π Computer Science @ Howard University (May 2026)
π Data Analyst | Applied Machine Learning | Business Intelligence
π Washington, DC
I build end-to-end analytical systems that transform raw data into actionable business insights.
My work spans SQL analytics, customer behavior modeling, A/B experimentation, cohort retention analysis, and applied machine learning systems designed with business impact in mind.
I focus on clarity, structure, and decision-oriented analytics.
- Analyzed 3,900+ transactions across 18 features
- Identified high-value customer segments driving revenue concentration
- Built SQL pipelines and interactive Power BI dashboards
- Delivered KPI tracking: AOV, revenue distribution, discount impact
- Cleaned experimental dataset and enforced group consistency
- Conducted two-proportion Z-test
- Measured statistical and practical lift
- Provided data-driven rollout recommendation
- Built cohort tables using transaction-level data
- Calculated retention decay and revenue trends
- Identified early churn windows
- Proposed targeted engagement strategy
- Combined collaborative and content-based filtering
- Engineered similarity metrics
- Improved personalization accuracy
- Advanced SQL optimization
- Experimentation and causal inference
- Production-ready ML pipelines
- Business-driven analytics systems
Building analytical systems that drive measurable impact.

