Curriculum Vitae

A PDF version of my CV is available to view or download here.

Education

 
 
 
 
 
MSc in Geophysics
University of California, Davis
September 2024 – Present Davis, CA
 
 
 
 
 
BA in Computer Science, Minor in Earth & Planetary Sciences, Supplementary Minor in Computer Science
McGill University
September 2019 – May 2023 Montreal, QC
  • GPA: 3.75/4.0

Skills

  • Programming Languages: Python, Julia, C++, C, Java, DB2/SQL/MySQL, R, Bash, MATLAB, HTML/CSS, OCaml, MIPS Assembly * Tools: Git, Linux/Unix, LATEX, Jupyter, AWS EC2, VS Code, RESTful APIs, MongoDB, Jira, Jenkins

Experience

 
 
 
 
 
Technology Analyst
Morgan Stanley
July 2023 – August 2024 Montreal, QC
 
 
 
 
 
Data Science Intern
Esri Canada (Spot On Systems)
May 2022 – August 2022 Remote
 
 
 
 
 
Software Engineering Intern
Blue Spiral Interactive/Albany IT Group
August 2019 – June 2019 Saratoga Springs, NY
 
 
 
 
 
Software Development Intern
Garnet River
February 2019 – June 2019 Saratoga Springs, NY

Projects

30 September 2023 Hackathons, Personal Projects
MAISpeare

Hackathon Project created at MAIS Hacks 2021, winner of the Best AI Hack for Art.

Code Slides Video
29 September 2023 Research
Building an Accessible Machine Learning Workflow for Geospatial Analysis

Starting in Fall 2022, I began working with Dr. Matthew Tarling and Dr. Jamie Kirkpatrick at McGill University to develop a deep learning (DL) workflow for geospatial analysis. Inspired by challenges we faced developing a DL model for landslide identification, we decided to create a free, open-source workflow for processing geospatial data and training DL models on the processed data.

Code Slides
29 September 2023 Research
Using U-Net to Detect Landslides

During my undergraduate degree, I worked with Dr. James Kirkpatrick and the California Geological survey to develop a custom machine learning model based on U-Net architecture to detect landslides in satellite imagery.

Slides

Awards

Bogo Hack @ MAIS Hacks 2022
McGill Artificial Intelligence Society (MAIS) Oct 2022
  • Created a web app (Python, HTML/CSS, Google Earth Engine) that predicts the price & quality of a bottle of wine from climatological conditions of the year & region it was produced with sequential neural network.
Achievement Unlocked, Best Design @ McHacks9
McHacks Jan 2022
  • Led a team to create a COVID-19-themed Pac-Man webGL game using the Unity Game Engine (C#).
  • The game can be played at this link!
Best AI Hack for Art @ MAIS Hacks 2021
McGill Artificial Intelligence Society (MAIS) Oct 2021
  • Led a team to create a web app, MAISpeare (Python, HTML/CSS) that generates a poem from an image using an LSTM.
Geotop 2021 Scholarship Competition
Geotop May 2021
  • Selected based on my research proposal to Use ML to Indentify Landslides & my academic performance.
Best Overall Hack @ MAIS Hacks 2020
McGill Artificial Intelligence Society (MAIS) Oct 2020
  • Led a team to create a web app (Python, HTML/CSS) that predicts MBTI Personality Type based on Twitter data using a XGBoost-driven neural network.
Alma Mater Scholarship
McGill University Sep 2019
  • Entrance bursary to McGill University for academic excellence.

Extra-Curricular Activites

Member
Machine Learning for Geoscience Reading Group (McGill University) Jan 2021 – May 2021
  • Participated in an informal reading group with faculty and researchers to examine current papers in ML applications in the geosciences.
Vice President Communications
The Monteregian Society (McGill University) Sep 2020 – Apr 2023
  • Managed communications for the undergraduate student council for Earth & Planetary Sciences.
  • Designed & built the council’s website to host student resources, events, & other information.

Professional Development

SCIWS12 Tutorial on Machine Learning and Deep Learning for the environmental and geosciences
American Geophysical Union (AGU) Dec 2020
MAIS 202: Accelerated Introduction to Machine Learning
McGill Artificial Intelligence Society (MAIS) Jan 2020 – May 2020
  • Selected through a technical interview to participate in a 12-week accelerated course on machine learning.
  • Webscraped data to train a CNN to classify geologic sample images into 4 classes; deployed as a webapp. Check out the repo here.

Publications

Nathalie R. Redick (2023). Building an Accessible Machine Learning Workflow for Geospatial Analysis.

Cite Project

Nathalie R. Redick (2023). A Review of Pumice Raft Formation Environments, Saturation, and Dispersal Mechanisms. McGill Science Undergraduate Research Journal.

Cite DOI