Gettysburg, Pennsylvania, United States
• Manage residential communities of over 200 residents, fostering cross-functional student engagement and well-being • Organize two financial literacy workshops per semester, helping students manage budgeting and banking needs • Put together 3 diverse programming events per semester, managing $500 budgets and increasing participation by 25%
• Coordinate appointments and track call records using tools like Excel; promptly relay them to appropriate staff • Organize residential keys for 350+ students during seasonal breaks using internal software
• Instructed 60+ students in statistical methodologies, including linear and multiple regression, using Excel • Developed hands-on data exercises with real-world datasets, enhancing student proficiency in data interpretation by 10% as measured by course assessments
• Spearheaded data-driven fundraising strategies, securing $600K in seed funding by analyzing key metrics from data warehouses to support strategic growth • Assisted in preparing financial statements & balance sheets in line with GAAP, ensuring accurate liquidity tracking • Optimized interactive Grafana/Tableau dashboards, boosting operational efficiency by 30% across six sprints • Conducted comprehensive SQL analysis on customer lifecycle data, uncovering trends that reduced churn by 12% and increased user activation by 18%, significantly boosting platform engagement and retention • Developed KPI dashboards to track revenue trends, providing leadership with real-time insights for cash flow decisions
• Conducted an in-depth consumer analysis of Gen Z audio trends, interviewing 5 participants and analyzing 100+ data points to identify key preferences, such as sound quality, and brand influence in the over-the-ear headphone market • Led research from recruitment to data analysis, uncovering a 20% preference for customizable designs and delivering insights on social influence that shaped Beats' new marketing campaign, boosting Gen Z engagement
• Collaborated with a cross-functional team to execute sentiment analysis on Nepali texts using Natural Language Processing (NLP), contributing to data cleaning, tokenization, and stemming for high-quality model training input • Assisted in fine-tuning NLP models by analyzing model performance metrics and making adjustments, which improved the model's accuracy to 92.26% in detecting and handling of sentiment nuances in the Nepali language
• Executed a pilot program for a two-month long online course with 1900+ students • Led meetings & tracked class performance based on daily tests, resulting in an increase in student success • Facilitated feedback sessions with students and teachers, leading to a 25% improvement in student satisfaction