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Med DhifallahMD

Med Dhifallah

AI System && Data Engineer

400 €/jour
Paris, FR
3-7 ans

Délai de réponse moyen : 1h

À propos de Med

AI System & Data Engineer with experience building intelligent automation systems, NLP applications,
analytics dashboards, and machine learning solutions across enterprise and startup environments.
Skilled in Python, Tableau, LangChain, and full-stack development, with hands-on experience in embedded AI,
LLM-based educational systems, and data-driven problem solving.
Passionate about designing scalable AI solutions that bridge business operations and intelligent systems.
  • Anglais

    Bilingue ou natif

  • Français

    Bilingue ou natif

  • Arabe

    Bilingue ou natif

  • Allemand

    Capacité professionnelle limitée

Accepte de travailler sur site
Paris (jusqu’à 50 km)

Expériences

  • Self-Employed
    AI System & Data Engineer
    AGENCE & SSII
    décembre 2025 - mai 2026 (6 mois)
    Paris, France
    • Developing AI-powered automation and analytics solutions for startups and SMEs, focusing on NLP workflows, intelligent reporting, and data-driven applications.
    • Building LLM-based systems and automation pipelines using Python, LangChain, Pandas, and machine learning frameworks to reduce manual analytical effort by up to 74%.
    Python LLM Langchain Pandas React.js
  • Arval – BNP Paribas
    Data Expert - COO Office
    BANQUE & ASSURANCES
    janvier 2025 - décembre 2025 (11 mois)
    Paris, France
    • • Deployed a Tableau dashboard used by 23 global teams, improving KPI tracking and reporting efficiency for the different Account Team.
    • • Building an Automated EDA assistant with a Thinker–Worker architecture that applies rule-based heuristics for data profiling, cleaning, and fully logged transformations.
    Data visualisation intelligence artificielle SQL Dataiku Python
  • Télécom SudParis (SAMOVAR)
    AI & Embedded Systems Intern
    INTERNET DES OBJETS
    juin 2024 - août 2024 (2 mois)
    Évry, 91000 Évry-Courcouronnes, France
    • • Built a resource-efficient AI prototype on Raspberry Pi and Arduino, enabling real-time embedded inference for a drone project and a line follower.
    • • Improved model latency by deploying TensorFlow Lite + scikit-learn for RL-based tasks in constrained settings while documenting the process and serializing the data.
    intelligence artificielle Python Pytorch Deep Learning Computer Vision

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Formations

  • M2 - Intelligence Artificielle
    Université Paris Dauphine - PSL
    2025
    M2 - Intelligence Artificielle
  • M1 – Computer Science & Networks
    Télécom SudParis
    2024
    M1 – Computer Science & Networks

Compétences

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