Career Profile
Data Scientist with deep experience in the Mining sector, delivering AI and machine learning solutions that optimize production workflows, enhance commodity sales, and improve safety outcomes. Skilled in designing and deploying scalable ML solutions with MLOps best practices. Recent projects include a vessel scheduling optimization system and NLP applications with LLM workflows. Outside of work, I experiment with creative AI projects and enjoy cooking and running.
Experiences
- Developed and maintained a real-time vessel scheduling system that increased iron ore sales by 18M tonnes annually ($900M value) through optimized fleet allocation and inventory management.
- Developed and maintained end-to-end LLM workflows that automated complex assay data extraction and contract reconciliation, eliminating 600+ hours of manual effort annually and delivering $2.5M in recoverable revenue.
- Deployed LLM models on AWS SageMaker that successfully classified $2.7B of off-contract spend data, reducing procurement compliance risks by 35% and enabling targeted contract negotiations.
- Led Snowflake platform optimization for 200+ Commercial users, achieving 50% reduction in compute costs while establishing robust data governance protocols and automated CI/CD pipelines.
- Supported technical migration from IBM CP4D to AWS cloud platform, implementing enterprise-grade security frameworks that enabled 15+ analytics workstreams and reduced infrastructure costs by 40%.
- Provide L2 and L3 support for Commercial Analytics data products.
Rotational program focused on developing technical and analytical skills across BHP’s technology operations:
- Engineered comprehensive Spotfire dashboards for the Maritime Process and Operations team, automating real-time reporting of key metrics including Contract Errors, Open Voyages, and Laytime settlements, reducing reporting time by 75%.
- Developed Python packages for anomaly detection of equipment failure using advanced ML techniques (autoencoder + LSTM, one-class SVM) and automated dust data collection from multiple sources including APIs, FTP servers, and SQL databases.
- Generated actionable data insights for the Driver Safety System monitoring vehicles and equipment across mine sites, improving safety compliance tracking and operational risk management.
- Implemented process improvements for 3rd Party Logistics supply chain that increased stock accuracy across 16 BHP warehouses through SAP system enhancements, redesigned labeling protocols and optimized packing processes.
Led company-wide engagement initiatives through The Singapore Community (TSC), fostering employee morale and workplace culture across BHP’s Singapore office of 250+ employees.