Data & Analyst · Statistical Modelling · Machine Learning · AI
Looking beyond the numbers, bringing depth to every analysis.
I work across the full analytical process: preparing and exploring data, testing relationships, building and evaluating models, and reporting findings clearly. I care most about why one method fits a problem better than another.
11
end-to-end projects
6
domains
CV · NLP · statistics · time series · ecology · operations
4
live applications
2
co-authored analyses
01 / About
A short introduction
I enjoy working with data and understanding what it can tell us beyond the numbers. I work with Python, R, and SQL, applying statistical methods such as hypothesis testing and regression from basic to more advanced approaches, along with time-series analysis, multivariate analysis, machine learning, deep learning, and applied AI.
Before moving into data and analytics, I spent over four years working in IT and systems, which gave me a practical and methodical approach to problem-solving that I continue to bring to my work today.
My work spans
- Statistical Methods
- Statistical Testing · Hypothesis Testing · Regression (Basic to Advanced)
- Simulation & Optimization
- Simulation Modelling · Optimization · Queueing Networks
- Machine Learning
- Algorithms · Supervised & Unsupervised Learning · Model Evaluation
- Time Series
- Temporal Analysis · VAR · Forecasting · Sequence Modelling
- Multivariate Methods
- Distance Metrics · PCA · Multivariate Analysis
- Deep Learning
- Neural Networks · Bi LSTM · LLM Fundamentals
- Applied AI
- RAG · Semantic Retrieval · Conversational Systems
- Database Management
- Database Design · Querying · Data Management
02 / Tools
What I work with
- Languages
- PythonRJavaScript
- Machine learning
- PyTorchscikit-learnLangChainGemini API
- Data
- pandasNumPyMongoDB Atlasggplot2
- Apps & deploy
- FlaskStreamlitRender
- Workflow
- JupyterGitGitHub
- Visualisation
- Tableausf / Leafletdplyr / tidyr
Education
Post-Baccalaureate Diploma, Applied Data Science
Thompson Rivers University · 2024 – 2026 · Dean's List (Fall 2024 & Fall 2025)
Certifications
- Fundamentals of Deep Learning (NVIDIA), Mar 2025
- Fundamentals of Visualization with Tableau, Jul 2025
03 / Work
Selected projects
Eleven projects across computer vision, NLP, statistics, time series, ecology and operations. Use the arrows or swipe.
04 / Explore
Where to go next
11 projects
Work
Machine learning, statistics, simulation and applied AI, each traced from question to result.
7 analyses
Case studies
Shorter statistical investigations: one research question, one dataset, a defensible answer.
Timeline
Experience
Education, earlier IT and systems work, awards and certifications.
Approach
About
How I think about a problem, what I work with, and what I care about in an analysis.