Reliable data models
Customer identity, ELT checks, metric ownership, and reporting flows that teams can maintain.
Data systems that make product and operations work easier to reason about.
I studied Data Science and Business Economics at UC San Diego, and I work across data engineering, product analytics, logistics reporting, and transportation-linked analysis.
Customer identity, ELT checks, metric ownership, and reporting flows that teams can maintain.
Funnels, experiments, cohorts, and decision views that connect analysis back to product changes.
Planning, logistics, fairness, and access questions shape how I think about data work.
Project notes focused on the problem, the model, and how the work became useful.
Account-level customer view for GTM reporting.
Tests and monitoring for steadier ELT.
Funnel tracking and experiment readouts.
Airfare model review with fairness metrics.
Data work across GTM, logistics, product analytics, and operations.
EnvoyX
GTM data for customer identity and reporting.
United Parcel Service
KPI reporting for logistics teams.
United Parcel Service
Brokerage intake and compliance reporting.