Lead Data Scientist
il y a 2 semaines
Led by Rodolphe Saadé, the CMA CGM Group, a global leader in shipping and logistics, serves more than 420 ports around the world on five continents. With its subsidiary CEVA Logistics, a world leader in logistics, and its air freight division CMA CGM AIR CARGO, the CMA CGM Group is continually innovating to offer its customers a complete and increasingly efficient range of new shipping, land, air and logistics solutions.
Committed to the energy transition in shipping, and a pioneer in the use of alternative fuels, the CMA CGM Group has set a target to become Net Zero Carbon by 2050.
Through the CMA CGM Foundation, the Group acts in humanitarian crises that require an emergency response by mobilizing the Group’s shipping and logistics expertise to bring humanitarian supplies around the world.
Present in 160 countries through its network of more than 400 offices and 750 warehouses, the Group employs more than 155,000 people worldwide, including 4,000 in Marseilles where its head office is located.
**MISSION**:
**WHAT ARE YOU GOING TO DO**:
**The position will focus on four main missions**:
Accelerate AI projects by delivering models, data processing pipelines, analyses, or problem modeling.
Lead the projects, suggesting technical solutions, and presenting findings to executive members and business sponsors, while providing support to ensure successful team delivery.
Drive AI initiatives, particularly within the scope of our partnerships such as Mistral, Google, Kyutai while staying abreast of state-of-the art research.
Provide strategic guidance to business units and IT teams on AI; actively participate in the training and adoption of AI within the Group.
**WHO ARE WE LOOKING FOR**:
**Experience**: 4-8 years in a data scientist position or similar role.
**Education**: Degree from a top engineering school, university, BAC+5, or PhD; specialization in mathematics, statistics, or computer science.
**Skills**: Strong skills in mathematical modeling and problem-solving, with extensive knowledge in statistics, machine learning and deep learning (NLP is a plus). Autonomy and adaptability; ability to synthesize and communicate effectively.
**Technical Stack**: Proficiency in Python, SQL, Spark with additional expertise in model deployment (Airflow, Gitlab, Docker) and/or deep learning (pyTorch, vLLM).
Come along on CMA CGM’s adventure
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