I hold a degree in Data Science and build practical data and backend systems designed to be run, inspected, and evaluated. My work spans machine-learning evaluation, SQL analytics, Python APIs, data engineering, and production delivery.
Open app | Repository | Model card | Latest release
A machine-learning system for estimating seven-day NYC 311 resolution risk from creation-time information. It combines chronological evaluation, leakage controls, verified artifacts, human-review workflows, Entra application roles, append-only Neon audit storage, shared rate limits, and scheduled model monitoring. The app runs on Vercel, with container releases, SBOM, provenance, and alternative Azure infrastructure included in the repository.
The review console requires Microsoft Entra sign-in and an assigned application role. The model card and source are public.
Live dashboard | API documentation | Repository | Latest release
A FastAPI operations service for pipeline run tracking, data quality checks, webhook alerts, metrics, and ownership metadata. It runs on Vercel with durable Neon PostgreSQL storage and API-key-protected writes. The repository includes Alembic migrations, non-root containers, Azure infrastructure, CI quality gates, an SBOM, and build provenance.
Live project site | Repository
40 runnable SQL analytics challenges with validation checks, learning paths, and browser-friendly challenge pages. The exercises cover cohorts, retention, window functions, revenue analysis, and data engineering SQL patterns.
| Project | Scope | Stack |
|---|---|---|
| Data Engineering Lab | Python pipelines that ingest data, load SQLite, and write report outputs | Python, pandas, SQL, SQLite |
| SignalBoard | Full-stack productivity dashboard with authentication, database models, tests, and a live deployment | Next.js, TypeScript, Prisma, NextAuth, Vercel |
- Data science and analytics: chronological evaluation, leakage controls, calibration, drift analysis, SQL, and pandas
- Python services: FastAPI, SQLAlchemy, Alembic, pytest, and PostgreSQL
- Delivery: Docker, GitHub Actions, Azure Container Apps, release automation, and observability
- Full-stack development: TypeScript, Next.js, Prisma, and authentication