Leclercq Nathan
nathan.leclercq9@protonmail.com
Profile
Master’s student in Machine Learning, currently working as an apprentice at DataKhi, where I specialize in predictive modeling, ML solution deployment, and MLOps architecture. I am focused on the design and deployment of end-to-end artificial intelligence solutions. Combining a dual background in mathematics and computer science with practical experience in Data Science and data engineering, I am currently developing a complete MLOps platform via my homelab. Currently pursuing a Master’s in Machine Learning, I am seeking a position that combines distributed systems architecture and innovative ML solutions deployment.
Professional Experience
Data Scientist (Apprenticeship)
Hall U Need (via DataKhi), Tourcoing
2023 - present
- Footfall and sales prediction by product type:
- Development of predictive models based on time series
- Algorithm optimization to reduce error margin
- 90% error coverage achieved
- Adapted to different volumetric types and recurrence patterns
- Fine-tuning of embedding models (CamemBERT) on textile data
- Overfitting resilience and visualization creation for business teams
- Weather data collection and extrapolation
- Use of autoML libraries for model comparison and selection
- Technical stack: Python, Scikit-learn, Polars
Data Engineer & ML Engineer (Apprenticeship)
Tossée Project (via DataKhi), Tourcoing
2023 - present
- Development of an application displaying environmental scores for textile products:
- Design of a Python web scraping solution
- Hybrid automation and deployment on local servers and Azure
- Automatic normalization flows with NLP techniques
- Fine-tuning of embedding models (CamemBERT) on textile data
- Infrastructure and databases:
- Design and optimization of databases (Graph, MongoDB, PostgreSQL with pgvector)
- Development and optimization of FastAPI (response time < 1 second)
- Design and maintenance of front-end applications (OCR)
- Technical stack: Python, JavaScript, Flutter, Azure (Synapse, DevOps, Data Lake), Ansible, Kubernetes, SQL, MongoDB, GraphQL
FullStack Developer (Internship)
Internal Mission Datakhi, Tourcoing
2023 (4 months)
- Architecture and development of a versioning system for PowerBI:
- Design of a high-performance C++ backend managing report differentials
- Development of a React frontend with graph-based visualization
- Distribution via Electron for cross-platform compatibility
- Technical stack: C++, React, Electron, Git
Music Teacher
Music Schools, Apprentus
2017 - present
- Teaching saxophone and music theory
- Development of personalized teaching materials
Technical Skills
Data Science & ML
- Predictive modeling: Scikit-learn, PyTorch, TensorFlow
- MLOps: MLflow, Weights & Biases
- Data processing: Pandas, Polars
- NLP: Model fine-tuning (CamemBERT), embedding techniques
- Big Data: Spark
Infrastructure & DevOps
- Cloud: Azure (Synapse, DevOps, Data Lake, Functions)
- Infrastructure as Code: Ansible, Terraform
- Containerization: Docker, Kubernetes
- Monitoring: Prometheus, Grafana
- Linux: System administration, shell scripting
Databases
- Relational: PostgreSQL (with pgvector)
- NoSQL: MongoDB, Redis
- Graph Oriented Database
- Querying: SQL, GraphQL
Development
- Backend: Python (FastAPI), Node.js, Go, Haskell
- Frontend: React, TypeScript, Vue.js, Flutter
- System languages: C++, Rust
- Scientific languages: Julia, R
Education
Master’s in Machine Learning
University of Lille
2023 - 2025
- Specialization: Deep Learning, NLP, MLOps
- Major projects:
- Deployment of LLMs on GPU infrastructure
- Optimization of recommendation systems
Bachelor’s in Computer Science
University of Lille
2020 - 2023
- Advanced algorithms
- Distributed architecture
- Full-stack development
Mathematics Education
University of Lille
2017 - 2020
- Solid foundations in numerical analysis
- Fundamentals of probability and statistics
- Applied linear algebra
Significant Projects
MLOps Homelab Platform
Since 2024
- Complete infrastructure with GPU servers for ML/DL
- Deployment and training of agents with crewAI based on RAG
- Automated deployment of ML services (LLMs, recommendation systems)
- Monitoring and observability via Prometheus/Grafana
Book Recommendation System
September 2023 - January 2025
- Scraping and preprocessing pipeline (>100k books)
- NLP and vector database-based recommendation API
- Vue.js user interface with visualizations
- Metrics collection and model versioning with MLflow
Algorithms Club Leader
Since 2024
- Organization of programming competition preparation sessions
- Implementation of optimized solutions in Julia
- Competition participation: Google Hash Code, Reply Code Challenge, Cloudflight Coding Contest
Cross-functional Skills
- Technical curiosity: Continuous technology watch
- Rigor and documentation: Methodical approach to projects
- Autonomy: Ability to lead end-to-end projects
- Analytical mindset: Complex problem solving
- Teamwork: Effective collaboration in agile environments
Languages
- French: Native
- English: Professional (TOEIC 885/B2)
Interests
- Music: Saxophone (jazz, soul), orchestra participation
- Sports: Daily cycling, badminton
- Reading: Science fiction, technical essays
- Tabletop role-playing games