Senior Operations Research Engineer, Ocean Network Optimization

At Maersk, we connect people, businesses and markets across the world through one of the most complex logistics networks ever built. As a Senior Operations Research Engineer, Ocean Network Optimization , you will join a team at the forefront of transforming how global trade moves. Leveraging advanced analytics, mathematical modelling and optimisation algorithms, we solve some of the industry's toughest challenges, from improving shipping container flows and vessel routing to designing resilient ocean networks that balance cost, service, sustainability and reliability. Your work will directly influence operational and strategic decisions that shape the future of global supply chains. This is an opportunity to do more than build models. You will define and solve high-impact problems, lead innovative optimisation capabilities from concept through implementation, and help drive the shift towards data-driven, model-led decision making across Maersk's global ocean network. Working alongside talented colleagues from diverse backgrounds and disciplines, you will combine deep technical expertise with practical business impact, mentoring others and turning complex ideas into scalable solutions. If you are excited by tackling real-world problems at global scale and seeing your work create measurable value across one of the world's largest ocean logistics networks, Maersk offers an unparalleled platform to make your mark. Within your impact and responsibilities, you will: Design advanced optimisation models and heuristics and take them from idea to validated and implemented capability Frame complex planning problems as clear mathematical formulations with explicit assumptions and success criteria Build reusable modelling components that follow modern engineering standards and integrate with production data systems Improve existing optimisation logic by closing gaps and lifting performance and scalability Run structured experiments to compare alternatives and verify model behaviour with data Translate findings into clear recommendations and partner with stakeholders to drive implementation and adoption Shape the innovation roadmap by identifying new application areas and accelerating promising concepts into pilots and scale Coach junior analysts and raise standards in modelling practice, documentation and code quality Communicate results, trade offs and limitations in simple and decision-oriented language What you'll be accountable for: Integrity, stability and performance of optimisation logic used in planning and decision making Robust validation and successful implementation of new modelling features with clear readiness criteria Clear documentation of assumptions, constraints and data dependencies to support transparent decisions A value based and well prioritised modelling backlog focused on measurable business impact and time to value Demonstrated improvements in modelling logic, scalability and performance in real planning scenarios Effective adoption and correct use of optimisation capabilities across the user community with visible change outcomes Active contribution to the optimisation innovation pipeline by shaping new concepts, evaluating emerging methods and advancing promising ideas toward pilots and scale Leadership in the transformation agenda by helping teams shift from manual work to model driven planning and ensuring new solutions are embedded and used with confidence You can offer: A PhD or master's degree in engineering, mathematics, computer science or a related quantitative field with exposure to optimisation or modelling Documented experience designing and deploying optimisation models or decision support algorithms in operational or production environments Expert level Python skills, experience applying C++ for performance critical components and strong SQL capabilities Advanced knowledge of Operations Research , including Mixed Integer Programming, graph theory, decomposition methods, and large-scale optimisation Strength in problem framing, algorithm design, empirical validation and scaling solutions Confident use of Git and modern software engineering workflows Ability to collaborate smoothly across diverse functions and to build strong working relationships that support clear communication, shared problem solving and aligned decision making Ability to lead change by guiding stakeholders through adoption, explaining trade offs and ensuring appropriate use of models A disciplined approach to documentation, testing, version control and reproducibility 5 days per week onsite presence at the advertised location It is a plus if you also bring: Familiarity with GPU based acceleration or parallel computation for optimising large problem instances Experience with AI or machine learning methods Knowledge of deep learning architectures and training workflows Background in advanced statistics or statistical inference Experience with time series modelling or forecasting techniques If you're ready to jump in, push the boundaries of modelling and optimisation, and make a visible impact from day one, let’s connect. We’re excited to see the ideas, expertise, and momentum you’ll bring as we elevate Maersk’s decision‑support capabilities and shape the future of our network planning technologies. Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements. We are happy to support your need for any adjustments during the application and hiring process. 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