I will be completing a Master of Data Science (MDS) degree at the University of British Columbia in June 2021. I also have over 11 years of consulting experience in water resources as a senior engineer providing analysis and management of data collection programs. While working in this area, I developed an interest in applying machine learning to support analyses typically approached using more traditional methods, as well as the use of interactive applications to better communicate results and uncertainties. After several years of informal learning using R and Python, I am completing the Masters degree to further develop in these areas of interest.
My consulting experience includes managing hydrology data collection programs, data analysis, probabilistic water balance and energy modelling, development of in-house data analysis and visualization tools, and open channel numerical modelling. I have worked on projects in the hydropower and mining sectors ranging from conceptual design and project viability assessments to environmental permitting and operational modelling.
Master of Data Science, In Progress (June 2021)
University of British Columbia (Okanagan)
Bachelor of Applied Science (Civil Engineering), 2008
University of British Columbia (Vancouver)
Approach for open-source near real-time anomaly detection with InfluxDB time series database using a LSTM neural network
R Package API Wrapper for the Government of Canada Vehicle Recalls Database published on CRAN
Shiny R application hosted on AWS to explore Water Survey of Canada hydrometric data and conduct data summarization and flood frequency analysis
Shiny R application hosted on both AWS and shinyapps.io to bulk download Environment Canada climate data and view summaries of available/missing data
Data Collection and Analysis:
Development of In-House Data Tools:
Probabilistic Balance Modelling: