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Data Scientist with strong development background and 15+ years of experience using quantitative methods to solve challenging problems.


  • Python, Docker, Pandas, Scikit-Learn, Lifelines, Falcon, Flask, NumPy, TensorFlow, OpenCV
  • Java, Spark, Kafka Streams, Mahout, Akka, Elasticsearch, MongoDB
  • Javascript, JQuery, Bootstrap, Plotly.js
  • Data Cleaning, Modeling, and Mining
  • Machine Learning, Survival Analysis, NLP, Graph Algorithms
  • Deep Learning, Image Classification, Object Detection, Computer Vision, Image Processing, Forecasting


MSc. Physics

Queen’s University

Honours BSc. Physics

Lakehead University


Data Scientist - Officer

Wealth Management & Investment Services, U.S. Bancorp

April 2019 - Current

  • Built “flight risk” application to identify investments, accounts, and clients likely to leave the bank using survival analysis
  • Developed real-time investment / account balance forecasting algorithm based on deep learning
  • Built incident prediction algorithm based on Random Forest and time-series ensemble forecasting to provide early warning of stability issues in business-critical applications

Software Engineer

Data Science, C.H. Robinson

April 2017 - April 2019

  • Built document classification application based on deep learning and image processing to identify incoming shipping documents. In production the solution examines nearly 35,000 images per day and is 84% correct in its predictions.
  • Built signature detection application based on deep learning, object detection, and image processing to identify whether a packing list had been signed by the recipient. In pre-production, the solution examines several thousand documents per day and is correct more than 96% of the time when its confidence is 60% or greater.
  • Designed an algorithm for automatically extracting fields such as invoice amount and payee from OCR data without training a model using similarity metrics, Named Entity Recognition (NER), and graph edit distances.


Emphysic LLC

August 2015 - April 2018

  • Funded by NASA to design a distributed algorithm based on online learning, image processing, and pipeline parallelism to automatically detect structural damage in aircraft. A visualization of the algorithm is available at and a demonstration of the subsequent application is available at .

Data Analytics Engineer

Contata Solutions

April 2015 - February 2016

  • Developed proof of concept approach for finding anomalies in customer rewards card program data with BIRCH clustering, outlier detection, and Spark.
  • Designed a NoSQL Data Lake based on Cassandra and Elasticsearch for aggregating customer data from multiple sources and schema into a single datastore.

Computational Physics Programmer

Computational Physics, Canadian Nuclear Laboratories

September 2013 - April 2015

  • Built an extensible application for automatic analysis of nuclear reactor simulation data based on Natural Language Processing.


NDE Division, TRI/Austin, Inc.

October 1999 - September 2013

  • Patented a statistical approach to assessing the structural integrity of aircraft and helicopters in real time during flight, used to predict future health and recommend a course of action to mitigate. First successful test flight in 2006 on an F-15/E and the basis of more than $1 million in revenue for the company.

Magnetics Engineer

Pipetronix Ltd.

August 1998 - October 1999

  • Developed a model of the behavior of the magnetic field around an in-line inspection tool as it moved through the pipeline, used to determine the bias in sensor readings as a function of velocity.