Grégoire MUREAU

Architected, developed, and deployed from scratch a production-ready, mobile traceability application for a client in the agri-food distribution sector. Engagement renewed for v2 (from May 2026). 🛠️ Core Achievements: • Traceability app: stock, conditioning, and shipping workflows (AppSheet, Google Apps Script / JavaScript); IFS compliance; dynamic PDF generation; user training. • Data architecture: 15-table relational database + Python migration pipelines from legacy Excel. • Full project lifecycle: requirements → delivery → iterative v2 with operations. 📱 Estimaciones PWA (parallel product): • React 18, Vite, Tailwind, React Router — estimated vs actual grids, dashboards, installable PWA • Wired to Google Sheets (Service Account) for business data • Demo (anonymized portfolio): https://greg-madman-nas.duckdns.org/estimaciones_demo/ 🧰 Stack: React, PWA, Google Sheets, JavaScript, Google Apps Script, AppSheet, Python, SQL ⚡ Daily agentic IDEs (Cursor, Devin)

Large-scale oceanographic data management for the Copernicus Marine Service (European program). 🎯 Responsibilities: - Architecture and maintenance of distributed ETL pipelines (50M+ observations/day in real-time) - Multi-source quality control automation - Validation of heterogeneous and noisy data - Production of ISO 9001, CF, FAIR compliant datasets - Operational monitoring (Kibana, alerting) - Coordination with European and international centers 📊 Achievements: - Reliable processing of millions of daily observations - Co-author of 2 scientific publications (altimetric data validation) - Collaboration with NOAA, Australia, Korea 🛠️ Technologies: Python • Oracle SQL • Cassandra • NetCDF • Airflow • Kibana • Git Skills developed: Large-scale data engineering, real-time pipelines, data quality, distributed architectures, international standards.

Time series analysis for characterizing plunging wave dynamics in coastal zones (ESITC Caen wave flume). 🎯 Signal Processing & Analysis: - Time series analysis of pressure and mechanical forces on coastal structures - Characterization of shock phenomena induced by trapped air bubbles - Data scaling for coastal engineering applications 📊 Methodology: - Statistical processing of wave data - Spectral analysis and feature extraction - Scientific literature review on plunging wave modeling 🛠️ Technologies: Python, Signal processing, Statistical analysis, Time series analysis Skills: Signal processing, time series analysis, scientific literature review, data scaling, coastal engineering.

Time series analysis for characterizing plunging wave dynamics in coastal zones (ESITC Caen wave flume). 🎯 Signal Processing & Analysis: - Time series analysis of pressure and mechanical forces on coastal structures - Characterization of shock phenomena induced by trapped air bubbles - Data scaling for coastal engineering applications 📊 Methodology: - Statistical processing of wave data - Spectral analysis and feature extraction - Scientific literature review on plunging wave modeling 🛠️ Technologies: Python, Signal processing, Statistical analysis, Time series analysis Skills: Signal processing, time series analysis, scientific literature review, data scaling, coastal engineering.

International project (Iceland collaboration): shoreline evolution monitoring and extreme sea level analysis on Sandvik beach (1957-2018). 🗺️ GIS, Photogrammetry & Remote Sensing: - Multi-date aerial imagery processing (1957-2018) - Historical aerial photograph orthorectification - Orthomosaic generation via photogrammetry (drone surveys) - Spatio-temporal shoreline monitoring (diachronic analysis) 📊 Modeling & Validation: - Historical extreme sea level computation from models (ERA5, FES2012) - Cross-validation model/in-situ - Correlation analysis between shoreline movements and extreme levels 🛠️ Technologies: ArcMap, QGIS, Agisoft Metashape, Python, image processing, oceanographic models (ERA5, FES2012) Skills: GIS, photogrammetry, remote sensing, multi-temporal image processing, ocean modeling, data validation, international collaboration.

Validation of satellite data from the Franco-Chinese CFOSAT mission (ocean waves) through cross-analysis of in-situ data and numerical models. 🛰️ Multi-source Validation: - Cross-study of in-situ data (Copernicus Marine), model (WaveWatch III hindcast), and satellite observations (CFOSAT) - Coherence analysis and bias identification - Quality assessment of satellite products 📊 Methodology: - Multi-source data extraction and harmonization - Comparative statistical analysis (in-situ vs model vs satellite) - Scientific validation of operational products 🛠️ Technologies: Python, NetCDF, WaveWatch III, satellite data processing, statistical analysis Skills: Data validation, multi-source processing, remote sensing, ocean modeling, comparative analysis, oceanographic data processing.

Mathematics teaching in middle school (grades 6-9, ~150 students/year) alongside bachelor's degree in mathematics. 🎓 Pedagogy & Communication: - Course design and delivery adapted to different levels - Simplification of complex mathematical concepts for diverse audiences - Individual student mentoring and support - Pedagogical adaptation according to learning profiles 📊 Results: - ~300 students mentored over 2 years - Development of scientific communication skills - Classroom management and group facilitation 🛠️ Skills Developed: Pedagogy, simplification of complex concepts, multi-level communication, educational project management, audience adaptation Transferable Skills: Technical communication, training, presenting ML/Data concepts to non-experts, stakeholder management.