About
I am a data scientist keen on learning how to build websites. During some months of unemployment, I decided to start this website for fun and to polish it as much as possible.
Besides making this website look pretty, my interests include machine learning, network analysis, natural language processing, and geospatial data.
Currently
Collaborating as a research assistant in the Cataloguing Crop Traits and Breeders Across the OECD 1980-2025 project (financed by the Carlsberg Foundation).
Core Skills
- Machine Learning
- NLP (Transformers, Topic Modeling, RAG)
- Python (pandas, numpy, scikit-learn, PyTorch, TensorFlow)
- Geospatial (Geopandas, Rasterio, QGIS)
- Data Visualization (Matplotlib, Seaborn, Tableau, Power BI)
- Docker, Git, AWS, UCloud, CI/CD, ETL, SQL
Projects
Mobility and Income Segregation in Madrid, Spain
Detailed portfolio entry describing my master’s thesis work.
Directory-to-Graph Visualization
Turn any folder into an interactive tree graph in the browser.
Breast Cancer Prediction
Small cancer prediction project.
LLM-Powered PDF Retrieval
Using Mistral, LangChain, and RAG to turn PDFs into structured data.
Design Portfolio
I like to draw and to sometimes digitalize what I draw.
Monet-Style Painting Generation Using CycleGAN
Academic project.
git-notes
A Git cheatsheet based on traumatic experiences during projects.
Recommendation app for POIs in Montreal
Geospatial Data Science project work on Montreal, a 15-minute-city.
QA Tool in Different Languages
Creating a question-answering tool for different languages.
Publications
Divine Policy: The Impact of Religion in Government
I had the chance to collaborate on this paper as a research assistant. The paper examines the impact of policies on personal values and beliefs by exploiting the staggered introduction of the faith-based initiatives across US states. A difference-in-differences analysis reveals that the initiatives strengthened religiosity and conservative-religious social views, such as attitudes against homosexuals.
Divine Policy: The Impact of Religion in Government (2026). Jeanet Sinding Bentzen, Alessandro Pizzigolotto and Lena Lindbjerg Sperling. Forthcoming at the AEJ: Applied Economics. Previously circulated under the title God Politics.
CV
You can access a PDF version of my CV here.
Summary
Data Scientist with hands-on experience building machine learning and NLP models (including RAG and topic modeling) and scalable containerized data workflows. Interests span network analysis, geospatial data, and applied machine learning for actionable insights.
Experience
Research Assistant, Data Science
- Collaborating as a research assistant in the Cataloguing Crop Traits and Breeders Across the OECD 1980-2025 project (financed by the Carlsberg Foundation).
- Building a unified database with all new cereal varieties released in the OECD since 1980, their traits and breeding history, and information about the companies involved in developing them.
- The database will be the first large, unified database of its kind, and will be instrumental for exploring how to improve the crop innovation system to increase the global food supply without expanding cropland into pristine environments.
Research Assistant, Data Science
- Contributed to the Shocking Religion project.
- Built topic models to uncover thematic trends in text data.
- Built RAG-based LLM pipelines for document insights.
- Designed and containerized scalable ingestion & preprocessing workflows (UCloud).
- Coordinated with multidisciplinary research team.
Data Scientist
- Automated data workflows to improve efficiency.
- Developed computer vision brand logo detection models.
- Dockerized solutions for reproducible ML workflows.
- Collaborated with product to refine output quality.
Marketing Strategist
- Analyzed campaign performance (Google Analytics, Ads).
- Automated internal reporting with Python scripts.
- Competitor analysis and audience benchmarks; stakeholder reporting.
Education
M.Sc. Social Data Science
- Thesis: Mobility and income segregation in Madrid, Spain.
- Selected courses: Advanced Machine Learning (ITU), Geospatial Data Science (ITU), Advanced Network Science (ITU), Natural Language Processing (DIKU, University of Copenhagen).
B.Sc. Marketing and Computer Science Minor
- Magna Cum Laude.
- Dean's List (2018–2022).
- Best Graduating GPA (Marketing, 2022).
Skills
- Programming & Data: Python (pandas, numpy, matplotlib, tensorflow, pytorch, scikit-learn), SQL, Bash
- ML & NLP: Transformers, RAG, Topic Modeling (UMAP, HDBSCAN, BERTopic), Computer Vision, Predictive Modeling, Feature Engineering
- Visualization & Analysis: Matplotlib, Seaborn, Tableau, Power BI, Statistical Analysis, Data Wrangling
- Geospatial: Geopandas, Rasterio, QGIS, Spatial Analysis
- Cloud & DevOps: Docker, Git, Linux, AWS, UCloud, CI/CD, VSCode
- Other: LaTeX, Overleaf, Statistics
Languages
- Spanish (Native)
- Galician (Native)
- English (Professional)
- Danish (Beginner)
Awards
- Dean's List (2018–2022): GPA above 3.5 each semester.
- Best Graduating GPA Marketing B.Sc. (2022).
- Academic and Athletic Grant (2018–2022): Full scholarship for academic excellence and soccer performance.