Throughout my college career, I have gained significant programming experience and developed strong analytical skills. In my Computational Data Exploration class, I have learned how to manipulate data frames, create data visualizations, and perform multiple regression in Python. In my Modern Data Mining course, I analyzed datasets on diabetes and Kobe Bryant’s shots using Lasso, logistic regression, random forests and machine learning to build predictive models in R. My strong attention to detail and quality-focused mindset allowed me to carefully analyze these datasets and write clear reports on my findings. These two examples of programming classes that I have taken showcase a small portion of my skills in both Python and R as I have since worked on multiple data projects in both languages to further develop my coding skills. On top of learning Python and R, I also have experience working in SQL and Tableau. Outside of the classroom, I was a member of multiple clubs at my school that provided real-time data analytical consulting to clients. These projects covered a wide range of data types including both numerical and text data as well as a wide range of topics from farming data to survey data to sports data. Not only did these projects give me vital experience in working through a complete data project, but they also provided me with plenty of experience communicating with clients in real-time and working with them to best solve their needs. Finally, I have interned at two different companies over the past two summers to work as a data analyst intern. During my time at the S.E.C., I gained experience wrangling data from multiple sources to create integrated views and help decision making. I also worked on streamlining data collection by developing web scrapers. During my time at Earnest Research, I developed skills in extracting necessary data to generate creative and actionable insights using SQL and Tableau. Lastly, I have recently been hired by Mastercard as a full-time Associate Consultant Data Analyst.