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Ismail Ait-LahssenIA

Ismail Ait-Lahssen

Data & ML Pipeline Engineer

EUR 650/Tag
Paris, FR
3-7 Jahre

Durchschnittliche Reaktionszeit: 1h

Über Ismail

I help companies transform raw and messy data into clean, structured datasets and build machine learning pipelines for prediction and decision-making.

I specialize in tabular data (customer data, financial data, operational data) and deliver end-to-end solutions: data cleaning, feature engineering, model building, and deployment on AWS.

My goal is simple: turn your data into something usable and valuable as quickly as possible.
  • Französisch

    Muttersprachlich oder zweisprachig

  • Englisch

    Muttersprachlich oder zweisprachig

Vor Ort möglich
Paris (bis zu 50 km)

Projekt- und Berufserfahrung

  • Themison
    Machine Learning Engineer – Clinical Data
    MEDIZIN
    Juli 2024 - Heute (1 Jahr und 11 Monate)
    Copenhagen, Denmark
    Prepared and processed clinical and behavioral datasets for predictive modeling in clinical trials.

    Built patient risk segmentation models using K-Means, GMM, and DBSCAN to identify early dropout patterns.

    Designed and deployed a real-time monitoring system with automated interventions to reduce patient dropout.

    Performed cluster analysis and data visualization, contributing to a 22% reduction in dropout rate.

    Ensured compliance with GDPR and HIPAA standards for sensitive patient data handling.
    Python model evaluation Machine learning Data Cleaning AWS Glue
  • Keyrus
    Data Analyst / Machine Learning Intern – Customer Retention
    PERSONALWESEN
    März 2022 - September 2022 (6 Monate)
    Levallois-Perret, France
    Analyzed business requirements to understand customer retention challenges and existing manual processes.

    Collected and consolidated data from multiple sources to build structured and usable datasets.

    Cleaned and transformed raw data to prepare it for statistical analysis and machine learning models.

    Built and evaluated predictive models including Logistic Regression, Decision Trees, Random Forest, SVM, and K-Means.

    Delivered insights to support customer retention strategies and improve decision-making.
    Machine learning Data transformation Jupyter Programmation Python Team management

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Ausbildung und Abschlüsse

  • INGÉNIEUR EN SYSTÈMES UBIQUITAIRES ET DISTRIBUÉS
    LYCÉE HASSAN II
    2022
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