Jean-Gabriel Marchetta

Core Skills: - Linux & Bash – Mastery of terminal usage and automation scripting - MLFlow – End-to-end management of Machine Learning project lifecycles - CI/CD – Version control with Git & GitHub Actions, API security, AWS Solutions Architect certification - DataOps – Docker containerization, Kubernetes orchestration, unit testing (Pytest), AWS SageMaker deployment - Monitoring – Model performance tracking with Prometheus & Grafana Capstone Project: - Deployment of a Product Classification API for Rakuten Applied Skills: - Workflow automation with #ApacheAirflow - Development and deployment of Python APIs using Flask and FastAPI8 - Containerization and orchestration with #Docker and #Kubernetes

Core Skills: - Machine Learning – Classification, clustering, anomaly detection, and text mining - Deep Learning – Recurrent and convolutional neural networks using Keras and TensorFlow - Big Data – Data processing and distributed computing with PySpark - ModelOps – Deployment and automation of ML systems using Docker, MLflow, Kubernetes, and Airflow - Cloud Computing – Proficiency in AWS technologies (Cloud Practitioner, Solutions Architect) Program Highlights: - Design and implementation of AI systems capable of learning and predicting outcomes - End-to-end development: algorithm design, model deployment, and production integration - Strong foundation in modern AI, data processing, and cloud-based machine learning operations

Core Skills: - Agile Methodologies – Mastery of agile frameworks applied to Business Intelligence and Data Science products - Data Project Management – Design and leadership of data-driven products Definition of strategic roadmaps and creation of #MVPs aligned with business needs - Technical Expertise – Advanced proficiency in #PowerBI, #Python, and #SQL Capstone Project: - Improved Velib’ service quality through data analysis for Smovengo, the operator of the Paris bike-sharing system (Machine Learning project management) Applied Skills: - Bridging technical and business teams through agile project management - Translating business goals into measurable data products - Driving data initiatives from concept to delivery

Advanced coursework in machine learning, statistical analysis, and data mining. Proficient in Python, SQL for data manipulation and analysis. Experienced with Seaborn, Matplotlib, Plotly for data visualization. Expertise in predictive modeling, clustering, and classification. Completed real-world projects solving complex business problems. Strong grasp of data ethics and privacy. Specialized in Deep Learning for Computer Vision and NLP. Proficient in TensorFlow, PyTorch for building neural networks. Applied CNNs, Transformers for image classification, NLP tasks. Led projects automating image recognition, text processing. This succinct summary highlights both foundational data science skills and specialized knowledge in Deep Learning, demonstrating readiness for roles requiring advanced analytics and AI expertise.

Core Skills: - Data Exploration & Analysis – Collecting, cleaning, and interpreting data to support strategic business decisions - Statistical Modeling – Building data models to segment marketing audiences and analyze performance - Business Analytics – Conducting sales analysis to improve company strategy and profitability - Database Management – Querying statistical databases to answer key business questions - Data Visualization – Designing dashboards with KPIs and visual indicators to monitor and report results - Market Research – Aggregating and analyzing datasets to conduct data-driven market studies Technical Expertise: - Languages & Tools: Python, R, MySQL, Knime, Tableau Program Highlights: - Joint program with ENSAE, a leading engineering school specializing in statistics and data science - Developed strong analytical, statistical, and technical foundations for data-driven decision making