Data Scientist - Applied AI & Optimisation

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 robust and scalable solutions 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 within machine learning, optimisation, and generative AI. 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: 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, such as ship’s crew or terminal workers 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 provide: Shared standards for MLOps and responsible AI Peer sparring and code/model reviews A modern stack (Python, APIs, k8s based CI/CD pipelines, and MLOps tooling) Example of 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 educational background can be many, e.g. a M.sc. or Ph.D. in Computer Science, Mathematics, Physics, Engineering, or similar. you most likely bring: ~2–4 years of industry experience working with ML/statistical models Strong skills in modelling, mathematics, and problem formulation Experience with designing, training and implementing of predictive models or optimisation algorithms in a production environment. Your strengths You enjoy turning real-world problems into structured models that delivers value You appreciate the practices that keep