AI/ML Scientist (Applied Scientist)

Design, build, and maintain data-driven AI/ML and optimization models specifically for container terminal operations affecting equipment efficiency, yard positioning, vessel sequencing, and vehicle routing.

Develop operational tools for real-time terminal management and strategic models for long-term planning impacting global container shipping operations.

Translate complex physical terminal realities into mathematical models, monitor and improve model performance through collaboration with operations and leadership.

5+ years of industry experience delivering technical or optimization solutions; strong PhD or exceptional demonstrated ability may substitute partly.

M.Sc. or PhD in Operations Research, Industrial Engineering, Machine Learning, Statistics, Applied Mathematics, Computer Science, or related quantitative field.

Proven experience producing production-quality Python code integrating ML, optimization, simulation, or statistical models.

Experience in operations research techniques (LP, MILP, constraint programming), simulation, statistical modeling, or AI/ML applied to operational problems.

Deep expertise or solid working knowledge in operations research optimization, discrete event simulation, statistical modeling, or operational AI/ML suitable for complex scheduling and resource allocation.

Ability to bridge physical operational challenges with mathematically sound models and to communicate technical insights to non-technical operational stakeholders.

Experience shipping data-driven solutions in a production environment impacting real-world physical operations, preferably in logistics, terminal operations, or similar complex contexts.