IT Graduate
Resume:
Thea Roseanne Jaeger
Graduate Computer Scientist MSc
****.********.******@*****.*** Pretoria, SA
EDUCATION
MSc Computer Science
(Conversion)
University College Dublin Dublin, IE
Awarded First Class Honours
BIS (HONS) Information
Science 2015-2016
University of Pretoria Pretoria, SA
Graduated with Distinction
BIS Information Science (cum laude)
2012-2014
University of Pretoria Pretoria, SA
Graduated with Distinction
SKILLS
Languages
Python Java JavaScript
C# Bash CSS3 HTML5
SQL
Frameworks
Bootstrap Flask
Familiar
Ruby Git Maven
XGBoost EC2 MySQL
Random Forest Docker
COURSEWORK
Python and OOP
Machine Learning with Python
Big Data
Data Mining
Java
Distributed Systems
Web Development
Software Engineering
Data Programming with R
Operating Systems
Relational Databases
Ruby
Information Security
EXPERIENCE
Computer Science Demonstrator UCD CS Department
Jan 2024 – Dec 2024
●Taught more than 50 undergraduate students over the course of
“Computer Architecture” module.
●Graded assignments, ensuring students received feedback on time.
Forensic Research Analyst Nexus Forensics
Jan 2018 – Aug 2022
Conducted data analysis and forensic research with a focus on Open-Source Intelligence (OSINT). Key responsibilities included:
Performing OSINT investigations to collect and analyse publicly available information.
Gathering, analysing, and interpreting large datasets to uncover insights and patterns using IBM i2 Analyst's Notebook.
Compiling Due Diligence and Lifestyle Audit Reports to assess financial and behavioural risks.
This role honed my ability to conduct thorough investigations using advanced digital tools and methodologies, enabling me to navigate and analyses online information sources for intelligence gathering and investigative purposes effectively.
PROJECTS
Smart City Explorer Group Project
Jun 2023 - Aug 2023
A ML Full Stack application to predict busyness levels within Manhattan and gamify the travel experience.
●Developed and optimised two ML models (Random Forest and XGBoost) to predict busyness levels in Manhattan with a focus on enhancing accuracy and reducing prediction response time.
●Implemented a Random Search hyperparameter tuning strategy to iteratively improve the Random Forest model, resulting in robust model performance.
●Created a Flask application to serve ML model predictions, utilising JSON for efficient backend communication.
Dublin Bikes Dashboard Group Project
Feb 2023 - May 2023
A ML Flask application to calculate the best available Dublin bike station to collect and dock city bikes with relevant route and weather information.
●Acted as a Scrum Master and managed the project team. Carried out code reviews, version control and documentation for the project.
●Implemented key features such as bike station heatmaps, geolocation tracking, and dynamic data visualisation, using AJAX, JSON, and third-party APIs.
●Developed and integrated a real-time weather data feature.
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