I like to tell stories with data.

At my very core, I am a problem-solver. I was attracted to the versatile field of data sciences because of the immediate and plentiful ways that data could be used to solve real problems, coupled with the various roles I could play in answering those questions. Yet what caused me to pivot my career directly into the world of data was not simply the promise of using data to answer interesting questions, but rather something of the opposite, that is, using data to ask interesting questions. When data has a story to tell (and I intend to tell its full story), many questions spark at least two more. Immediately, I discovered that I needed to sharpen my skills around gathering and transforming data, developing infrastructure and processes, ensuring I had accessible, reliable, quality data at my fingertips. And now, as a data and analytics engineer, I get the best of all worlds: Writing data stories from beginning to end.

Prior to my transition into data engineering, I earned a Ph.D. in Systems Modeling and Analysis from Virginia Commonwealth University in 2021. My research focus was in graph theory, a relatively new branch of discrete mathematics. During graduate school, I taught several mathematics and statistics courses. My experience as an instructor and researcher has taught me the importance of clear, thorough communication. I attribute my successes to my excellent communication skills, my perseverance, my resilience, and my unyielding self-motivation.

Ultimately, I just think of myself as a numbers person. If it has a number in it, I probably want to know more about it.