MS Applied Data Science @ The University of Chicago · Business Engineering @ KU Leuven
I work at the intersection of data science and business strategy — building models that translate cleanly into decisions for non-technical stakeholders. My training spans classical statistics (OLS, GLM, time series), applied machine learning, and modern NLP (transformer fine-tuning, RAG pipelines, topic modeling at scale). I'm most interested in roles where quantitative work has to make it out of the notebook and into a conversation with an operator, an analyst, or a founder.
I grew up across six countries, hold dual EU/US citizenship, and work in four languages. That background makes me particularly drawn to companies operating across borders — marketplaces, fintech, mobility, and logistics platforms where the data is messy in more than one jurisdiction at a time.
- Spring 2026 capstone with HERE Technologies — building an AI agent that automates quality checks on operator-resolved support tickets (team "Ground Truth").
- Coursework in Generative AI (RAG systems, embeddings) and ML II (optimization, regularization, transformer architectures).
- Portfolio build-out — migrating academic and consulting projects into public repositories with proper documentation.
| Project | Domain | Stack | Repo |
|---|---|---|---|
| Carbon Intensity of Electricity — Cross-country OLS | Energy · Econometrics | Python · statsmodels · HC3 robust SE | carbon-intensity-regression |
| AI Impact Analysis — 191K news articles, 2022–2026 | NLP at scale | BERTopic · DistilBERT fine-tuning · spaCy NER | ai-impact-analysis |
| WELFake Fake News Detection | Applied ML | scikit-learn · Ridge Classifier · text pipelines | welfake-fake-news-detection |
| CTA Ridership Forecasting | Time series | SARIMA · GARCH · Prophet · LSTM | cta-ridership-forecasting |
| HERE Places: Customer Issue Management | LLM agents | RAG · evaluation · workflow automation | in progress |
Each repo includes a detailed README, reproducibility instructions, and methodology notes. For write-ups of projects I can't open-source (company take-homes, consulting engagements), I'm happy to share privately on request.
Languages Python · R · SQL · LaTeX Machine learning scikit-learn · statsmodels · PyTorch · Hugging Face Transformers NLP transformers · spaCy · BERTopic · ChromaDB · sentence-transformers Time series ARIMA / SARIMA · GARCH · Prophet · LSTM · DeepAR · N-BEATS · TimeGPT Data & BI pandas · NumPy · Power BI · Microsoft Fabric · ETL pipelines Visualization matplotlib · seaborn · Plotly Tooling Git · Jupyter · Linux · Docker (intermediate)
Education
- The University of Chicago — MS in Applied Data Science (2025–2026) — merit scholarship
- KU Leuven — Business Engineering
Selected experience
- Data & Business Intelligence Intern — SMT Belgium (Power BI, Microsoft Fabric, ETL, governance standards)
- Consultant — UChicago Gargoyle Consulting Club (healthtech AI startup engagement)
- Research contributor — KU Leuven × NGO Sabore's Well (humanitarian water pricing, Kenya)
- PIP Consultant — Ray & Jules Sustainable Coffee (competitive intelligence)
- Secretary & Marketing — Rotaract KU Leuven
Languages English · Dutch · Italian · French
- LinkedIn — www.linkedin.com/in/matteo-mirgone-6b58ab246
- Email — matteo.mirgone@gmail.com
- Location — Chicago (US) · Netherlands (EU) · open to relocation