R&D Engineer / Data Scientist
Luxembourg
- Architected a graph database infrastructure enabling automated integration of heterogeneous data and facilitated the implementation of an automotive parts catalog for non-standard and semi-assigned parts- Developed and deployed an expert system orchestrating multiple machine learning algorithms based on input data, resulting in annual cost savings of 30% in data purchasing- Design and implementation of VinX, an innovative machine learning algorithm enabling the prediction of new information such as origin references of car parts, reducing reliance on expensive web services from car manufacturers and other suppliers- Implementation of various machine learning models across automotive datasets from multiple European countries (France, Italy, Spain, etc.)- Utilized the D3.js library to visually communicate complex data insights to stakeholders, facilitating understanding and decision-making processes- Engineered a dynamic route optimization tool for the transportation sector, enabling the calculation of dynamically optimized delivery routes for the distribution of car partsUsed technologies:- Python (tensorflow, keras, numpy, matplotlib, scikit-learn, pandas, seaborn, poetry, pyenv, xblack, flake8, etc.), GO (Golang), Vostok Golang Framework (homemade, open source)- MySql, NoSQL (Neo4j, Cypher),- Talend, GitLab, CI/CD
