Data analyst focused on recurring KPI reporting, reporting automation, and translating SQL, Tableau, Excel, and Python workflows into faster executive answers.
Built recurring KPI reporting across lodging, tax, web, campaign, and airport data, cutting turnaround 99%, saving 200+ hours annually, and improving executive reporting cadence.
Identified lodging cannibalization by reconciling lodging tax, occupancy, ADR, and RevPAR trends across council, board, and stakeholder reporting used in planning decisions.
Produced bimonthly council and stakeholder briefings translating Tourism Economics, GA4, hotel, and survey data into planning, budget, and performance discussions.
Validated budget, tax, and partner reporting against Tourism Economics datasets spanning 202 dashboards and 162 sources, strengthening QA and stakeholder confidence.
Re-platformed R workflows into a one-click Python app, cutting delivery time by 95% for recurring QA, handoff, and review cycles.
Built decision-tree models that expanded serial-number tracking by 10x while flagging anomalies with 98% precision for downstream review prioritization and follow-up.
Deployed an autoencoder model that improved data quality for downstream analytics, QA review, and exception handling workflows.
Built SQL ETL views and anomaly detection to surface store, region, and associate risk patterns for investigation prioritization, exception follow-up, and leadership review.
Used Excel geo-analysis and optimization to explain shift, location, driver, tipping, service-area, and delivery-window differences across service zones.
