Alexandre Terrand-Jeanne

– Deep expertise in building scalable data infrastructure, building complex algorithms (including NLP models, RAG systems), creating digital twins for experimentation, and leveraging data for strategic decision-making. – Developed and deployed production-ready REST API endpoints on OVH cloud infrastructure to serve Machine Learning/Deep Learning models. Enabled seamless integration of advanced AI capabilities into backend systems, ensuring scalability and reliability. – Developed and deployed a personalized matching solution leveraging BERT NLP models. This innovative feature enabled matching based on nuanced criteria such as client preferences (e.g., gender) and professional experience, further enhancing matching accuracy and customer satisfaction. – Developed a Retrieval-Augmented Generation (RAG) system prototype to automate question answering using the company FAQ and another one to improve data discovery within the data catalog. – Designed and implemented a digital twin of the marketplace operations to create a sandbox environment for testing and validating new matching algorithms, scoring methodologies, and for simulating KPI evolution. This proactive approach accelerated innovation and de-risked operational changes.

– As the first data hire, I spearheaded the development of the data function from the ground up, consistently delivering data-driven solutions that directly impacted revenue, operational efficiency, and strategic innovation. – Dramatically improved client-professional matching algorithms, increasing the matching rate from a fluctuating 50-90% to a consistent 80-90%. This optimization directly translated to a significant revenue uplift, contributing hundreds of thousands of euros annually to the company's bottom line. – Provided strategic data insights to C-level executives, identifying key growth opportunities in service optimization and market expansion. Notably, recommended a shift from department-level to urban unit geographical granularity. This optimization improved resource allocation, reduced imbalances in professional/customer density, and enhanced service efficiency across markets. – Architected and implemented a robust and scalable data pipeline on Google BigQuery, leveraging Dataform for SQL-based ELT and Python on GCP VMs for advanced processing. This modern data infrastructure empowered data-driven decision-making across the organization and supported rapid business growth. – Played a crucial role in scaling the data team by mentoring and training junior data analysts. – Consistently spearheaded Research & Development initiatives, Dedicating 2-3 months annually to proposing and implementing innovative data projects, main contributor to the company's eligibility for French Research Tax Credit (CIR).