Grounded in experience. Focused on clarity.

Hello, I am Virginia Levy Abulafia.

I work on complex problems, digging until structure, meaning, and usability emerge.


With over 20 years of experience in airport operations and hospitality, I developed a strong foundation in complexity management, coordination, and time-critical decision-making.
I now apply the same discipline to data analytics, business intelligence, and AI solutions for SMEs.

– Certified in Data Science
– Specialized in AI and AI Agents
– EITCA/AI European Certification (in progress)


I design analytical systems and dashboards that support operational clarity and informed decisions.
My work focuses on structure, reliability, and human oversight.
I help projects move forward by simplifying complexity, respecting constraints, and keeping accountability explicit.

Based in the Apennine hills near Bologna.
Continuously learning, building, and refining systems.
still curious?
My Tools

LANGUAGES: 

Python · R · SQL

FAVORITE LIBRARIES:

Pandas · Matplotlib · Seaborn · Folium · Scikit-learn

BI & WORKFLOW: 

Excel · Tableau · Looker Studio · BigQuery · Google Sheets

AI:

Prompt Engineering · APIs · Predictive Modelling · Compliance

Gallery
Lexie – GDPR & AI Act Compliance Copilot
Lexie analyzes policy documents (PDF) or free text and compares them to key articles in the GDPR and EU AI Act. It returns a downloadable human-readable PDF report with risk score, violations, citations, and recommendations.
AI Multi-Product PDF Generator – Bilingual Product Sheet Automation. It combines Generative AI (text), image integration, and layout with ReportLab.
An AI-powered compliance agent that evaluates meeting content against organizational policies.
The Hidden Cost of Unresolved Issues – Google Fiber Repeat Call Analysis
Traffic Volumes: Hours of the Day – Minnesota DOT
Agent Meme – Because crafting a clever LinkedIn comment shouldn’t take longer than reading the post
A ML project to predict whether the Falcon 9 first stage will successfully land after launch
Comparative Data Cleaning (Python & R) – Wine Quality Dataset
Designed for Desire – A Cultural and Data-Driven Journey Through Sex Toy Evolution

AI Policy

I follow a transparent and responsible approach to AI, aligned with ISO/IEC 42001 principles.
My work integrates risk assessment, human-in-the-loop design, and traceability by default.
Responsible AI is not a constraint. It is a cultural choice that enables trust and long-term value.

go to projects
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