Data Science Intern
EdiGlobe · May 2025 – Jun 2025
- Analyzed 119,390 hotel bookings and 1,000 IMDb movies using data cleaning, EDA, statistical analysis, correlation, and outlier detection to identify trends in cancellations, pricing, ratings, revenue, genres, and audience engagement.
- Identified a 37.0% hotel cancellation rate, with cancellations increasing from 30.3% to 98.8% with longer booking lead times, and found a 0.64 correlation between IMDb audience votes and revenue; Animation averaged $191.2M in revenue.
- Used these insights to identify high-risk hotel bookings and revenue-associated movie characteristics, supporting datadriven decisions around cancellation policies, movie selection, and marketing.
- Created data-driven visualizations and statistical summaries to communicate findings clearly, helping convert raw datasets into actionable insights for business-oriented decision-making.