Mattie Gisselbeck
Geospatial Consultant Intern at Esri
© Mattie Gisselbeck
Geospatial Consultant and Developer Leveraging Data Science and GIS for Multidisciplinary Informed Decision-Making
I recently graduated from the University of Minnesota with a Master of Science in Geographical Information Science, with an emphasis in Data Science. Throughout the MGIS Program, I held various roles as a Graduate Research Assistant and Graduate Teaching Assistant, and I interned at Travelers as a Geospatial Consultant. My academic journey at the University of Minnesota has been marked by a consistent ability to translate theoretical knowledge gained both in and outside the classroom into practical applications across a range of professional contexts. Currently, my studies in the MGIS Program are focused on data science, AI, and machine learning. My primary research interests are centered around utilizing spatial data science and machine learning methods to tackle optimization issues.
3+
Years of
Experience
50+
Projects Completed
900+
Network Connections
Education
SEPTEMBER 2022 - MAY 2024
University of Minnesota, Minneapolis, MN — Master of Geographic Information Science
Emphasis in Spatial Data Science
Relevant Coursework: Spatial Data Science I, GIS Project Management, Spatial Data Science II, Principles of Geocomputing, Advanced Geocomputing, Spatial Database Design and Administration
Advisor: Dr. Bryan Runck
Awards: Esri Innovation Program University of Minnesota Student of the Year, 2024; Best Presentation of Research, 2023.
SEPTEMBER 2018 - MAY 2022
University of St. Thomas, St. Paul, MN — Bachelor of Arts in Psychology
Minor in Sustainability
Relevant Coursework: Geography of Global Health, Remote Sensing
Honors and Awards: St. Thomas Award, 2018; Matthew Hoff Memorial, 2018.
Experience
University of Minnesota, Minneapolis, MN — Graduate Teaching Assistant
JANUARY 2024 - PRESENT
Principles of Geocomputing
JANUARY 2023 - MAY 2023
Principles of GIS: Instructed two lab sections. Hosted regular office hours to support students with gaining a better understanding of fundamental GIS principles and spatial analysis. Received a letter of recognition from the Center for Educational Innovation for dedication to student learning.
University of Minnesota, St. Paul, MN — Graduate Research Assistant
AUGUST 2023 - JANUARY 2024
GEMS Informatics: Collected biotic threat analytics on seven different invasive species for risk assessment. Created a system for organizing literature, literature reviews, and data.
JUNE 2022 - JANUARY 2023
Department of Forest Resources: Conducted and assisted with research quantifying the role of state and private forest lands in providing surface drinking water for Minnesota, Wisconsin, and the St. Croix River. Created a series of StoryMaps to display the results for the Upper Mississippi River, Minnesota, and Wisconsin.
Travelers, St. Paul, MN — BI&A LDP Geospatial Intern
AUGUST 2023 - JANUARY 2024
Developed an ETL pipeline using a Python script to transform and standardize GPS track telematics. Generated participant facing web maps and instant applications to visual boating history and behavior. Designed a data processing pipeline using a Jupyter Notebook to ingest feature and imagery-based data using Nearmap API. Supported the creation of the Enterprise CAT Storm Surge Hazard layer.
City of Stillwater, Stillwater, MN — GIS Intern
JUNE 2023 - AUGUST 2023
Supported the development, maintenance, and implementation of Stillwater’s geospatial system. Assisted in spatial database management, web mapping, map creation and design, data collection, and data analysis. Encouraged Stillwater’s transition to ArcGIS Online and ArcGIS Pro. Developed a new and efficient system to organize Stillwater’s GIS data, maps, and documents.
Skills & Expertise
Geographical Information Science, Data Science & Computer Science
ArcGIS Pro, ArcGIS Online & ArcGIS Enterprise
Extentsions: Geostatistical Analyst, Spatial Analyst, Network Analyst, ArcGIS API for Python, ArcPy,
Applications: ArcGIS API for Python, ArcPy, Dashboards, Notebooks, ArcGIS StoryMaps, Experience Builder, Survey123
Data Science & Computer Science
Languages: Python, SQL, HTML, CSS, JavaScript, R
Libraries & Packages: scikit-learn, sci-py, Pandas, Geopandas, Numpy, Matplotlib, SQLAlchemy, Requests, Flask
Tools: Git, Postgres
Web Development & Cloud Computing
Front-End & Back-End Web Development
Google Cloud Platform
Amazon Web Services
Leadership & Involvement
Officer
GIS Student Organization (GISSO)
Managed the social media accounts for GISSO (Instagram, Facebook, and Google Site). Designed content for social media and events. Assisted with administrative tasks such as communication, event planning, and organizing weekly meetings. Assisted with financial management.
2022 - 2023Featured Projects
Brown Marmorated Stink Bug Transmission Risk Across Minnesota
University of Minnesota
An end-to-end analysis pipeline that assesses Brown Marmorated Stink Bug (BMSB) transmission risk across Minnesota by to processing input data, performing analytics, and serving the results out via an Swagger API. The workflow makes use of several Python libraries, like ArcPy, pandas, psycopg2, and Flask. For more information, view GitHub repository below.
Puerto Rico’s Spontaneous Reforestation
University of Minnesota
The aim of this project was to determine the most significant factors contributing to forest transition (~1950s-2000s) and to find a model that best predicts forest cover based on the explanatory variables. The explanatory variables under consideration comprise slope, soil productivity, precipitation, poverty rate, population density, and land protection level. This project utilized Python and spatial statistics to examine Puerto Rico’s forest transition. To view the associated StoryMap, click here.
Environmental Justice Concern Prediction Using Machine Learning
University of Minnesota
This project utilized a machine learning model, Random Forest, to predict whether census tracts in the Twin Cities Metro Area (TCMA) are areas of environmental justice concern and visually display the predictions using an interactive map.
Surface Water for Forest Lands for the Upper Mississippi River
University of Minnesota
Forests provide the most stable and highest quality water supplies among all land uses. Forests cover around 34.6 percent of the land in Minnesota and 49.1 percent in Wisconsin. All of the forests in Minnesota and Wisconsin are owned and managed by either federal, state, local (county and local governments), or private entities, thus it is critical to understand the role of these forest lands in providing water across the state and region. To view the associated StoryMap, click here.
Related: Benefits of Forest Lands for Surface Water in Wisconsin, Benefits of Forest Lands for Surface Water in Minnesota
2023