Faculty

Alan Lattimer

Professor of Practice

As an industry leader working in healthcare analytics, I have built and worked with several data science teams over the years. Senior leaders often view analytics and models as black boxes developed by their data science teams to provide insights to critical business problems. From the other perspective, data scientists frequently lack the domain knowledge and often create analyses and models without considering the context of the problem. This gap can often lead to incorrect results or misinterpretation of what the model is saying.

I believe the M.S. in Data Science degree at Virginia Tech is uniquely positioned to close this gap. With a curriculum developed by industry leaders with strong technical backgrounds, students will be taught the rigor needed to understand the technical landscape while being exposed to real-world data sets and problems. Our program is built on the notion that it truly is the ability to combine math, statistics, computer programming, and domain knowledge that differentiates a great data scientist from a good one.

With that philosophy, the Virginia Tech Academy of Data Science has designed a master's degree program that will provide the skills necessary to create the next generation of leaders and expert practitioners in the evolving world of data science.

Scott Mutchler

Associate Professor of Practice

I'm thrilled to help launch the Virginia Tech's new M.S. in Data Science. What excites me most is our commitment to welcoming students from diverse academic backgrounds — because I've seen firsthand how different perspectives enrich the data science field and lead to more innovative solutions.

Throughout my career spanning insurance, manufacturing, distribution, retail, and energy sectors, I've witnessed the transformative power of data science across industries. This extensive cross-domain experience shapes my teaching approach: our students won't just learn theoretical concepts; they'll work with realistic problem statements and datasets that mirror the complexities and challenges they'll face in their careers.

My passion for developing data scientists runs deep. Building my own data science consultancy from the ground up with recent graduates was one of the most rewarding experiences of my career. I watched young professionals grow from hesitant analysts into confident data scientists, capable of tackling complex problems and driving meaningful change. This experience reinforced my belief in hands-on, practical learning — an approach that will be central to our program.

A master’s in data science is more than just a degree; it's a gateway to making a positive impact on the world. Whether it's optimizing processes, improving outcomes, or developing innovative solutions to complex problems, our graduates will have the tools and knowledge to address important challenges facing society.

I'm excited to bring my real-world experience and mentorship approach to Virginia Tech, helping shape the next generation of data scientists who will drive innovation across industries and create positive change in our world.

Oliver Schabenberger

Professor of Practice

During my professional career I experienced the beginnings, rise, and evolution of data science — in academia and in corporate roles. It is fascinating to see the diverse backgrounds of data scientists. You do not have to be a statistician to become a data scientist. You do not have to be a computer engineer or mathematician to become a data scientist. And being a statistician, mathematician, or computer scientist does not guarantee that you will be a great data scientist. Data scientists work at the intersection of these disciplines to solve real-world problems through data and drive change in their organizations.

I am stoked about the M.S. in Data Science at Virginia Tech because it does not stop with the theory fundamentals. Your random forest is as good as someone else's random forest. 

You will also learn how to participate and lead data science projects, how to effectively work on data science teams, how to communicate data technology across organizations, and how to implement end-to-end solutions. And you will learn firsthand from experts who have walked the walk in data science for years. That is how you realize the transformative power of data.