Stack Inventory
Engineering Stack
A weighted matrix of tools and domains—categorized by operational depth and strategic focus across analysis, ML, BI, economics, and vision.
Data Engineering
Machine Learning
Business Intelligence
Economics & Quant
Vision Lab
CORE
Daily execution Data Analysis Machine Learning Business Intelligence Economics Python SQL
STRONG
Architecture Power BI Google Data Studio BigQuery Scikit-learn Statistical Modeling Tableau Salesforce Stata
GROWTH
Acquisition Experimental Design Plotly Web Scraping
EMERGING
Horizon Vision Lab OpenCV Computer Vision Pipelines
Philosophy
The stack favors explainable pipelines and decision-ready outputs over tool sprawl. Mature tools handle persistence and reporting; emerging layers stay scoped and honest.
Connectivity
Tools connect through reproducible SQL/Python workflows, API integrations, and shared metric definitions—not ad hoc spreadsheet exports.
Automation
Python ETL, scheduled dashboards, and validated models reduce manual handoffs. Production means repeatable pipelines, not one-off heroics.