Freelancer profile translated to English.
Back to original languageAbout Moad
I am Hadmen Moad, a graduate of Paris 1 Panthéon-Sorbonne University in econometrics and statistics.
Passionate about data and quantitative analysis, I have had the opportunity to work on several concrete projects:
• Machine learning project in collaboration with Edinburgh Airport, aiming to improve passenger traffic prediction.
• Data visualization project carried out for Carrefour, focusing on the analysis and enhancement of sales data to optimize decision-making.
Today, I offer my services in data analysis, statistical modeling, and visualization, with a rigorous and results-oriented approach.
French
Native or bilingual
English
Fluent
Can work on-site
Paris (up to 50km)
Experience
- RENAULTData ArchitectApril 2026 - Today (4 months)• Design of a bronze/silver/gold medallion architecture to ingest and structure 2,700 vehicle test reports to reconcile physical and simulation test data.• Definition and prototyping of a business data model in JSON Schema to standardize the representation of procedures, test cases, scenarios, results, and execution data.• Development of a data model-driven application POC with FastAPI and Streamlit, integrating schema validation, business workflow, results input, and test data structuring.• Detection of heterogeneities between tests using cosine similarity on file signatures, with interactive treemap visualization to explore the hierarchy of unstructured SharePoint.• Implementation of a reconciliation pipeline to recreate links between a test repository and associated raw data files (CSV, PDF, HTML, photos). Semantic matching is performed via Gemini 2.5 Pro on Vertex AI, with structured JSON output, confidence score, and justification per file.• Stack: Python (pandas, BeautifulSoup, Pydantic, asyncio, RapidFuzz, scikit-learn, FastAPI), GCP (Vertex AI, GCS, Workbench, BigQuery), Microsoft (Copilot Studio, Power Automate), GitLab, Git.
- CARREFOURData AnalystAugust 2025 - February 2026 (6 months)Design of ELT workflows on BigQuery and Cloud Functions to ensure supply chain data reliability.• Development of SQL models and Looker Studio dashboards for stock monitoring and S&OP decision support.• Integration of Python scripts and Google Sheets APIs to automate data collection and updates.• Stack: BigQuery, Cloud Functions, SQL, Python, Looker Studio, Google Sheets API
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