Franck Sirguey

Data Scientist @Amundi

Paris, FR
MOBILE NUMBERS
+91 *********19

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WORK HISTORY

Sep 2025 — Present

Data Scientist @Amundi

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Paris, FR

Designed two LangChain + OpenAI pipelines transforming Teams transcripts into (1) structured investmentbullet points and (2) factual meeting reports (standardized outputs, easier review process).• Industrialized Python pipelines for recurring fund production tasks (performance, sector allocation, attribution):improved reliability and reduced manual work.• Developed a News Intelligence tool for monitoring portfolio companies: data collection (web scraping + TradingViewAPI), Azure orchestration, multi-agent architecture, LLM-based generation/summarization, Streamlit interface.• Built Superset dashboards consolidating fund KPIs and reporting views for internal teams.• Data point of contact for the team: maintenance of pipelines and migration data from Excel to Python.

EDUCATION

2022

Faculté des Sciences et Techniques - Université Jean Monnet Saint-Etienne

Licence, Informatique

N/A

Paris ESLSCA Business School

MBA 2, Trading & Finance de marché

N/A

Faculté des Sciences et Techniques - Université Jean Monnet Saint-Etienne

Master International , Machine Learning Data Mining

ABOUT FRANCK SIRGUEY

I\'m a Junior Data Scientist with a strong academic background in machine learning, NLP, and applied AI. I hold a Master’s degree in Machine Learning & Data Mining and am currently completing a front-office apprenticeship at Amundi (CPR Asset Management), where I develop LLM-powered automation tools to support Investment Specialists in fund reporting and meeting summarization.Previously, I built a full Retrieval-Augmented Generation (RAG) system at Banque de France during my internship, using LangChain and LLMs to support financial education through document-grounded answer generation.My main interests lie at the intersection of AI systems (multi-agent architectures, RAG, recommendation) and real-world financial applications. I\'m passionate about building tools that are not just technically elegant, but also useful, explainable, and production-ready.

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Franck Sirguey — Data Scientist at Amundi in Paris, FR | Unifers