CSS, SASS, and frameworks (Bootstrap, Materialize, Materialize Design Boostrap)
Node.js + Express, Python + Flask
Data: shp, osm xml/pbf, geojson, wkt, wkb, images (geotiff, jpg, png), imagery (Landsat, Sentinel-2), kml, GPS tracks
Geospatial processing and analysis: QGIS, OpenStreetMap (iD, JOSM), GDAL, PostGIS, Esri products (e.g., ArcMap, ArcPro, ArcOnline), GeoServer, Valhalla, OpenRouteServices, other open-source geospatial libraries/software (e.g., R and Python packages like rgdal and geopandas)
Web mapping: Mapbox GL JS, Leaflet (R, Folium, or JS), Google Maps API, OpenLayers, D3.js
Data: json, geojson, shp, (satellite) imagery, tiff, csv, kml, osm xml/pbf, R/Python data frames, sas7bdat, unstructured text (tweets, free text)
Mgmt: SQLite, PostgreSQL(+PostGIS), Oracle, Microsoft SQL Server, MongoDB
Analytics & Machine Learning: R, Python (e.g., Keras, TensorFlow), Stata, GeoDa, SAS
Visualizations: D3.js, R Shiny Apps + Plotly + Leaflet, Tableau, PowerBI
Architecture: client-server (RESTful API), pipline, database-centric, event-driven
Environment: package/library mgmt (npm, pip, conda, R), version control (git, GitHub, Bitbucket, GitLab)
- June 2021 - Present
Casual / On-Call GIS Developer for Nauttiqsuqtiit Research and Monitoring Map
Developed a participatory mapping platform with open source software (Nunaliit SDK) to collect geographic information for conservation priorities in parts of the Canadian Arctic. Currently facilitating collection with participating communities. Also developing static maps in QGIS for reports.
- August 2020 - Present
Senior GIScientist at Statistics Canada
Lead GIScientist at Statistics Canada's Data Exploration and Integration Lab. Supporting projects that apply alternative methods for passive and active data collection (e.g., computer vision, image processing, crowdsourcing) and dissemination of geographic information and services. For example, I am leading the Linkable Open Data Environment (LODE) Viewer.
- January 2018 - August 2020
Senior GIScientist at Employment and Social Development Canada
Supported evidence-based decision making through the following: researched and devised advanced geospatial techniques (e.g., calculating spatial accessibility for identifying underserved areas); designed and developed software and web apps to host statistical, analytical, and machine learning models; and, educated internally and externally on how to leverage geographic data with open source tools (FOSS4G).
- Cleaned, analyzed, and visualized spatially-referenced survey, crowdsourced and administrative big data in R and Python (e.g., spatial accessibility index calculations for services/programs).
- Designed and developed web apps (full stack) with Node.js or Python for pushing machine learning models into production.
- Initialized and managed SQL and noSQL databases.
- Developed interactive visualizations with D3.js or R for sharing research results to inform policymakers.
- Managed product development. For example, led the design, development and implementation of an open source technology, PASS.
- Prepared, wrote and presented presentation decks, briefing notes, and reports to upper management, with a twist (e.g., generate GIFs to demo apps, simple HTML web page as PowerPoint alternative)
- July - December 2017
Data Intern at Mapbox
- Remote mapped on OpenStreetMap (OSM) with JOSM and iD Editor.
- Developed Node.js based validators to assess the quality of OSM data.
- Developed data visualizations from OSM data and administrative data with Mapbox GL JS and React (e.g., Crimecouver and BC2020 Mapathons).
- Organized nation-wide multi-stakeholder workshops (e.g., Building Canada 2020) as well as local community events. Check out my post on Mapbox's "Points of Interest" blog.
- Taught English through running daily lessons to learn reading and writing, as well as immersive activities to improve listening and speaking.
- February - June 2017
Contracted Geographic Information Systems Technician at Statistics Canada
- Communicated and maintained engagement with stakeholders for Statistics Canada first crowdsourcing project.
- Collected, managed, monitored, analyzed and visualized large administative and crowdsourced spatial datasets with R and Python.
- Researched and designed a mobiled crowdsourcing web app as well as a method to quality assure crowdsourced building footprint data.
- Developed a spatial server with PostGIS and Node.js for quality assurance adn web mapping services. Code can be seen on the GitHub repo.
- Advised internal stakeholders on open data licensing and open source software.
- August 2016 - June 2017
Freelance Open Data Consultant & Full-Stack Web Developer
To increase transparency on where and what different resource extraction companies are paying organizations across Canada, I was tasked to develop a real-time interactive map dashboard for Open North and Publish What You Pay Canada. To accomplish this, I collected and managed a database of payments to government organizations from extraction companies; and, with the data, designed and developed an interactive Mapbox.js map and D3.js dashboard web app. Check out the code on the GitHub repo.
To increase the adoption of open data standards and to ultimately improve interoperabiltiy across different civic datasets, I was tasked to develop a website for Johns Hopkins University’s Center for Government Excellence. I designed and developed the user interface, managed data with a PostgreSQL database, and developed a Node.js web app hosted on Heroku. Check out the website.
- May - August 2016
Research Assistant at Geothink
Research assistant for Geothink’s Civic Open Data Standards project. I (1) assessed Canadian municipal datasets and open data portals; (2) designed and developed a web app to host a catalog of open data standards; and (3) designed, conducted, and transcribed semi-structured telephone surveys. Code can be seen on the GitHub repo.
2020 - 2022Master of Science at Carleton University
Department of Geography and Environment Studies, with a specialization in Data Science
Community-based Geomatics, co-developing web-based geovisualizations and supporting a community-led monitoring program
- Developed Convolutional Neural Network binary classifier to predict if images of building exterior pathways are "accessible" or "inaccessible" for those dependent on wheeled mobility devices. Used class activation mapping to better interpret model predictions. The scripts and model architecture are available on GitHub.
2012 - 2016Bachelor of Arts at McGill University (Graduated with Distinction)
Major: Geography; Minors: Geographic Information Systems, Remote Sensing, Anthropology
Activities: Big Buddies Tutoring (2015); Drive Safe (2013); McGill Varsity Soccer Team (2012-2013); Maptime MTL (2015-2016)
- With Python, mined thousands of georeferenced tweets and then managed, analyzed, and visualized the spatial and temporal.
- Developed a web app that automatically scraped, standardized, and mapped Kijiji real-estate postings.
- Designed an online survey, coded the data, and then spatially predicted where new dumpsters should be located in Montreal.
- Ran a cost distance analysis that identified a new hiking path in North Vancouver.
October 2021Canadian Cartographic Association Best Student Presentation
March 2021Carleton University Data Day Poster Fair Winner
2020-2021Dean of Graduate Studies Entrance Scholarship for Domestic Students
2020-2021Duncan M. Anderson Graduate Scholarships in Geography & Environmental Studies
2020-2021Carleton Graduate Scholarship
December 2019Employment and Social Development Canada Assistant Deputy Minister Award for Excellence in Innovation
2019Employment and Social Development Canada Deputy Minister Award for Excellence in Innovation