Prefer a PDF? Here you go.
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
AI / ML Scientist – Datasite
- Research and develop solutions in support of Datasite’s suite of products targeting the mergers and acquisitions (M&A) sector
- Created an “investment recommender” deep learning model to recommend investments based on a client’s deal history and free-form search criteria
- Apply Natural Language Processing (NLP) techniques and technologies in the analysis of contracts and other documents
- Mentor and tutor new team members in Python, machine learning, data science, and statistics. Cultivate enthusiasm for and a deeper understanding of machine learning
Data Scientist (Officer) – U.S. Bank
- Collaborate with Global Fund Services to provide statistical analysis to answer weekly questions from executive team, such as the feasibility of forecasting dividends and demonstrating an approach to flag unusual transactions in real time
- Planned and assigned schedules and projects for an offshore data science team
- Implemented a document digitization strategy for extracting information from invoices
- Created an AIOps incident prediction model that reads metrics from Application Performance Management (APM) systems to predict whether the application is at risk of incident, providing detailed information about the risk factors
- Developed a customer attrition model based on survival analysis and random forest, interviewing relationship managers for clients determined to be at risk by the models to learn more about them
Founder – Emphysic
- Bootstrapped with NASA funding
- Developed a distributed algorithm for finding damage in aerospace structures, based on computer vision, machine learning, and pipeline parallelism
Data Science Engineer – C.H. Robinson
- Coordinated with Finance team and others to apply data science techniques into their workflow which were estimated to have been able to save over 200 hours of overtime per year
- Developed a deep learning model to determine whether a document had been signed. In production it scanned more than 35,000 images per day with over 96% accuracy
- Developed an approach to handling “orphaned” documents, reading the contents of the document to place it 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