I studied Finance at Oakland University where I pursued my minor in Business Analytics. This was my first interaction with the interaction of programming, statistics, and industry knowledge known as data science. Throughout my finance learning, I leveraged the tools learned in my analytics coursework to model complex problems and tell a story with the data.In spring of 2019, I graduated Summa Cum Laude and was invited to join the Finance Leadership Development Program at Fiat Chrysler Automobiles (now known as Stellantis) later that summer. This is a fast-paced program for high potential individuals geared towards understanding the automotive industry from a commercial, industrial, and corporate view. My first rotation was in World Class Finance, the analytics and process improvement department within the Finance organization. From there, I held positions in Supply Chain Management Finance, the Office of Tax Affairs, and Detroit Assembly Complex - Jefferson; learning core functions in these teams as well as leveraging my technological background to improve processes and create models. Throughout my time at Stellantis, I acted as an internal analytics consultant, taking on various data science projects to drive business value. My technical skills include the following programming languages: Python, R, SQL, Visual Basic for Applications, Bash, and Windows Command Prompt. Relevant web skills include: HTML, CSS, and JavaScript. Other technologies that I am proficient in are: PyCharm, JupyterLab, RStudio, Atom, Visual Studio Code, Tableau, Qlik Sense, KNIME, Quick Base, SAP, Essbase, Microsoft Office Suite, and G-Suite.One thing that drew me to this program was the constant change associated with it. I love meeting new people and learning new ways of tackling old problems, and just seeing differing perspectives. This is especially relevant currently as the merger with Peugeot that was finalized in January 2021 has created an influx of new processes, systems, and coworkers to manage. It was a very rewarding experience.In my spare time, I enjoy taking the publicly available datasets related to Major League Baseball and manipulating them in new and interesting ways. My favorite project to date related to this was an in-depth analysis of Justin Verlander’s oft-overlooked 2016 season where he finished runner-up in the AL Cy Young.