In both my academic and internship experiences, I’ve often had to manage competing priorities under tight deadlines. During my internship at Tarte Cosmetics, I balanced responsibilities across marketing, operations, and finance. One week, I was tasked with updating a product pricing model, organizing influencer send-outs, coordinating vendor communications, and preparing slides for a weekly marketing sync. To manage the urgency, I first clarified expectations and deadlines for each task with my manager—understanding what was truly time-sensitive versus what felt urgent. Then, I mapped out my tasks based on urgency and impact. I typically prioritized deliverables that affected others’ workflows first, such as vendor scheduling or providing data needed for meetings. I used tools like Trello and Google Calendar to track progress and block focused time. When things shifted, I remained flexible and communicated any delays early to maintain transparency. By staying organized and proactive, I was able to complete all tasks on time and even received recognition for how smoothly I handled the week’s workload.

In my data analysis course, I worked on a team project where we analyzed a housing dataset to identify cost-efficiency patterns for a real estate case study. Accuracy was crucial because even small data entry errors could significantly impact our conclusions and recommendations. To ensure our data stayed clean and up to date, I took the lead in setting up a shared spreadsheet that logged all updates and data sources. I created standardized input formats and used data validation tools in Excel to minimize manual entry errors. We also scheduled regular team check-ins to review any changes, flag inconsistencies, and make sure we were all using the same versions of the dataset. Additionally, I cross-referenced key variables with original source files to ensure nothing had been lost or misrepresented during preprocessing. By being meticulous about cleanliness and consistency, we were able to confidently present our findings, and our professor noted the reliability of our analysis in their feedback.

In one of my management science courses, we were tasked with analyzing operational efficiency for a simulated company over multiple quarters. I led the effort to build a complex spreadsheet system in Excel to track and analyze our operational and financial data. The spreadsheet included multiple tabs that captured inputs like staffing levels, production capacity, raw material costs, and inventory. I used formulas and lookup functions to calculate total costs, profits, and performance metrics like utilization rates and cost per unit. To make the data more actionable, I built a dashboard with pivot tables and charts that visualized trends across quarters, helping us understand the impact of our strategic decisions. What made it complex was that each decision we made in one quarter would affect future performance, so I had to ensure the model was dynamic enough to account for these dependencies while remaining clear for my team to use. This system helped us make informed decisions and ultimately contributed to our group ranking near the top of the class for overall performance. This experience sharpened my ability to design efficient data tracking tools and translate operational details into strategic insights—skills I’m excited to bring to future roles.