Previous Education: B.S., Texas Tech, and B.S. and M.S., University of Houston
Location: Houston, Texas
Occupation: Global Director of Product Engineering and QA
Tell us a bit about yourself.
I like being outside (golf, biking) and learning and I’m attracted to solving problems and leaving things better than when I found them. I played baseball in the Houston Men’s League for several years, but my work travel schedule got crazy and made that difficult which was probably a good thing because I was in denial about how age had affected my skills. The good news is that my arm still works well enough to throw tennis balls for the dogs. I dabbled with umpiring at the high school level and lately I’ve been catching up with old friends.
What initially attracted you to the field of data science?
I had lost a sense of fulfillment at work and decided that I couldn’t do that job for another 15 years. I saw data science as a puzzle of sorts. How do you see through the cloud of information to find something useful? It’s different and has wide application, and I think my background and experience give me a good set of tools to use in a new way.
Why did you choose an online program?
Commuting to school would have added considerably to the time commitment, and I like the technology of the online environment. Being able to “rewind” the lectures allows me to slow things down when I need more time to absorb the topic.
Were there any adjustments you had to make to get acclimated to an online learning environment?
Just time management. Having a class on campus requires you to be there. The time commitments for online courses are not as rigid, so you have to be a little more diligent to make sure you put in the time and keep up. I found it to be an easy transition.
What is your current profession, and how will earning your Master of Science in Data Science degree from SMU help you achieve your future career goals?
I’ve been in the workforce for 26 years now in one industry. I started as a design engineer and progressed up to an executive position with responsibilities for my department and direct reports. I’m still in the technical side of the business, but I found myself in a career rut and started looking to make a change. I’m hoping that data science will help me move on from my prior work and get me excited about other industries/businesses where my technical and managerial experience can be put to new uses.
How do you see the use of data science evolving in the future? How will that affect DataScience@SMU graduates?
Information is everywhere, so someone will need to have the skills to work with it. I think the pinch point will be who is going to do it. As I learn more about what this is all about, it seems that it really isn’t a career path for entry-level work. What I mean is that computer skills to find, retrieve and manipulate data are more readily learned than making judgments about what makes sense once that is done. Time and exposure to executive level-thinking is key to helping the data folks know how to apply their time wisely and, more importantly, to know how to approach presidents and CEOs with novel or not obvious conclusions. It’s never black and white, and there are often many other factors that need to be put into context before a decision can be made, especially in publicly traded companies. I see a communication gap growing within companies as data science matures.