I build end-to-end data systems that transform complex scientific and operational data into reliable datasets, analytical insights, and machine-learning solutions. My background in biological research shapes my interest in bioinformatics, health informatics, medicine, and scientific data systems.
I also enjoy learning unfamiliar domains and translating their processes and business rules into practical data products using Python, SQL, PostgreSQL, ETL development, data modeling, and applied machine learning.
Explore my data projects portfolio →
| Project | What it demonstrates |
|---|---|
| Aptafind | Reproducible computational aptamer research, provenance-aware data pipelines, grouped evaluation, and PyTorch and TensorFlow sequence-generation experiments |
| Healthcare Clinical Intelligence | FHIR and HL7 ingestion, layered PostgreSQL modeling, data quality and reconciliation, Airflow orchestration, OMOP-compatible analytics, and governed machine learning |
| Healthcare Claims ETL | Healthcare data modeling, Python and PostgreSQL ETL, data validation, and analytics-ready transformations |
| Gene Metadata Pipeline | REST API ingestion, scientific-data transformation, validation, and relational storage |
| Project | What it demonstrates |
|---|---|
| Manufacturing Intelligence Platform | PostgreSQL data modeling, modular Python ETL, manufacturing KPIs, Tableau reporting, root-cause analysis, and predictive-maintenance modeling |
| BOM Material Planning | ERP-style production demand, BOM explosion, time-phased inventory netting, supplier constraints, and actionable purchasing recommendations |
| CAD-to-ERP Pipeline | Engineering metadata extraction, structured BOM processing, data validation, and CAD-to-ERP integration |
- Data engineering: ETL pipelines, data validation, relational modeling, data integration, and reproducible analytical datasets
- Languages and databases: Python, SQL, PostgreSQL, and SQLite
- Analytics and machine learning: Pandas, NumPy, scikit-learn, Tableau, operational KPIs, and predictive modeling
- Development workflow: SQLAlchemy, pytest, Git, and Apache Airflow
- Domain experience: Biological research, bioinformatics, healthcare, manufacturing, and ERP/BOM workflows
I am particularly interested in bioinformatics, health informatics, scientific data systems, medicine, and applied machine learning. I also value cross-domain work that requires learning a complex process and translating it into a reliable, understandable data solution.