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Francesco P.

Francesco P.

I don't know

Belgium flagSchaerbeek, Belgium

Key Skills

Software

No software listed

Top Subject Matter

Ranked by both depth
how rare/valuable they are for AI training work:
EU politics & policy — your standout. European Parliament
Council
legislative process

Top Data Types

TextText
DocumentDocument
ImageImage

Top Task Types

Text SummarizationText Summarization
DiagnosisDiagnosis
Text GenerationText Generation
Point/Key PointPoint/Key Point
Prompt + Response Writing (SFT)Prompt + Response Writing (SFT)
Data CollectionData Collection

Freelancer Overview

Francesco is a computational social scientist and AI builder with a decade of applied machine learning experience at the intersection of language, politics, and data. He pioneered NLP analysis of Italian political discourse — his 2018 work decoding Salvini's rhetoric was featured in Wired Italia — and has since trained and deployed production ML systems, including vote-prediction models for the European Parliament. He contributes to academic data infrastructure (V-Dem) and writes data-driven journalism for outlets like POLITICO Europe and The Parliament Magazine. Multilingual — native Italian, fluent English, B1–2 Dutch, plus classical languages — with a background in semiotics and structuralist analysis, he brings rigorous judgment to evaluating model outputs across reasoning, writing, and political-domain accuracy. He works daily with LLM tooling, giving him a practitioner's intuition for where models succeed, fail, and need sharper feedback.

Labeling Experience

Yes, please add AI/data experience

Yes, please add AI/data experience. I've trained and deployed production ML models — including a CatBoost vote-prediction model for the European Parliament — and built and annotated NLP datasets for Italian political-text classification. I contributed expert-coded data to V-Dem (Varieties of Democracy), which is essentially structured expert annotation, and I've worked on supervised bot-detection systems. I also work daily with LLM tooling, so I'm comfortable evaluating and giving feedback on model outputs. So: not platform-style data-labeling gigs, but hands-on experience with annotation, model training, and output evaluation.

Not specified

Education

D

did you read my cv?

Degree not specified

Not specified
Not specified

Work History

P

political forecasting

Founder & ML Lead, MEP Analytics (2025–present) — Built and trained production machine learning models

Location not specified
2025 - Present