Hi! I'm Guille, a Behavioural Data Scientist based in Spain with a background in electrical engineering and an MSc in Behavioral Data Science. I've worked as a Business Analyst at Santander Bank and recently designed a demographic analytics dashboard for UN ESCWA focused on Lebanon, handling everything from data processing to building interactive visualisations with Leaflet.js. My technical skills include Python, R, SQL, machine learning (Random Forest, XGBoost, clustering), data visualisation (Tableau, Shiny, Leaflet), and I'm comfortable with the full pipeline from wrangling to deployment (FastAPI, Docker, PostgreSQL). I'm drawn to projects at the intersection of behavioural data and social impact — particularly around wellbeing, mental health, education, or public policy — but I'm happy to contribute wherever the need is. I enjoy scoping messy problems as much as building the solution, and I work well in small, collaborative teams. I'm looking to contribute meaningfully to projects that matter while learning from others in the data-for-good space. Open to both short-term and longer engagements.

Personal information
Full name: Guillermo Martin de Oliva Carranza
User name: Guille1799
Organization memberships
Not a member of any organization.
Awards
No awards received yet.
Volunteer background
Education: Master's on Behavioral Data Science (Universitat de Barcelona)
LinkedIn profile
Github profile
Volunteer availability
Start date: April 26, 2026
End date: None
Hours available per week: 25
Volunteering interests
No stated preferences.
Skills
Skill
Beginner
Intermediate
Expert
Python
Computer Science (Algorithms)
Java
JavaScript
C/C++/C#
Haskell
Clojure
Ruby
PHP
Data in Text Files
SQL
Data in Relational Databases
Data from Sensors
Data > 1TB
Text Data (NLP)
Network/Graph Data
GIS tools
Geospatial
Multimedia Data (Video or Audio)
Data Visualization
Experience working on real-world problems using data
Experimental Methods (RCTs, A/B testing, etc.)
Social Science (Economics, Sociology, etc.)
Data Analysis
Causal inference
SVMs
Random Forests
Neural Networks / Deep Learning
Unsupervised models
Graphical models
Time Series Models
Semi-Supervised models
Decision Trees
Instrumental Variables
Matching (e.g., Propensity Score Matching )
Regression Discontinuity
R
Stata
Julia
Matlab
SAS
SPSS

Volunteer projects

No volunteer work yet.