I work at the intersection of data science and human behaviour, helping institutions benchmark performance, evaluate innovation ecosystems, and make evidence-based decisions.
I'm an analyst at EFIS Centre, a Brussels-based consultancy specialising in research and innovation policy for EU-level clients, including the European Commission. My day-to-day involves data analysis, quantitative modelling, report writing, and helping EU institutions understand how member states perform across innovation, sustainability, and competitiveness dimensions.
My academic path — spanning mathematics, psychology, and data science — gave me a somewhat unusual toolkit: quantitative rigour, a feel for behavioural nuance, and the technical skills to bridge the two. I'm most energised by work that sits in that gap between raw data and the human decisions it's meant to inform.
Outside of work, I follow Formula 1 and basketball (and frankly any other sport) with possibly excessive analytical attention, and I'm working toward completing an Ironman triathlon at some point before I come to my senses.
A selection of analytical projects I've contributed to, spanning scoreboard development, qualitative research, and data visualisation.
Contributed to the design and production of the ESS for the European Commission, developing R scripts for automated visualisations, generating country reports, and writing analytical commentary on EU27 member state performance.
Conducted deep methodological analysis of indicator selection rationale and data quality for the EII revision. Included hands-on validation of datasets and refined R-based analytical scripts for data processing.
Led the design and execution of a large-scale, AI-based qualitative analysis pipeline for the ST4TE Horizon Europe research project, processing ~400 interview narratives across multiple research questions using multi-step synthesis workflows and prompt engineering.
Contributed to analytical work on the European Innovation Scoreboard, including composite indicator methodology (COINr framework), Eurostat data extraction, and member-state benchmarking across innovation dimensions.
Led the design and execution of a large-scale, AI-based qualitative analysis pipeline for the ST4TE Horizon Europe research project, processing ~400 interview narratives across multiple research questions using multi-step synthesis workflows and prompt engineering.
The technical and analytical capabilities I bring to my work — spanning programming, data analysis, and policy research.
I also enjoy writing articles from time to time. Here's a list of selected pieces I've worked on.
A short description of the article — what it covers, why it matters, and the key takeaway. Keep this to two lines for visual consistency.
EU PolicyBrief description of the piece — the question it addresses, the data behind it, and the conclusion it reaches.
Data AnalysisSummary of the article's argument or findings. This section is designed to be easily extended — just duplicate the block and fill in new content.
Innovation