Machine Learning / Data Scientist

Are you excited about implementing ML, AI, and optimization solutions that improve real-world logistics and operations? Do you have strong mathematical skills and enjoy solving complex problems across classical ML, discrete optimization, and generative AI? If so, this is your opportunity to make an impact at DFDS A/S.

We are seeking a skilled and pragmatic Machine Learning Engineer/Data Scientist to join our AI Centre of Excellence in Copenhagen.
In this role, you will focus on designing and implementing scalable AI-driven solutions to enhance our logistics network, vessels, terminals, and warehouses across Europe.

About the role

In this position, you will have the opportunity to lead initiatives with the goal to turn business problems into data science solutions that provide tangible value for DFDS, and our customers, based on prototyping and product development following the minimum viable product mindset. We work with an explorative and fail-fast mind-set.

As part of our Technology and Innovation division, in the AI CoE, we have full end-to-end ownership of initiatives from building predictive models, creating prototypes, and assisting with integrating solutions into existing products. Some examples of projects we have worked on include

• Planning of hazardous cargo on board our ferries (discrete optimization),

• Automated vehicle registration on our terminals (visual recognition)

• Forecasting future demand for logistics (inference models)

• RAG based LLM application for extracting structured data from documents

Our pipeline of future projects includes many exciting new initiatives.
We are always looking for what could be our next project and you will have a role In that process, driven by our own curiosity and imagination. 

Your typical project will include:

• Work and collaborate with other data scientists, data engineers, business analysts, and product owners in cross-functional teams, to understand their needs and ensure a seamless workflow for model development and deployment.

• Translating complex solutions and sharing findings or recommendations in a clear, understandable way to both tech savvy colleagues and non-experts.

• Designing and implementing machine learning algorithms and statistical modelling (regression, forecasting, clustering, optimization, time series etc.) and expose them via API endpoints.

• Dockerise our software/models and deploy these on our Kubernetes clusters.

• Lead projects from ideation all the way through a usable product that can create proven impact, following an agile mindset.

About the Team

Our team consists of 8 experienced colleagues with 7 different nationalities and with different backgrounds, working collaboratively on different projects and regularly share findings and best practices. We keep a continuous focus on researching what new technologies we should focus on and define our ML-Ops standards together.

About you

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. 

With this in mind, we envision our ideal candidate to have a background in a quantitative field such as Computer Science, Mathematics, Engineering, Physics, or a related discipline.
We imagine you have at least one year of professional experience post-graduation in building and deploying machine learning applications.

Your strong mathematical skills should encompass areas like machine learning, discrete optimization, and statistical modelling.
You solid understanding of modern software development practices is essential where you have shown hands-on experience with cloud computing (preferably AWS), API development, and containerization technologies such as Docker and Kubernetes. 

We appreciate candidates who have experience working in cross-functional teams and who approach business problems pragmatically. While industry experience in logistics or shipping is a plus, it is not a requirement.

Moreover, we are looking for someone who is curious about the latest developments in AI, including large language models and generative AI. You should be committed to continuous learning and eager to contribute to your own development by finding the best solutions.
You will translate complex solutions and share findings or recommendations in a clear, understandable way to both tech-savvy colleagues and non-experts.

As a person you are open-minded with strong communication skills, able to collaborate closely with business and technology functions at various levels. 

Working at DFDS

Our newly built headquarters in Copenhagen is a unique, modern workplace. Here, we enjoy different work zones but open and quiet areas, our own game room, fitness facilities, cantina and café and a rooftop terrace with a beautiful ocean view, all just 5 minutes from the nearest train & metro station.

When you join us, you will become a part of Technology & Innovation (T&I), one of DFDS’ five divisions. Here you will get the opportunity to work with cutting-edge technologies and a cloud-based setup with event streaming and serverless.

While you’re with us, we want you to develop and grow. At DFDS, we believe that development happens first and foremost through activities in the workplace. One of these activities is our GROW framework which will support and help you to develop in your role and career.

By being inclusive and embracing our differences we get the best from everyone and an even greater result. We take great pride in empowering our people to make a real difference.

We hope you will join the movement and grow with us.

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

If you think your personality, skills, experience, and ambition match this role, we’d love to hear from you. Please send us your CV in English as soon as possible as we’re keen to meet potential candidates on an ongoing basis.

Is there something you need to know, we haven’t covered here, please do not hesitate to reach out to our Data Science chapter lead, Per Hansen on pehan@dfds.com

We look forward to hearing from you.