Maersk is achieving an unprecedented transformation in the growth of its businesses. Here data & software take center stage as we rethink how we engage with customers and partners, lead the industry in converting into CO2 neutral ships, and optimize the world’s trade flows across our global network. In this Data Scientist role you will create solutions within quantitative revenue management ranging from pricing to capacity optimization. Within this application space you will participate in cutting edge data science requiring advanced algorithms consuming large volumes of data moving at high speeds.
This job also presents a rarely found opportunity for you to help define what quantitative revenue management looks like in container shipping while working on highly in-demand solutions that are defining the modern algorithm-fueled economy. We do our share of R&D and create POCs, but we go all the way by deploying and scaling winning solutions to make a real impact on the operations at Maersk, the largest container shipping company in the world.
We wear what makes us feel comfortable in our newly renovated office; we meet for walks along the water; we enjoy breakfast and lunch in our canteen - or in our collaboration lounges - while finding solutions to problems that affect millions of people every day. If you are passionate about working in an entrepreneurial environment supporting an ambitious team on a great transformation journey – then this role is the perfect next step in your career!
This position offers a unique opportunity to develop and apply your knowledge of data science and quantitative revenue management to create results and insights that are transforming the transport and logistics industry.
- We operate in an innovative and creative environment utilizing modern technologies.
- We embrace innovation methods where we have a close dialogue with end users, make early use of mock-ups & POCs and are committed to incremental development.
- We value customer outcomes and are passionate about using technology to solve problems.
- We are a diverse team with colleagues from different backgrounds and cultures.
- We offer the freedom, and responsibility, to shape the setup and the processes we use in our community.
- We support continuous learning, including through conferences as well as workshops and meetups in our internal community of data science practitioners.
As a Data Scientist in Revenue Management you will participate in projects to shape business decisions and drive digital transformation at one of the largest companies in the world.
Your responsibilities include:
- Deeply understand end-user needs and business problems in the pricing and capacity domain. Apply statistical modelling, machine learning, and mathematical optimization to deliver commercially valuable insights. We care about team members who are not only technical specialists, but are excited about understanding the specifics of container shipping logistics.
- Design, prototype, implement and test descriptive, predictive and optimisation models, in collaboration with a talented and highly engaged team of data scientists, data engineers, and software engineers.
- Adopt applicable scrum-team methods to independently direct time and resources together with other data scientists, data engineers, and software engineers in the team. You will need to participate in transforming the way we work. The cultural transformation of our business and industry is the guarantee of long-term growth and success.
- Partner with business units and other internal stakeholders, including our front-line colleagues located around the world. This is a role with global impact which requires a candidate that thrives in an international environment.
We are looking for
- M.Sc. or PhD degree in statistics, applied mathematics, operations research, computer science or related field. At least three years of work experience that involves revenue management and/or closely related fields.
- Experience using Python and SQL to build and apply data science models (e.g., predictive and optimisation). R skills are valued, but you need to commit to achieving high skill with Python.
- Understanding and experience with the theory and application of data science models, for example machine learning and statistical models (prediction, classification, clustering, time series forecasting, regression models, etc.), mathematical optimisation, decision science and operations research (linear and mixed-integer programming, dynamic optimisation, stochastic optimisation, etc.)
- A good team player, balanced with the autonomy and motivation to produce individually. You are a problem solver who knows theory but embraces hands-on discovery and testing with real data.
- Ability to communicate data science results to business stakeholders.
- Fluent proficiency in both written and oral English.
- Experience using large data system (e.g. SQL, Hadoop, or Spark) and data visualization.
- Working knowledge of Git, Docker, Kubernetes and cloud technologies, ideally Azure.