Data operations and analytics professional based in New York. I build the infrastructure, reporting, and analytics that turn raw business data into clear decisions.
Financial securities validation system modeled on Bloomberg and Refinitiv workflows. SQL quality rules, Python anomaly detection, and an SLA breach dashboard.
End-to-end pipeline: ingest messy alternative datasets, engineer features, train a predictive model, backtest performance with a full research writeup.
Synthetic RLHF labeling workflow simulating Anthropic-style human data operations — labeling guidelines, QA logic, annotator tracking, and prompt experiments.
Power BI dashboard analyzing sales and profitability across countries and products for a fictitious company. Compares year-to-date vs. prior year to surface underperforming regions.
Analyzed 1,000+ customer reviews from 2016–2023 in Tableau. Surfaced patterns in service quality, aircraft performance, and geographic satisfaction distribution.
Centralized cost data across 34 NYC residential buildings — vendor expenses, labor hours, and building-level costs — replacing manual spreadsheets with automated reporting to support budgeting and decision-making.
A minimalist daily task manager built with PyQt5. Designed around focus and intentionality — set one Most Important Task (MIT) for the day, maintain a flexible might-do list, and cut through the noise. Dark-mode interface with automatic date tracking and local storage.
A personal knowledge system with audio memo capture and an interactive knowledge map. Take notes, record voice memos, and watch your ideas connect into a visual graph you can actually navigate.
Personal website for J. Alexander Martin, co-founder of FUBU. Built during my time at Vanguarde, the site covers his work across fashion, tech, media, and business — with sections for consulting, ventures, press, and speaking.
An interactive map cataloging murals across New York City for Thrive Collective. Lets users explore the city's public art scene geographically — find murals by neighborhood, artist, or location. Demo available on request.
A breakdown of ISIN, CUSIP, and SEDOL identifiers — why they matter, where they break, and how data quality failures cost firms millions.
How analysts can implement Great Expectations and Pandera to catch data issues before they become business problems — no dedicated engineering team required.
Behind every aligned LLM is an operations layer most people never see. This maps the systems, roles, and quality mechanisms that make human feedback work at scale.
Data operations and analytics professional based in New York. I build the infrastructure, reporting, and analytics that growing businesses need — without the complexity or the wait.