NYU MSIS graduate student with experience in Python, SQL, data analysis, data cleaning, forecasting, and web scraping. Interested in business intelligence, enterprise data systems, reporting, and technical analysis. Strong ability to learn new tools, document workflows, and communicate technical findings clearly.
• Developed time-series forecasting models using ARIMA and LSTM to analyze 2024 revenue trends.
• Built Python-based data analysis pipelines to clean, process, and visualize business data.
• Conducted exploratory data analysis to identify patterns and support data-driven decision-making.
• Evaluated model performance using error metrics and residual analysis, then summarized findings for reporting.
• Developed web scraping pipelines using Scrapy to collect and process 250+ structured records.
• Cleaned and preprocessed raw datasets to improve consistency and analysis readiness.
• Supported the design and implementation of a train ticket booking platform using HTML, CSS, and JavaScript.
• Collaborated with team members to organize requirements, troubleshoot issues, and support data-related development tasks.