Leaning over the frame of an almost complete, homemade trebuchet, my grandfather slid apiece of paper with a few scribbled calculations across the table to me. “You see,” he explained,“in order to maximize the distance that the projectile travels, we need to make the length of theprojectile arm much, much longer on the sling side than the weight side.” Sure enough, laterthat day, in the middle of an empty field, that garage-built trebuchet launched a tennis ballfurther than I could have imagined.In that moment, I knew I was hooked for life. Hooked on the need to create; to use science, math, creativity, and good old fashion sweat to bring wonderful, beautiful things into being.I followed this passion in college where I received a bachelors in mechanical engineering. My coursework deepened my appreciation for the rich set of tools science and math offer anyone who wants to make something new and useful. After a few years of work under my belt, I decided I wanted to expand my toolset even further and headed back to grad school. It was there that I discovered programming.As I stumbled through my first Python course, I could feel building inside me what Steinbeck would call "the indescribable joy of creation". Here at last was pure creation. All that stood between me and that new solution, that new thing was the limits of my knowledge and creativity.I cut my time in grad school short and found a job building Python applications for science based businesses. I now spend my days using programming, coupled with my science and engineering background, to help our clients solve their pressing R&D problems. Our tools help them visualize, organize, and search their data as they prepare it for scientific and machine learning analysis.My toolset is ever growing. I am comfortable in an Agile development environment writing Python code for analysis (the Python scientific stack including Numpy and Scipy), the desktop (QT), and the web (Flask) while managing it all with Git/Github. While I am always honing my data science tools, both EDA (SQL, Pandas, Seaborn) and Machine Learning (sklearn, Tensorflow, Pytorch), I am currently trying to add application front end (JavaScript, React) as well as deployment (Docker, AWS) to my toolset.