Badreddine Chaguer Email & Phone Number

Corbeil-Essonnes, Île-De-France, France

As a Senior Data Scientist, I lead projects, shape strategic direction, and mentor junior team members. Specializing in advanced analytics, I develop and deploy IA models and ensure ethical data practices. With deep domain expertise, I communicate insights effectively, driving innovation and continuous improvement within the organization.

Corbeil-Essonnes, Île-De-France, France

- Development of a chatbot Fine-tuned on over 1,000 PDF documentscontaining references for all company departments (audit, processes, etc.).This chatbot leverages various techniques (semantic vector approach,ElasticSearch, LLAMA2, RAG, etc.) to provide direct and efficient responses touser inquiries.- Development of a predictive maintenance model: Utilized historical sensordata and Deep Learning to forecast the Total Organic Carbon (TOC) factor 12hours into the future, achieving 91% accuracy. This led to a 75% reduction inunexpected downtime.- Creation of a machine abort event classification model: Classified machineabort events during the manufacturing process to determine whether a siliconwafer should be rejected, achieving 97% accuracy. This resulted in a 15%reduction in material waste and a 10% improvement in overall yield.- Development of a defect classification model for silicon wafer images: AppliedConvolutional Neural Networks (CNNs) to create a robust defect classificationmodel with 92% accuracy, reducing false positives by 30% and improvingdefect detection efficiency by 25%.- Automated classification of JIRA tickets: Utilized Natural LanguageProcessing (NLP) to classify and route JIRA tickets to the appropriate serviceteams, achieving 85% classification accuracy. This improved ticket resolutiontime by 20% and enhanced overall service management efficiency.- Multivariate data analysis: Performed root cause analysis.- JMP coordinator and trainer: Provided training and coordination on the use ofJMP

Cavaillon, Provence-Alpes-Côte D’Azur, France

 Projects: * Analysis of data ( numerical or image ) to improve production, yield and quality of products.* Detection of anomalies in a process.* Automation of the centralization of raw data (Excel files, text file ....) in a single database with a single click. Missions: * Identify relevant data sources, control their quality and then extract them in an automatic way.* Know how to set up and administer a database.* Propose recommendations on the databases to be modified.* Analyze data by doing exploratory study (univariate, bivariate, multivariate) and extract relevant information.* Identify the best Machine Learning model that best fits the problem.* Synthesize and popularize the information to make it accessible to the company's managers.* Facilitate the decision making process of companies by acting as a consultant.* Writing of deliverables (reports in English). Machine learning used:Unsupervised: K-means, Affinity Propagation, Agglomerative Clustering, Spectral Clustering.Supervised: Decision tree, Bagging, random forest, Gradient descent, XGBoost, Polynomial regression, Logistic regression...  Tools used: Pack office, VBA Excel, SQL, JMP (SAS), Python, R, JSL.

Paris, Île-De-France, France

 Projects:* Statistical study to create a database of carbon footprint monetary ratios.* Predicting the carbon footprint of a banking transaction.* Creation of a relevant recommendation system, Eco-coach, in order to accompany customers to act well towards the environment.* Detection of anomalies in banking transactions.  Tools used: Pack office, SQL/ PostgreSQL, Python, R, Git/ Gitlab, Google Cloud Platform. Machine learning models used: Unsupervised: K-means, Mini-Batch K-Means, DBSCAN, BIRCH. Supervised: Linear regression, Decision tree, Random forest, One-class SVM, Isolation forest.

Master, Data Science

Licence, Mathematics