About the job
We are seeking a highly motivated and experienced Planning Optimization Engineer/Consultant to join our team and play a pivotal role in developing and implementing cutting-edge planning optimization solutions for container terminals and logistics operations. The ideal candidate will possess a strong academic background in industrial engineering, operations research, computer science, or a related field, coupled with relevant industry experience in planning, optimization, and data science. You will be responsible for designing, developing, and implementing algorithms, models, and data-driven solutions to optimize complex operational processes, ensuring efficient resource utilization, reduced costs, and enhanced productivity.
Develop and implement complex mathematical models and algorithms to address operational challenges in container terminal management, logistics, and transportation.
Apply operational research and data science methodologies to solve intricate business problems, such as resource allocation, scheduling, route optimization, and predictive modeling.
Lead efforts to optimize container/cargo/resources scheduling, vessel/yard planning and management, gate operations, equipment allocation, and other logistics supporting entities through data-driven approaches.
Utilize machine learning, deep learning, and advanced analytics techniques to create predictive models that optimize resource allocation, reduce bottlenecks, and improve overall efficiency.
Conduct in-depth data analysis to identify patterns, anomalies, and opportunities for optimization within large datasets.
Explore the potential of technologies such as quantum computing to solve complex optimization problems that are beyond the capabilities of classical computing.
Collaborate closely with cross-functional teams, including data engineers, software developers, domain experts, and operational staff, to implement and deploy optimization solutions.
Create informative data visualizations and dashboards to communicate optimization results and insights to stakeholders.
Conduct research and stay updated with the latest developments in operational research, optimization techniques, data science, and optimization technologies to drive innovation within the company.
Continuously evaluate the performance of optimization models and algorithms, fine-tuning them for real-world deployment and guide the team during any assigned project.