Matthew Yee

I'm currently building enterprise reporting and decision-support pipelines for AT&T wireless, 5G, fiber, and network operations. Using Databricks, Apache Spark, SQL, and governed data models, I've improved service-issue detection by 25% and reduced capacity-planning cycle time by 30%.

At Affinius Capital, I consolidated investment, lending, valuation, accounting, and property data into standardized analytical datasets using AWS Glue, PySpark, Apache Airflow, Amazon S3, and SQL. I also established data-quality and lineage controls that reduced recurring downstream defects by 30% and shortened data-issue investigations by 25%.

I've delivered healthcare AI and data-intelligence solutions at HCLTech, including clinical NLP, predictive modeling, document processing, and medical-imaging decision support. Earlier at Bank of America, I developed fraud and transaction-risk models that improved fraud recall by 10% while reducing false-positive alerts by 20%.

Across consulting, data engineering, and machine learning engagements, I translate operational workflows into maintainable reporting and analytics products. I work directly with end users, document requirements and risks, validate data, troubleshoot production issues, and mentor teams on technical delivery.