analytics been?
It’s amazing how many things I learned in OMS Analytics that I continuously use in my position at Disney. Not only in my daily work but also in understanding how what I do contributes to the company’s larger projects. One of the most helpful aspects I learned from the program is being adaptable - learning to think things through and understand the solutions.
I absolutely love working at Disney. It is indeed my dream job. OMS Analytics provided me with the knowledge and skills I needed to work for an industry giant. It delivered everything I was looking for in an online format that I needed.
Credits
Writer: Laurel-Ann Dooley
Editor: Teresa Daniel
From Psychology to Analytics: In Search of Why
