A focused selection of portfolio work in data engineering, platform architecture, and time-series machine learning.
A public body of work focused on reproducible data engineering, platform architecture, ML, and AI. It includes quality standards, reference material, architecture decisions, and a roadmap for production-style projects.
Explore the portfolio →An end-to-end architecture for financial data: web capture, Kafka-based ingestion, distributed storage, log monitoring, dashboards, and opportunities for sentiment analysis and anomaly detection.
Read the thesis project →A practical collection of forecasting work covering data exploration, transformations, seasonality, moving averages, ARIMA, Prophet, and exponential smoothing techniques.
Explore forecasting work →