Data scientist

CMA CGM; Marseille; Sur place; EUR 45 000 - 75 000; Plein temps

Résumé du poste

CMA CGM is seeking a Data Scientist to join the Decision Science team in Marseille. The role focuses on designing, analyzing, and experimenting with data science models to support tactical and strategic decisions.

You will work with business experts to translate needs into solutions, develop complex models, and deploy analytics to drive optimization across logistics and network design.

Qualifications

• MSc or PhD in Data Science, Applied Mathematics or related field.
• Strong background in data science technologies (data analysis, machine learning).
• Proficient in Python and SQL.
• Excellent communication and collaboration skills.
• Knowledge of logistics or maritime industries is highly valued.
• Experience with data querying languages and statistical or mathematical software.
• Ability to write algorithms and select appropriate methods.
• Strong team collaboration and ability to convey technical information clearly.

Responsabilités

• Collaborate with business experts to understand needs and translate requirements.
• Work with partners to transform requirements into business solutions.
• Develop, validate, and deploy data science models to inform decisions.
• Identify data sources and structure data for models.
• Define KPIs and metrics to optimize objectives.
• Communicate results to stakeholders across the organization.
• Support IT for integration and deployment of algorithms.
• Engage with internal and external partners on projects.
• Handle complex issues with minimal supervision.

Connaissances

Python

Data Science

SQL

Communication

Teamwork

Innovation

Logistics

Formation

MSc or PhD in Data Science or Applied Mathematics

Outils

Python

SQL

Statistical Software

Mathematical Software

Description du poste

Job description

YOUR ROLE

Within the Data Science team and in cooperation with other departments of the group, your mission will be to develop solutions to address complex business problems. You will work on the design, the analysis and the experimentation of data science models to support tactical and strategic decisions.

WHAT ARE YOU GOING TO DO

As part of the Decision Science team, you will

• Work closely with business experts to better understand and translate business needs and requirements.
• Collaborate with internal and external partners to transform business requirements into a business solution.
• Use state‑of‑the art approaches and propose new algorithms to generate solutions to complex problems such as resource planning, scheduling, facility location and network design
• Develop, validate and deploy complex models to drive decisions.
• Identify, collect, and structure data from different sources to specify input for optimization models
• Identify relevant business KPIs and metrics that drive optimization objectives
• Communicate obtained results with different stakeholders and business entities
• Be in support of IT teams for the industrialization and integration of developed optimization and simulation algorithms
• Participate in discussion with internal and external (academic and industrial) partners
• Independently handle complex issues with minimal supervision, while escalating only the most complex issues to appropriate staff.

Profile description

• A MSc with 3+ years of experience or PhD degree in Data Science, Applied Mathematics or related fields.
• A strong background in data science technologies (Data Analysis, Machine Learning, etc.) is a must
• Strong programming skills using Python
• Good skills in SQL.
• Knowledge in the logistics industry is essential, and in the maritime industry is very appreciated
• Experience with data querying languages, and statistical or mathematical software.
• Proficient in writing algorithms and knowing when to apply them.
• Outstanding communication skills.
• Ability to communicate technical information clearly to both technical and non-technical people.
• Collaborative, able to work in multidisciplinary teams
• Open-minded and innovative, focus on customer value