Michael Catalano was born in St. Louis, Mo., where he currently resides. He holds a bachelor’s degree in chemical engineering and a Ph.D. in chemistry. After completing his graduate degree in 2016, he joined the big data/management consulting team¬†at WWT.

Q&A with Michael Catalano

Tell us about your background and how you got into technology.
My background is in scientific research, but I have always had interests in computer programming and mathematics. While in graduate school, I became interested in data science and began learning some of the tools of the trade in my spare time. I found that data science provided an avenue for me to transition into the tech field because it allowed me to apply my scientific training to real world problems.
What is your role at WWT?
As a data analyst for the big data consulting team, my role is to use data to solve customer-specific business problems. This involves gathering and cleaning data, conducting exploratory statistical analysis and visualization, mathematical modeling, and ultimately, uncovering the story within the data and conveying it to the customer in a meaningful way.
What innovation is happening in big data that has you really excited?
The intersection of big data and the internet of things with health care is a fascinating prospect. With the vast amount of data being generated by personal monitoring devices, it will be interesting to see what analysis of this data will bear moving forward.
Describe a recent interaction with a customer that led to solving a problem.
A recent project  involved working with hundreds of different continuous variables which varied over a dimension of length. One of our early tasks was to identify the meaning of each of these variables, as they were not clearly indicated. During initial exchanges with technical experts on the customer side, we had learned that they were treating these variables as time series for some of their analyses. Later, we were able to use a similar strategy to help classify the variables.