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Tier-1 brand, mid-level experience requirement, and Bangalore location increase applicant density.
Strong operations-research and terminal-operations focus makes domain experience highly required and less transferable.
Explicit 5+ years, PhD/MSc preference, and specialized optimization/ML skills create stringent filtering.
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Lead design, implementation, and delivery of advanced simulation, optimization, and AI/ML models to improve container terminal operations globally.
Develop operational tools for daily terminal use and strategic models for long-term planning to enhance efficiency and business value.
Collaborate with stakeholders to understand terminal operations, communicate model results, and continuously improve solutions based on data-driven insights.
Minimum 5+ years of industry experience in simulation modeling, optimization solutions, or data science product delivery.
PhD or M.Sc. in Operations Research, Industrial Engineering, Machine Learning, Statistics, Applied Mathematics, Computer Science, or equivalent experience.
Strong expertise in simulation modeling and optimization in complex operational environments.
Proven proficiency with Python programming and modern development tools like Git and JIRA; experience with AI development tools and cloud environments.
Experienced in operational AI/ML applied to complex resource allocation, scheduling, or logistics domains, preferably in container terminal, port logistics, or similar environments.
Skillful in translating complex operational requirements into efficient, maintainable engineering and data science solutions with measurable operational impact.
Capable of independent stakeholder engagement and cross-functional collaboration to deliver production-ready analytical products.