// Arthur Morvan profile data — derived from the live portfolio.
// Edit values here; both concepts read from this single source.

const PROFILE = {
  name: "Arthur Morvan",
  handle: "arthur",
  host: "morvan",
  location: "Paris / Milano",
  about: {
    title: "Engineer, researcher, builder.",
    description:
      "AIDAMS @ CentraleSupélec · ESSEC · Paris-Saclay (GPA 4.0). Currently on exchange at Bocconi. I build things at the intersection of data, ML, and product from generative AI research at Thales to data science for KLESIA.",
    quote: "First, solve the problem. Then, write the code.",
    quoteAuthor: "John Johnson",
  },
  skills: {
    languages: ["Python", "JavaScript", "SQL", "VBA", "Bash"],
    frameworks: ["PyTorch", "TensorFlow", "React", "FastAPI", "Spark", "Next.js"],
    databases: ["PostgreSQL", "MongoDB", "Redis", "Neo4j", "Supabase"],
    tools: ["Docker", "Kubernetes", "GCP", "AWS", "Git", "Linux"],
  },
  experiences: [
    { company: "Bocconi University",    position: "Research Assistant",       period: "March 2026 — present",  note: "Comparative analysis of institutional equity forecasting models using Python and MongoDB." },
    { company: "KLESIA Insurance",      position: "Data Scientist",           period: "May 2025 — Aug 2025",   note: "Built interactive dashboards for EUR 450M yearly transactions and automated data workflows on Azure/Databricks." },
    { company: "ESSEC Business School", position: "Database Administrator",   period: "Oct 2024 — present",    note: "Maintains and improves Salesforce data quality while automating collection via APIs and scraping pipelines." },
    { company: "THALES",                position: "Generative AI Researcher", period: "June 2024 — Aug 2024",  note: "Automated annotation/classification workflows and designed proprietary datasets and metrics for M-LLM evaluation." },
  ],
  projects: [
    {name: "equity models research", subtitle: "Research Project", tech: ["Python", "Supabase", "Transformers", "OpenAI"], description: "Comparative analysis of institutional equity forecasting models using a complete pipeline for complex and detailed financial documents analysis.", link: "https://github.com/ArthurrMrv/research_ocr_pipeline.git" },
    { name: "stock-sentiment-graph",       subtitle: "School Project",    tech: ["Python", "FastAPI", "Neo4j", "Hugging Face", "Docker", "CI/CD"], description: "Architected a multi-model Neo4j sentiment API with an interactive stock-news graph and 92% test coverage.",                                      link: "https://github.com/ArthurrMrv/graph_project" },
    { name: "financial-nlp-distillation",  subtitle: "Personal Project",  tech: ["Python", "Hugging Face", "FastAPI", "Docker"],                   description: "Fine-tuned DeBERTa-v3 for financial sentiment and distilled it into a lighter model deployed on Hugging Face.",                            link: "https://github.com/ArthurrMrv/nlp_final" },
    { name: "data-engineering-pipeline",         subtitle: "Professional Project",  tech: ["Python", "Pandas", "Spark", "Databricks"], description: "Built a data engineering pipeline to automate the processing and analysis of financial data of more than 100,000 clients." },
    { name: "random-forest-from-scratch",  subtitle: "Personal Project",  tech: ["Python", "Jupyter Notebook", "NumPy"],                           description: "Implemented a Random Forest classifier from first principles and optimized hyperparameters with a genetic algorithm.",                       link: "https://github.com/ArthurrMrv/RandomForestFromScratch" },
  ],
  resume: {
    url: "public/Arthur_Morvan_CV.pdf",
    lastUpdated: "April 2026",
    headline: "AIDAMS (CentraleSupélec · ESSEC · Paris-Saclay), GPA 4.0/4.0 · Bocconi exchange 2026",
  },
  contact: {
    email: "arthur.morvan6@gmail.com",
    linkedin: "https://linkedin.com/in/arthur-morvan",
    github: "https://github.com/ArthurrMrv",
    website: "https://arthurmorvan.com",
    calendar: "https://calendar.app.google/R9s9yTyqPMX8yvvRA",
  },
};

window.PROFILE = PROFILE;