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Now at Afterdata · Paris
Data Scientist & AI Architect
ML models and LLM agents built for real business decisions, from raw data to production.
I'm Enzo. I turn messy business problems into machine learning models, LLM agents and data products that people actually use.
Data scientist trained at Albert School × Mines Paris–PSL, now AI Architect at Afterdata. I like the whole path: understanding the business question, getting the data right, building the model, and shipping something a team can use on Monday.
From a joint MSc to real client missions and an AI architect role. Keep scrolling.
A joint programme mixing engineering and business: ML, deep learning, NLP and data engineering, applied every term to real company cases.
Short, intense consulting sprints on company problems: incident prediction, SLA modelling, maritime route optimisation, assortment and media-budget allocation.
Automation and data tooling for the operations team: Power Automate flows, Copilot Studio agents, Streamlit and Power BI apps.
Next chapter: designing AI systems end to end, from LLM agents and RAG pipelines to their deployment for clients.
From a messy dataset to a model in production, and the dashboard that explains it.
Predictive models built for a decision, not just a score: feature engineering, model selection and evaluation, then recommendations people can act on.
Assistants that answer from your own documents and data: retrieval pipelines, agent design, prompt and evaluation work, and integration into existing tools.
Clean, reliable pipelines and audits of the data you already have, so the analysis and the models downstream can be trusted.
Dashboards and small web apps that put the numbers in front of the people who decide, from KPI tracking to full Flask applications.