This position offers a unique opportunity to develop and apply your cutting-edge knowledge of data science methods and tools to create results and insights that are transforming the transport and logistics industry.
As a Data Scientist with Maersk, you will be part of the Data Science & Artificial Intelligence community, where we leverage data to make actionable business recommendations by combining domain expertise, scientific methodology and technology. We specialise in mathematical modelling, forecasting, optimisation and machine learning. Maersk is at the forefront of developing industry leading solutions & analytical applications: we drive a larger bottom-line impact than any of our industrial peers in Europe, and are 18-24 months ahead of most enterprises in industrial digital transformation.
This is an extremely exciting time to join a growing and dynamic team that solves some of the toughest problems in the industry and builds the future of trade & logistics. We operate in a fast-paced environment utilizing modern software and platform approaches, and bias toward action. We are responsive to customer needs, value outcomes, and are passionate about using technology to solve problems.
Maersk’s Technology organisation offers a unique opportunity to impact global trade via the largest container shipping company in the world. In our Copenhagen office, we are a growing team of more than 30 nationalities. We focus on our people and the right candidate will have broad possibilities to further develop competencies in an environment characterised by change and continuous progress.
As a Data Scientist you will participate in various projects with strong support from data scientists and software engineers, to shape business decisions and drive digital transformation at one of the largest companies in the world.
Your responsibilities include:
• Deeply understand business problems and apply your ability with predictive modelling, forecasting, machine learning, operations research or mathematical optimisation techniques to deliver commercially valuable insights. We care about team members who are not only technical specialists, but are excited about understanding the logistics domain---no prior experience in logistics required, so long as you are committed to learning!
• We work end-to-end: design, prototype, implement and test descriptive, predictive and optimisation models as software, in a talented and highly engaged team of data scientists and software engineers.
• Operate in scrum teams and independently direct time and resources together with other software engineers and data scientists 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.
• You will partner with businesses and internal/external stakeholders, including traveling to our front-line locations around the world on occasion. This is a role with global impact, and requires a candidate motivated by and comfortable with a highly international environment.
• M.Sc. or PhD degree in statistics, applied mathematics, operations research, computer science or related field
• PhD or more than 2 years industry experience
• 5+ years’ experience with using Python and/or R (SQL is a plus) to build and apply data science models (e.g., predictive and optimisation)
• Deep 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
• Ability to communicate data science results to business stakeholders
• Fluent proficiency in both written and oral English
• Experience with using large data system (e.g. SQL, Hadoop, or Spark) and data visualization
• Working knowledge of Git, Docker, Jenkins, Kubernetes and cloud technologies, ideally Azure.