I don't just build models. I build answers.
I bridge the gap between technical engineering and business strategy. I specialize in architecting end-to-end systems—from cleaning raw SQL datasets to deploying CatBoost predictive models on AWS that protect ARR and drive measurable ROI.
| Modeling & Analytics | Infrastructure & Cloud | Visualization & BI |
|---|---|---|
Python CatBoost Optuna |
SQL AWS (EC2/Lambda) |
Power BI (DAX) |
Scikit-Learn Pandas |
Docker Git Flask |
Plotly Seaborn |
Core Focus Areas:
- Predictive Systems: Real-time Fraud Detection & Demand Forecasting (CatBoost, XGBoost).
- Revenue Optimization: Churn mitigation and ARR protection through stratified modeling.
- Analytical Engineering: Modular ML pipelines using
DataManagerandPipelineRunnerpatterns. - Business Intelligence: Transforming high-dimensional data into executive Power BI stories.
- 🚲 Demand Forecasting: Cloud-deployed API with a 51% MAE reduction using TimeSeriesSplit.
- 📉 Churn Prediction: Targeted retention system protecting ARR with 0.64 precision.
- 🛡️ Fraud Detection: Real-time predictive engine optimized for high-stakes financial security.
Currently open to Full-time Roles | Washington, DC or Remote


