Ryan Christian Galaban

Designed and proposed a standardized database architecture to streamline the ingestion and retrieval of interinstitutional research project workflows across university departments. Engineered automated ETL (Extract, Transform, Load) pipelines using Microsoft Power Query to clean, restructure, and integrate fragmented legacy datasets. Developed and deployed dynamic executive dashboards across Power BI and Looker Studio, implementing continuous data-integrity audits to proactively identify and resolve reporting discrepancies.

Office Assistant – Database Management at UP Los Baños – Office of the Vice Chancellor of Research and Extension (2026-02 – 2026-05)

• Designed and proposed a standardized database architecture to streamline the ingestion and retrieval of interinstitutional research project workflows across university departments.
• Engineered automated ETL (Extract, Transform, Load) pipelines using Microsoft Power Query to clean, restructure, and integrate fragmented legacy datasets.
• Developed and deployed dynamic executive dashboards across Power BI and Looker Studio, implementing continuous data-integrity audits to proactively identify and resolve reporting discrepancies.

Intern – Office of the National Statistician at Philippine Statistics Authority (2025-05 – 2025-06)

• Conducted advanced statistical analysis and econometric modeling on massive-scale national survey datasets using R and Python (Pandas/NumPy), extracting key demographic and economic trends to support executive policy briefs.
• Designed and published high-fidelity data visualizations and comprehensive statistical reports, translating complex national metrics into intuitive insights for government stakeholders and the public.
• Managed and reconciled critical financial and administrative databases, implementing strict data-governance protocols to audit departmental records and ensure absolute reporting compliance.

Intern – Data Modeling at Bank of the Philippine Islands (BPI) (2024-09 – 2024-11)

• Developed predictive machine learning models for highly imbalanced financial datasets using XGBoost, CatBoost, and SMOTE, successfully mitigating data skewness to optimize risk classification accuracy.
• Engineered automated web-scraping pipelines using Python (Selenium / BeautifulSoup) to harvest alternative web data, executing advanced feature engineering on existing banking variables to maximize model predictive power.
• Synthesized complex quantitative outputs into actionable market intelligence, delivering data-driven strategic recommendations to senior banking stakeholders to support portfolio optimization.

Bachelor of Science in Statistics (Computer Science Elective) – University of the Philippines Los Baños (2026)