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Maxime CoffreMC

Maxime Coffre

Data analyst - SQL Python PowerBI

EUR 250/Tag
Bâle, CH
0-2 Jahre

Durchschnittliche Reaktionszeit: 1h

Über Maxime

Data Analyst with a strong foundation in mathematics and statistics (Agrégation).
I specialize in exploratory data analysis, statistical modelling and transforming complex datasets into actionable insights using Python and SQL.
My background in mathematics (Agrégation) allows me to design rigorous analyses, build statistical models, and interpret results with strong methodological reliability.


Experience working with environmental and biological datasets, including biodiversity data from APIs such as GBIF and GeoFabrik. Through the BioDivMap project, I developed a predictive model to identify potential observation areas of the Eurasian lynx and produced geospatial analyses to support ecological monitoring.
  • Französisch

    Muttersprachlich oder zweisprachig

  • Englisch

    Verhandlungssicher

  • Deutsch

    Konversationssicher

Vor Ort möglich
Bâle (bis zu 30 km), Mulhouse (bis zu 10 km), Colmar (bis zu 10 km), Strasbourg (bis zu 10 km), Fribourg-en-Brisgau (bis zu 10 km)

Projekt- und Berufserfahrung

  • DataForGood
    Developer for EuroforDocs
    VEREINE & GEWERKSCHAFTEN
    Januar 2026 - Heute (5 Monate)
    Integrated new external datasets (RNA registry) to enrich and improve the completeness of the organization database Performed data cleaning, normalization and transformation using Python and SQL Conducted exploratory data analysis (EDA) to identify inconsistencies and improve data quality Collaborated with a multidisciplinary team using Agile/Kanban methodology and GitLab version control.

    Gitlab repository :
    Data analysis Data Quality ETL Python SQL
  • Maxime Coffre
    Data sciencs project: Biodivmap
    UMWELT
    Februar 2026 - März 2026 (1 Monat)
    Huningue, Frankreich
    Design of a complete data pipeline to produce a probability map of lynx presence across Europe.
    Collection and structuring of massive environmental data via Google Earth Engine, geospatial processing with Python (GeoPandas, raster).
    Feature engineering and training of a machine learning model (Logistical regression) to model the presence of a species despite observation biases between countries.
    Development of a spatial decision support tool to identify areas with high observation potential.
    SIG Scikit-learn Feature Engineering Machine learning Python
  • DataBird Paris
    Data Analyst : Biomedical Project
    GESUNDHEIT & WELLNESS
    November 2025 - Dezember 2025 (1 Monat)
    Huningue, Frankreich
    Cleaned and processed a 10,000-row biomedical dataset using Python (Pandas) Performed exploratory analysis to identify factors associated with antibiotic resistance.
    Presented findings through data visualization and statistical summaries.
    Detected 27 relevant correlations between risk factor and bacterial resistance.
    Python Data visualisation Life Sciences Tests statistiques PowerBI

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Ausbildung und Abschlüsse

  • Analyst
    2025
    Analyst
  • Agrégation in
    Université Grenoble Alpes 38
    2019
    Agrégation in

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