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Mathieu CarmassiMC

Mathieu Carmassi

Data Lead | GCP • dbt • Anaplan Data Integration

€950/day
Saint-Genis-Pouilly, FR
8-15 years
Analytics Engineer
DBT
Google Cloud Platform (GCP)
LookML
Machine Learning Algorithms

Average response time: 1 hour

Freelancer profile translated to English.
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About Mathieu

Expert in the end-to-end Data value chain, I combine strategic vision with technical excellence. From designing Machine Learning models (Forecasting) to architecting global datamarts on GCP, I support organizations in creating reliable, scalable, and business-centric data products.

Why work with me?
  • Luxury/Retail Business Expertise: Deep understanding of business challenges (Sales, Planning, Stock) gained at Cartier.
  • Modern Data Stack & ML Ops: Advanced proficiency in GCP, dbt, BigQuery, and deployment of industrialized models (CI/CD, GitLab, Cloud Functions).
  • Performance Management (EPM): Expert in interfacing with Anaplan to transform data into budget simulation tools.
  • Data Mesh & Governance: Ability to orchestrate multi-source and multi-region environments (Looker/LookML).

  • French

    Native or bilingual

  • English

    Fluent

  • Spanish

    Conversational

Can work on-site
Saint-Genis-Pouilly (up to 50km), Paris (up to 50km), Annecy (up to 50km)

Experience

  • CARTIER
    Data Scientist
    LUXURY GOODS
    November 2019 - April 2022 (2 years and 5 months)
    Meyrin, Switzerland
    **Missions**: Industrialization of Machine Learning for sales forecasting.


    • Advanced Forecasting: Design of multivariate models for short-term (daily/market) and long-term (monthly/region) forecasts.
    • MLOps & Cloud: Deployment of automated pipelines (CI/CD GitLab, Docker, GCP Cloud Functions, Pub/Sub).
    • Data Warehouse: Construction of the BigQuery warehouse, integrating and cleaning heterogeneous sources for business.
    • Tools: Python, BigQuery, Looker, Anaplan.
    BigQuery Python Machine Learning Algorithms Looker Gitlab CI/CD
  • CARTIER
    Manager Data Commercial & Analytics
    LUXURY GOODS
    May 2022 - Today (4 years and 1 month)
    Meyrin, Switzerland
    **Missions**: Architecture and management of the global commercial data engine (GCP/dbt).


    • Scalable Architecture: Design and maintenance of the Commercial Datamart on GCP, ensuring a "Single Source of Truth" for all regions.
    • Analytics Engineering: Standardization of transformations via dbt, ensuring reliability and traceability of commercial KPIs.
    • Technical Leadership: Management of a Senior Analytics Engineer and evangelization of the Data Mesh culture to markets.
    • Strategic Management: Development of the Looker semantic layer (LookML) and complex interfacing with Anaplan for global budget planning.
    • Impact: Creation of the Retail performance dashboard for Sales Associates (global deployment).
    Google Cloud Platform (GCP) Analytics Engineer DBT LookML Data Strategy & Lead Management
  • EDF R&D
    Data Scientist (R&D)
    ENERGY AND UTILITIES
    November 2018 - November 2019 (1 year)
    Paris, France
    **Missions**: Predictive analysis and customer behavior modeling.


    • Statistical Modeling: Implementation of statistical learning models (XGBoost, neural networks, GLMnet) on massive consumption data.
    • Decision Support Tools: Development of interactive applications (Shiny) for visualizing load behaviors and aiding decision-making.
    • Technical Stack: R (Tidyverse), Python (Numpy, Scikit-learn).
    R Python R Shiny Machine Learning Algorithms SQL

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Education

  • Ph.D. - Applied Mathematics
    Université Paris Saclay
    2018
    Quantification d’incertitudes et Modélisation Prédictive Recherche doctorale axée sur la fiabilisation des modèles de performance (appliquée à l'énergie photovoltaïque). Ma thèse portait sur l'identification des incertitudes et la validation de modèles complexes pour garantir des estimations de production long terme robustes." Pourquoi c'est un atout pour vos projets Data : Rigueur Scientifique : Capacité à auditer la qualité des données et la précision des algorithmes (Forecasting, ML). Fiabilité des Résultats : Expertise dans la transition entre "modèles théoriques" et "prévisions terrain" (réduction de l'erreur). Maîtrise Mathématique : Une base solide pour résoudre des problématiques d'optimisation complexes (stock, ventes, supply chain).
  • Advanced Mechanical Engineering Degree
    SIGMA - Clermont
    2015
    Fiabilité, Stochastique & Optimisation des Structures Formation d'ingénieur centrée sur la modélisation de phénomènes complexes et la fiabilité des systèmes. Expertise approfondie en calculs probabilistes, analyses de sensibilité et problèmes stochastiques appliqués à l'optimisation.

Skill set

BigQuery
SQL
Python
R

Categories