À propos de Imad
Français
Bilingue ou natif
Anglais
Capacité professionnelle complète
Arabe
Bilingue ou natif
Expériences
- AccorSenior ML Engineer / Data Scientist (Consultant)HÔTELLERIEjuillet 2025 - Aujourd'hui (11 mois)Issy-les-Moulineaux, France
- Contributing to an internal GenAI platform (knowledge base management, access control, evaluation frameworks).
- Leading GenAI & RAG projects in production (LLMs, embeddings, retrieval, answer quality evaluation).
- Designed and deployed a customer churn prediction model in production for hospitality retention use cases.
- Built end-to-end ML pipelines: data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.
- Implemented model performance monitoring (data drift, seasonality effects) and continuous improvement loops.
- Working closely with product, data, and business teams to turn ML outputs into actionable decisions.
- LittleBigCodeData Scientist ConsultantCONSEIL & AUDITjuin 2023 - Aujourd'hui (3 ans)Paris, France
- Designing and deploying production-grade ML and GenAI systems from data ingestion to monitoring.
- Building RAG & LLM systems: embeddings, retrieval strategies, evaluation pipelines, and knowledge access governance.
- Applied R&D on large-scale audio & speech data (STT pipelines with Whisper, detailed error analysis on noisy and heterogeneous audio).
- Designing evaluation frameworks for embeddings, retrieval systems, and LLM-based applications in production.
- Collaborating with product, data, and business teams to align AI systems with real-world use cases.
- Documenting and presenting results to both technical and non-technical stakeholders.
- AtosConsultant Data ScientistCONSEIL & AUDITseptembre 2021 - juin 2023 (1 an et 9 mois)Bezons, France
- Developed deep learning models for audio and video content analysis in production environments.
- Worked on speech processing, audio event detection, and multi-label content classification.
- Fine-tuned NLP and speech models for automatic content summarization and metadata enrichment.
- Contributed to the transition from research prototypes to industrialized ML systems with engineering teams.
- Prototyped ML/NLP models and contributed to data processing pipelines.
- Participated in applied research projects across vision, audio, and NLP tasks.
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Formations
- Generation (RAG)Generation (RAG)
- Large Language Models (LLM)Large Language Models (LLM)