I am a senior data scientist and software engineer. I build predictive software, data pipelines, and applications, lead projects through testing and deployment, and train data scientists and junior colleagues. As a Mercor code reviewer and super reviewer, I also check code, tests, and technical answers against the source.
My work includes Python and SQL applications, forecasting, A/B testing, model deployment, and data integration with BigQuery, Snowflake, Databricks, and REST APIs. I hold a master's degree in Data Science. The public projects below include source code, tests, model results, and live applications.
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