About

Work Experience

• President & Data Science / AI Instructor, Programming Club of IST (pcIST)

  Aug, 2025 - Jul, 202611 months

  • Led a team to organize 10+ workshops and technical events on AI and Data Science, increasing student participation through cross-functional collaboration

  • Taught 50+ students Python, data analysis, and ML fundamentals; conducted hands-on training on NumPy, Pandas, and real-world datasets

  • Mentored students in building end-to-end data-driven projects from problem definition to deployment

• IT Supervisor, Population and Housing Census Project 2022

  May, 2022 - Jun, 20221 month

  • Managed real-time data ingestion workflows for 135+ field operators during a national-scale data collection exercise

  • Ensured data accuracy, consistency, and integrity across all submissions before upload to centralized government systems

  • Supervised structured, high-volume data uploads under strict time and accuracy constraints

Projects Experience

• Vendor Performance Analytics — ETL Pipeline & BI System

  - Present

  Scalable ETL/ELT pipeline and business intelligence system for vendor performance analysis

  • Designed and implemented a scalable ETL/ELT pipeline to ingest datasets with 10M+ rows using chunk-based processing, optimizing for memory efficiency and throughput

  • Optimized SQLite insert operations by dynamically handling parameter limits; applied data warehousing principles to structure an analytics layer for reporting

  • Built modular pipeline architecture (Ingestion → Transformation → Analytics) with structured logging for pipeline observability and failure tracing

  • Wrote production-level SQL using CTEs and multi-table joins to generate business KPIs: Gross Profit, Profit Margin, Stock Turnover, and Sales Efficiency

  • Validated data integrity across all pipeline stages with schema consistency checks and null auditing

• Global Supply Chain Analytics & Shipment Optimization

  - Present

  End-to-end data engineering and ML system for supply chain analytics and shipment delay prediction

  • Designed a relational data model simulating real-world logistics (4 tables, 1,000+ shipments, 12 ports, 10 carriers across 5 regions) with full schema documentation

  • Built a 3-stage ETL pipeline with schema validation, null auditing, and structured logging

  • Developed reusable analytical SQL views using window functions and joins for consistent reporting

  • Trained an XGBoost classification model (85.9% accuracy) for shipment delay prediction and a regression model (R² = 0.87) to estimate shipping costs

  • Built a What-If simulation tool: switching carriers reduced predicted delay probability by 18 percentage points

  • Delivered a Streamlit dashboard with KPIs including on-time delivery rates, carrier performance rankings, and port congestion analysis

Skills

Education

Certificates

Awards