Help build AI systems that power real-world logistics

At DFDS, we use AI to solve concrete operational problems across European logistics, ferry, and terminal operations.

We are looking for a Data Scientist focused on Applied AI and optimisation — someone who enjoys turning complex, real-world challenges into working systems that deliver measurable impact.

This is not a research role. This is about building solutions that are used.

About the role

You will join the Data Science Chapter and AI Center of Excellence (CoE), where we both enable AI adoption across the organisation and build applied AI solutions for real operational problems.

In this role, your primary focus will be on developing and delivering AI solutions that support decision-making in logistics, ferry, and terminal operations.

You will work on turning complex operational challenges into deployable systems — combining modelling, optimisation, and modern AI approaches such as LLMs and agentic workflows.

At the same time, you will contribute to a shared foundation of best practices, reusable patterns, and continuous learning across the team.

You will collaborate closely with product owners and engineers, while the chapter provides support for deployment, monitoring, and scaling.

What success looks like

In your first 6–12 months, you will:

• Deliver at least one MVP used in a real operational context

• Contribute to a model or solution that is integrated into a product or workflow

• Help shape how we apply AI and optimisation in practice at DFDS

What you will do

• Translate operational problems into analytical and modelling approaches.

• Develop ML models, statistical methods, and optimisation solutions

• Design and build AI products leveraging agentic workflows where they create real value

• Build MVPs and iterate them into production with engineers

• Collaborate with stakeholders and communicate results clearly

About the team

You will be part of DFDS’ Technology & Innovation division (T&I), working in a collaborative and experienced environment across data science, optimisation, and engineering.

The Data Science Chapter and AI CoE provides:

• Shared standards for MLOps and responsible AI

• Peer sparring and code/model reviews

• A modern stack (Python, APIs, cloud, containers)

Example problems that we are working on

• Optimising route planning across logistics networks

• Reducing fuel consumption through predictive and optimisation models

• Predicting overbooking in freight and passenger systems

• Forecasting invoice payment behaviour

• Designing agent-based planning tools for terminals

• Automating structured data extraction using LLMs and RAG

About you

We are looking for an early- to mid-career professional with strong analytical foundations.

Your background

• M.Sc. or Ph.D. in Computer Science, Mathematics, Physics, Engineering, or similar

• ~1–5 years of experience working with ML/statistical models

• Strong skills in modelling, mathematics, and problem formulation

• You have had experience with designing, training and implementing of predictive models or optimisation algorithms in a production environment

Your strengths

• You enjoy turning messy real-world problems into structured models

• You are comfortable working across ML, statistics, and optimisation

• You are curious about LLMs and modern AI — but not driven by hype

• You can prototype solutions in Python and collaborate with engineers on production

For this position, we value strong analytical thinking and modelling ability more than deep software engineering expertise.

We think the strongest teams are built on diversity and inclusivity. Contrasting opinions, varied skills, and strong characters bring out the best in us all. And we cannot wait for you to join.

Working at DFDS

Join the movement and grow with us

We promote a great workplace with a diverse and vibrant community. Our award-winning headquarters in Copenhagen offers a modern workspace with ocean views and easy access to public transport.

Beyond the day-to-day work, DFDS has a strong social and community culture, including employee sports clubs, choir, and other shared activities — as well as on-site facilities that make it easy to connect with colleagues across teams.

You will join an environment focused on:

• Real-world impact over hype

• Learning and experimentation

• Continuous development through T&I’s career development model, GROW

Are we a match? Then what are you waiting for? Apply now.

If you think your personality, skills, and experience match this role, we’d love to hear from you. Please submit your CV and a brief motivational letter (in English) on why you are applying as soon as possible as we review applications on an ongoing basis.

For questions, please contact Data Science Chapter Lead, Per Hansen at pehan@dfds.com.

We look forward to hearing from you.