Optimization Expert

Job title:

Optimization Expert

Company:

Maersk

Job description

Optimization ExpertJoin Maersk Energy Markets in Leading the Energy TransitionAre you an algorithmic wizard with a passion for solving complex problems, experience applying your skills on real world business problems and driving impactful change? If so, we invite you to join us in leading the energy transition at Maersk Energy Markets.About the RoleMaersk Energy Markets is the fuel sourcing and trading organization of Maersk, and plays a key role to enable Maersk in its green energy transformation. A core functionality is our fuel planning capability, ensuring that we plan to refuel at the right port, volume and grade for each our +700 ships. This is a complex task given the many fuel types in play, regulatory costs, emission zones, and ever-changing vessel schedules. If care and fuel choices aren’t thought through, it leaves Billion of dollars at stake.We are launching a fundamental reworking of our planning system; to support our energy transition future and optimize our business, we are on the lookout for a highly skilled and experienced Optimization Expert. This role is pivotal in enhancing our capabilities, as we explore the best approaches and subsequently implement them. The role is based in Copenhagen where you will become part of a highly specialized fuel optimization team.Key Responsibilities

  • Rebuild our planning systems to support Maersk’s energy transition goals.
  • Increase our algorithmic and optimization power to identify and implement the most effective approaches.
  • Develop and implement algorithms to support the purchase of 11 million metric tonnes of fuel annually for Maersk’s fleet of over 700 vessels.
  • Work closely with stakeholders to understand their needs and solve their problems.
  • Cross-Functional Collaboration: Work with software engineering, data engineering, and product platform teams to implement solution
  • Support Maersk’s green transition initiatives.

Key Requirements

  • PhD or Master’s degree in Computer Science or a related STEM field.
  • Minimum 5 years of experience developing algorithms.
  • Practical experience with Column Generation and Dantzig-Wolfe decomposition.
  • Team work focused.
  • Proven innovative application of technical skills to complex problems
  • Strong focus on understanding customer needs and providing tailored solutions.
  • Motivated by delivering tangible, real-world impact.
  • Passionate about supporting the green energy transition.

Why Join Us?

  • Be at the forefront of Maersk’s energy transition journey.
  • Chance to apply advanced operations research on real world problems
  • Work in a dynamic and innovative environment.
  • Collaborate with a team committed to making a significant impact.
  • Contribute to sustainable and green initiatives.

Application ProcessInterested candidates are encouraged to submit their applications along with their CV and a cover letter detailing their relevant experience and motivation for the role.Join us and be part of a team that is set to redefine the future of energy at Maersk.#LI-MG1
#LI-Hybrid
#LI-POSTMaersk 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. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing .

Expected salary

Location

København

Job date

Sun, 06 Jul 2025 02:01:20 GMT

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