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Open nowPosted 23 hours ago

Data Scientist, Maritime Logistics

NORDEN8 open roles

Where
Denmark
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Your applicationOpen nowData Scientist, Maritime LogisticsNORDEN · Denmark

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

13.5% of postings close within 7 days. Measured by our own scanner across the market. NORDEN postings stay open a median of 9 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.6%3 days
  3. 13.5%7 days
  4. 21.8%14 days
  5. 36.6%30 days
  6. 58.9%60 days
This job: posted 23 hours ago

NORDEN median: 9 days open

The posting

Your models might start in Python. Their impact goes far beyond it.

Your career in data science might only just be getting started. At NORDEN, you will apply it to real logistics challenges involving vessels, ports, terminals, weather and cargo flows.

At NORDEN, moving cargo from A to B involves vessels, ports, terminals, weather, cargo flows and countless operational constraints. Understanding how all those pieces interact can make a real difference to the decisions we make and at the end our base margin.

As our new Data Scientist in Maritime Logistics, you will turn that complexity into models we can explore, test and learn from, helping us make better operational and commercial decisions.

You do not need years of experience or deep shipping knowledge. What matters is a strong foundation in Python and supply chains and the curiosity to apply it to the real world.

Why this role?

Because you get to take problems that exist in the real world and build models that help us understand what could happen next.

You might be modelling how vessels move through a logistics network, exploring the capacity of a terminal or testing what happens when weather, congestion or operational constraints change. Other times, you could be looking at historical data, improving an existing model or helping colleagues understand what different scenarios could mean commercially and operationally.

A central part of your role will be translating complex logistics systems into simulations that allow us to ask better questions before decisions are made in the real world.

You will work closely with commercial and operational colleagues while learning from experienced colleagues within analytics and shipping. Our broader Quantitative Analytics environment works with Python and technologies including Prefect, Docker and Azure and you will also gain practical experience developing solutions and visualisations using Power BI.

What you will be doing

You will work where shipping, logistics and data science meet. Helping us continuously improve how we work with simulation, optimisation, analytics and software development.

To be more specific you will:

  • Design and develop simulation models of supply chains and maritime logistics operations.
  • Use discrete-event simulation and agent-based modelling to represent vessels, terminals, ports and other parts of complex logistics systems.
  • Analyse logistics networks and explore opportunities to improve capacity, throughput, utilisation and operational efficiency.
  • Use historical and operational data to calibrate, validate and continuously improve your models.
  • Build analytical tools that allow colleagues to explore scenarios and understand their operational and commercial implications.
  • Develop robust analytical models and simulation solutions in Python.
  • Create visualisations that make complex outputs easier to understand and use.

What you bring

There is no need to understand every aspect of shipping or every modelling method from day one. What matters is that you have a good analytical foundation, an understanding of supply chains and logistics and the curiosity to keep learning.

Qualification we are looking for:

  • Have 0–3 years of relevant professional experience.
  • Hold a degree in Supply Chain Management and Logistics, industrial engineering, operations research or another relevant quantitative field.
  • Have a good foundation in Python and are comfortable writing structured, maintainable analytical code.
  • Are fluent in English, our working language.
  • Are eligible to work in Denmark.

What matters just as much is how you work with people. You are curious about how complex operations actually work, you ask questions before jumping to the model and you can explain what your analysis means to colleagues who may never open a line of Python themselves.

Application

Please upload your motivation letter, resume and relevant diplomas via our website as soon as possible and no later than 22 November 2026. Your motivation letter helps us understand what drives you, why you are interested in the role, and how your skills and experiences could contribute to the team. We are especially interested in your motivation and transferable skills, not a recap of your CV. It is your opportunity to tell us the story behind your application.

We review and interview candidates on an ongoing basis.

We will do our best to get back to you at least within ten working days after the application deadline, 22 November 2026.

In NORDEN we value a range of perspectives, educational backgrounds and professional experience and encourages all qualified candidates to apply.

Our company

We are a global provider of ocean- based freight services for bulk and project cargo of all sizes. We integrate freight solutions with port logistics, helping our customers optimise and decarbonise supply chains. We provide tailored solutions built on flexibility, reliability, and intelligence.

Our agile business model ensures stability by continuously adapting our fleet to market developments and customer needs.

Founded in 1871, NORDEN is one of Denmark’s oldest internationally operating shipping companies. Incorporated in Denmark, we are listed on Nasdaq Copenhagen as part of the OMX Nordic Large Cap index.

With offices across 6 continents, we are a truly integrated part of global trade.

Posting text belongs to the employer. Removal requests: contact us.

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