Data Analyst focused on reporting automation, BI, statistical analysis, forecasting, and building practical systems people actually use.
Projects that combine analytics, product thinking, data modeling, and execution.
Private, offline-first fitness tracking PWA combining nutrition, workout progression, bodyweight tracking, saved recipes, USDA food data, and goal-based calorie/macronutrient logic.
SQL → Python → Power BI pipeline on 50,000+ retail records with automated data cleaning and executive KPI reporting.
40% faster data prepLogistic regression and random forest modeling to identify at-risk customers and translate model output into retention decisions.
85%+ accuracyMulti-year sales analysis across territories, products, and customers with forecast-vs-actual KPI reporting.
Automated reporting, improved data validation, reduced manual handling, and shipped stakeholder-facing BI dashboards.
Applied regression, clustering, forecasting, and hypothesis testing across research and startup datasets.
Built SQL, Excel, and Power BI reporting across sales, CRM, quota attainment, incentives, and productivity.
Used Python EDA, SQL, Excel VBA, and Power BI to surface logistics inefficiencies and improve visibility.
The same discipline I bring to analytics shows up outside work too.
Led a competitive state-level team — communication, decision-making, and accountability under pressure.
Competitive training background built around consistency, composure, and performance.