Maxence Labesse

Designed and delivered a complete data collection system from PoC to production, including: - Web scraping & API integration (multiple third-party sources) - AI-assisted data filtering using GPT (OpenAI API) - REST API (FastAPI or Django), task orchestration (Celery + Redis) - Containerized deployment with Docker + NGINX - Cloud hosting, logging, and integration with client workflows

- Framework design and leadership: Led the design and implementation of a robust web scraping framework, ensuring its scalability and adaptability to evolving project needs. Took ownership of architectural decisions to create a maintainable and efficient solution. - Maintenance and bug resolution: Actively contributed to maintaining the existing codebase, diagnosing and resolving issues to guarantee optimal performance and reliable data extraction. - Collaboration and code quality improvement: Organized coding sessions and actively participated in code reviews to elevate overall code quality. Worked closely with the team to refine coding standards and enforce best practices, fostering a culture of continuous improvement.

Application Enhancement and Maintenance: - Developed new frontend and backend features to meet user needs. - Optimized existing functionalities, updated web scraping scripts, and resolved bugs to improve performance and reliability. - Expanded unit and integration tests to strengthen application stability. Technical Documentation: - Addressed the lack of technical documentation by detailing the application's architecture, technologies, data model, processes, and asynchronous tasks. - Simplified complex technical concepts to make them accessible to the Product Owner and clients. Migration to OpenShift: - Successfully deployed the application on an OpenShift platform using a microservices architecture. - Provided comprehensive documentation to facilitate future maintenance and scalability.

Designed and developed a Python library enabling seamless communication between a testing software (Python) and a centralized test result management tool through API. Ensured efficient data transmission and integration to streamline the testing workflow.

Development of Advanced Features Enhanced an existing Jira project in production by integrating advanced functionalities to meet operational needs efficiently. Creation of a New Project - Designed and managed a new Jira platform from the ground up, ensuring a structured and efficient setup. - Developed a Python application to streamline interactions with the Jira API, improving automation and data exploitation.

Customer Portfolio Segmentation Designed a customer segmentation model based on current and potential value to drive targeted commercial actions. Development of an AutoML Library Built an AutoML library to automate key steps in predictive modeling (exploration, data preprocessing, feature engineering, model selection), accelerating decision-making for go/no-go use cases. (Prototype: AutoMxL) Data Analysis & Business Insights - Extracted and processed data for marketing campaigns and business needs (SQL/Excel). - Developed predictive scoring models and interactive dashboards. - Conducted market and customer behavior analysis.