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Overview

I like to think of myself as analytically minded and that I’ve demonstrated a strong ability to deliver complex insights via data analytics and advanced data-driven methods.

Recent Experience

Data Scientist Consulting Manager – NTT DATA

  • Explainable AI for estimating physical security risk for a Fortune 500 healthcare provider’s facilities
  • Cold start mitigation pipeline and evaluation methodology for a top interactive entertainment company’s recommendation systems
  • Feasibility of GraphRAG built on Azure CosmosDB (internal sales)
  • Self-contained open source Llama RAG framework for a leading construction engineering company

Senior AI / ML Scientist – Datasite

  • DocChat, an interactive agentic chat with one or more documents in a Virtual Data Room (VDR)
  • Fine-tuned open source LLMs for entity extraction and document classification
  • Hierarchical taxonomy document classification deep learning model
  • Strategic / financial acquisition recommender deep learning model

Data Scientist (Officer) – U.S. Bank

  • Stock dividend forecasting
  • Explainable AI for predicting failure in mission critical applications
  • Anomaly detection for flagging unusual fund transactions in near real-time
  • Survival analysis for predicting customer attrition

Founder – Emphysic

Data Science Engineer – C.H. Robinson

  • Deep learning model for classifying shipping documents. Scanned more than 35,000 documents per day in production
  • with an accuracy of 96%
  • Deep learning model for tagging signed vs. unsigned shipping documents
  • Procedure for placing ”orphaned” documents with the correct shipment to reduce invoice processing time

Education

Master of Science – Queen’s University Kingston

  • Major: Physics
  • Thesis topic: effects of initial stress conditions on the magnetic properties of steel

Honours Bachelor of Science – Lakehead University

  • Major: Physics with specialization in Energy & Fuel Science

Patents And Publications

Distributed Mode System for Real-Time Acoustic Emission Monitoring (US7080555B2)