Data Scientist Lead

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.
YOUR ROLE
As a Lead Data Scientist, you will play a critical role in shaping and driving the technical capabilities of our global data science team, leveraging AI and data analytics to support the strategic goals of a leading worldwide shipping company. You will lead a team of data scientists, support their technical development, and work cross-functionally to define best practices, provide strategic insights to top management, and promote knowledge sharing across diverse teams. Additionally, you will oversee and foster the internal community of data scientists, ensuring collaboration and knowledge sharing across the global organization.
WHAT ARE YOU GOING TO DO?
**Team Leadership & Development**:
Lead a team of data scientists ensuring clear direction, effective communication, and alignment with company objectives.
Provide mentorship and coaching to team members, fostering a collaborative environment that encourages professional growth.
Identify skill gaps and work with HR and leadership to provide necessary training and development opportunities.
Organize technical reviews, code audits, and peer-learning sessions to ensure best practices and maintain a high-quality standard of work.
**Strategic & Technical Contributions**:
Collaborate with top management to define the AI and data science strategy for the organization, ensuring alignment with business goals.
Conduct technical feasibility assessments for new AI technologies, tools, and platforms, providing expert viewpoints to guide investment and adoption decisions.
Stay up-to-date on the latest trends in AI, machine learning, and data science to drive innovation in the shipping industry.
Develop and enforce best practices in model development, deployment, and maintenance, ensuring the team operates with high standards of reproducibility, performance, and ethics.
**Community Management & Knowledge Sharing**:
Manage and grow the internal community of data scientists, fostering collaboration, communication, and shared learning across different regions and project teams.
Facilitate knowledge sharing across geographically dispersed teams through workshops, documentation, and internal tech talks.
Develop and maintain a central repository of best practices, code templates, and solution architectures to ensure the team operates cohesively.
Promote a culture of continuous learning by organizing seminars, hackathons, and attending global conferences.
**Transversal & Cross-functional Responsibilities**:
Work closely with data engineers, project managers, core IT and other stakeholders to design end-to-end solutions integrating AI models.
Collaborate with cross-functional teams to ensure the integration of AI-driven insights into various business functions, from operations optimization to customer experience enhancement.
Manage and report on key metrics that demonstrate the business impact of data science initiatives.
Engage with internal and external stakeholders, effectively communicating AI-driven strategies and results to both technical and non-technical audiences.
**Project Oversight & Resource Management**:
Oversee multiple projects, ensuring that timelines, resources, and deliverables are managed effectively.
Serve as a point of escalation for technical challenges and facilitate cross-project resource allocation.
Review and sign off on major deliverables such as machine learning models, data pipelines, and AI-driven tools.
WHO ARE WE LOOKING FOR?
**Technical Expertise**:
Proven experience leading and mentoring a team of data scientists or other technical professionals.
Expertise in machine learning frameworks (e.g., Scikit-Learn, PyTorch, Tensor flow) and strong programming skills in Python or R.
Hands-on experience with data engineering workflows, including data integration, ETL processes, and cloud platforms (AWS, Azure, GCP).
Familiarity with MLOps practices, model deployment, and monitoring in production environments.
Experience with various data & AI stacks suc