AI
Daniele Raimondi
AI Twin • Ask me anything!
Senior Data Scientist Basel
Turning data into intelligence.
A decade of Data Science and AI: scientific depth meets quantitative rigor.
On stage at PyData London 2026
About
Senior Data Scientist
Daniele Raimondi is a Senior Data Scientist and AI leader with 10 years taking Data Science, AI, LLM and GenAI systems from prototype to production. Tech Lead of cross-functional teams and international speaker, from PyData London to the Italian Parliament. Deep expertise in Data Science, AI systems, and quantitative finance. Former Italian National Team athlete with a high-performance mindset.
Ten years of Data Science and AI, in production
From international AI stages to the Italian national track team: the moments that define the journey.
Presenting an AI platform for public-policy decisions at the Italian Parliament.
On the panel in the Parliament's press room, speaking on AI for research and innovation.
4x400m relay with the Italian senior national team at a premier Diamond League event.
On stage with LLM pipelines at scale, for one of Europe's leading data communities.
Building a 110,000-concept scientific taxonomy with graph clustering, embeddings, and LLMs.
Automating paper classification at scale with retrieval, reranking, and LLM validation.
Read the MATCH paper →
Applied AI systems and impact-driven experimentation.
Tracking rejected manuscripts with Qdrant and Specter2, presented to the scientific Python community.
Data science models for Bitcoin and decision support.
AI initiatives and publishing innovation, presented in the United States.
AI strategy and scalable data-driven processes for editorial operations.
The azzurri lineup in Rome, and the same discipline I bring to AI delivery today.
Applied AI and real-world data science impact, presented to the Swiss data community.
Professional track record in descending chronological order.
Tech Lead for Data Intelligence Team: owning roadmap and delivery of ML and LLM products, including multimillion-record semantic tagging, ontology-based graph clustering, and production pipelines with Azure OpenAI, Qdrant, and Prefect.
Led data science across a multi-billion-euro retail operation: delivered 3% revenue and margin uplift, reduced churn by 20% on 6M+ customers, improved CLV by 15%, and automated workflows with 90%+ time savings.
Delivered quantitative consulting for banking clients using SPSS, SAS, and Python across finance and risk transformation projects.
Built statistical models for credit risk and scoring, including Machine Learning, Value at Risk, Expected Loss, Loss Given Default, and Exposure at Default.
Quantitative training spanning statistics, economics, finance, and modern data science.
2021 · Advanced ML, NLP, and data products
2017 · Financial Markets, Insurance, and risk analytics
2014 · Statistical modeling and econometrics
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