Nathan Smith

Nathan Smith

Data Science | Water Resource Engineering

Knight Piesold Ltd.


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)




Statistics and Machine Learning

Interactive Data Tools

Project Management

Water Resources


Sensor Anomaly Detection

Approach for open-source near real-time anomaly detection with InfluxDB time series database using a LSTM neural network

Board Game Data Explorer

Board game data explorer app built using Plotly Dash and deployed on Heroku

caRecall R Package

R Package API Wrapper for the Government of Canada Vehicle Recalls Database published on CRAN

ShinyCFA App

Shiny R application hosted on AWS to explore Water Survey of Canada hydrometric data and conduct data summarization and flood frequency analysis

ShinyWeatherCan App

Shiny R application hosted on both AWS and to bulk download Environment Canada climate data and view summaries of available/missing data


Exploration of streamflow estimation in British Columbia using machine learning



Senior Engineer

Knight Piesold Ltd

Sep 2009 – Present Vancouver, Canada

Data Collection and Analysis:

  • Data collection and management of large data collection programs with projects consisting of up to 50 stream gauges and multi-year timelines.
  • Analysis of energy and hydrometric data to support financial modelling, project design, and permitting requirements.
  • Time series modelling, extreme value analysis, and long-term synthetic data generation using statistical and machine learning techniques.

Development of In-House Data Tools:

  • Interactive data visualization and analysis tools built in R and Python.
  • Tools developed to reduce time spent on data processing, improve quality control of analyses, and better communicate results and uncertainties to project teams and clients.
  • Technical support and user interface feedback for software development teams working on in-house data management software.

Probabilistic Balance Modelling:

  • Development of water balances and energy models to assess potential future conditions supporting decision making on mining and hydropower projects.
  • Application of deterministic scenario-based assessments and probabilistic sampling methods.

Project Management:

  • Managed multi-year projects with annual budgets of up to $1M.
  • Budget and schedule control, client communication, multi-discipline team management of up to 10 staff, technical reviews, and mentoring of junior staff.


  • BC, Canada