Freelancer profile translated to English.
Back to original languageAbout Hedi
I am a consultant specializing inDataandArtificial Intelligence**, with particular **expertisein the design anddeployment of generative AI solutions**. I work on the **entire**project lifecycle**, from scoping to production, using agile methodologies (**Scrum**) and technologies such asMachine Learning**, **LLMs**, **RAG systems**, and **Deep Learning**. Passionate about **applied**mathematics** and **statistical models**, I have a strong appetite for advanced data analysis and the creation of AI solutions with high business value.
English
Native or bilingual
French
Native or bilingual
Can work on-site
Paris (up to 50km)
Experience
- TalanData Engineer / DeveloperCONSULTING AND AUDITSMarch 2025 - October 2025 (7 months)Paris, FranceAs part of a strategic internal project at Talan, I led and executed from end-to-end an intelligent staffing chatbot capable of identifying the most relevant consultants for a given mission offer. I implemented a RAG (Retrieval Augmented Generation) engine deployed on Microsoft Teams, connected to a vector index hosted on Azure.
- Designed a completeCV processing pipeline**: **ingestion**, **cleaning**, format **harmonization**, automated **metadata extraction(availability date, grade, current mission, etc.).
- Deployed astorage architectureon **Azure Data Lake**, with software structuring of files (original CVs, anonymized CVs, mappings, dynamic statuses, etc.).
*CV vectorizationusing OpenAI embeddings (text-embedding-3-large) and creation of an enriched FAISS index.- Implemented aRAG(Retrieval Augmented Generation) search engine withavailabilityfiltering, **vector similarity**, **contextual sorting**, and **custom scoring**.
- Implemented anintent classification agentfor targeted questions about selected consultants (**experience**, **availability**, **mission fit**).
*Deployedthe chatbot onMicrosoft TeamsviaAzure Bot Service(application registration, channels, secrets configuration). - AXAGen AI Developer / Front EndJune 2024 - February 2025 (8 months)Paris, FranceWithin the AMMRAG project (Agent Multi Modal RAG), the objective was to create achatbotspecialized in a domain (**Insurance**) capable of answering questions precisely and without error on various document types (**complex tabular data**, **Word**, **PDF**, **scanned PDF**, **images**, **PPT**).Development and improvement of FAISS (Vector Store)
- Enriched FAISS by indexing new documents to improve information retrieval.
- Processed and ingested various document formats (PDF, Excel, OCR, Word).
- Implemented an automated FAISS update process, ensuring efficient indexing of new data.
Automation of tests to validate response relevance- Developed a test automation script to evaluate the quality of the model's responses.
- Compared generated responses with expected answers, facilitating the evaluation of RAG result relevance.
- Integrated a scoring mechanism and analysis of RAG response performance.
Development of a graphical interface for consultation and interaction- Designed and developed a graphical interface allowing users to test and interact with the model.
- Integrated several features: document type selection, button to display documents used for the last RAG response, button to download conversation history.
- Implemented a fluid and intuitive user experience to simplify access to documents and their content.
- NestleData Sciences / ML/MLOpsJanuary 2024 - March 2024 (2 months)Paris, FranceAs part of a collaboration withNestléin 2023, the project aimed to improve and supportMachine Learning pipelinesviaAzure Machine Learning**. The objective was to **optimizetheprocessesof datapreprocessingand **model training**, while ensuring better monitoring and maintenance of deployed solutions.Optimization and monitoring of Machine Learning pipelines
- Developed detaileduser storiesto define **user needs**, thus facilitating feature prioritization and alignment with Nestlé's strategic objectives.
- Participated inPoker Sessionswith the team to estimate task complexity and refine priorities, ensuring efficientbacklogmanagement and timely delivery.
- Implementedmonitoring strategiestotrackmodelperformancein production and ensure **proactive maintenance**.
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Education
- Master in Data Sciences & Business AnalyticsCentrale Supélec X ESSEC BUSINESS SCHOOLMaster en Data Sciences & Business Analytics
- Bachelor in Political EconomyHEC LausanneBachelor en Economie Politique