À propos de Briac
👨💼 Hello, I'm a passionate and rigorous data scientist specializing in artificial intelligence, data analysis, and statistics.
🤝 With 5 years of experience, I support companies in their data projects, from exploratory analysis to ML model deployment in production. My added value: an end-to-end vision covering the entire data project lifecycle.
I have led projects ranging from supply chain cost reduction, yield prediction and automation in the cloud.
🎯 Recent achievements:
Developed NLP pipelines and LLM-based classification in production.
Implemented Brand Safety models (text, image, audio) in a SaaS with Automatic Speech Recognition
Reduced losses by 30% through predictive modeling in agriculture
Deployed cloud solutions (AWS, Gitlab) with CI/CD pipelines
💡 Technical expertise:
AI & ML: NLP, LLM (OpenAI API), RAG, Deep Learning, Time Series
Languages: Python, SQL, R
Tools: HuggingFace, TensorFlow, PostgreSQL, ElasticSearch
Français
Bilingue ou natif
Anglais
Capacité professionnelle complète
Néerlandais
Capacité professionnelle limitée
Accepte de travailler sur site
Bruxelles (jusqu’à 30 km)
Expériences
- StellarData Scientist LeadRÉSEAUX SOCIAUXseptembre 2025 - Aujourd'hui (9 mois)Bruxelles, BelgiqueObjective: Develop models to analyse the BrandSafety of text, image and video in a SaaS.
- Benchmarked & optimized inference pipelines (CPU/GPU)
- Deployed LLM-based classifiers for brand safety detection
- Deployed ASR pipeline (Whisper/HuggingFace, VAD, STT)
- Computer vision, brand recognition with YOLO.
- Transformer, VLM, matching-algorithm, embeddings...
- Ensured model compliance with GDPR & EU AI Act (bias, explainability)
Result: Deployed script in gitlab (K8s). Provide overview of AI models with testing.Tools: Python, Gitlab, OpenAI, RabbitMQ, HuggingFace, Kubernetes, Docker, ElasticSearch - Bayer Crop ScienceData Scientist AnalystLOGISTIQUE & SUPPLY CHAINseptembre 2023 - février 2025 (1 an et 5 mois)Rennes, FranceObjective: Reduce seed production costs at European sitesActions:
- Developed NLP pipeline to extract hybrid seed information from PDF reports and structure it for analysis.
- Implemented LLM-based classification to detect and label field inspection issues from free-text reports.
- Analyzed the impact of input variables (weather, SAP data, agricultural practices, harvest cycles) on production efficiency.
Result: Improved process transparency and decision-making, leading to 300 workdays saved for agricultural engineering teams. - CooperlDevelopment engineerAGROALIMENTAIREmars 2025 - mai 2025 (2 mois)Rennes, FranceObjective: Convert an R script into python about spiruline productionAction: Developed deep learning model to improve production processResult: Python script to optimize spiruline production.
Recommandations
Soyez le premier à recommander Briac
Contribuez à la réussite de ce freelance en partageant votre expérience de collaboration avec lui.
Ces profils de freelance correspondent également à vos critères
Agatha Frydrych
Backend Java Software Engineer
4.7
(3)
2
Baptiste Duhen
Fullstack developer
4.6
(4)
5
Amed Hamou
Senior Lead Developer
4
(2)
7
Audrey Champion
Web developer
4.3
(3)
4
Formations
- Erasmus ExchangeWarsaw University of Technology2018Modelisation, Environmental
- Engineering DiplomaIMT Mines Alès2019mathematics, physics, programmation
Certifications
- The Data Science Course Complete Data Science BootcampUdemy2020