Road & Capacity Scientist (m/f/d)

**DHL Express - a company that connects people!** ================================================= What makes DHL great? Our People! We know each employee’s individual contributions make us the #1 Express Delivery and Logistics Company in the world. *Distinguished as No.1 World’s Best Workplace™ by Great Place to Work and Fortune Magazine* DHL Express is committed to maintaining an environment that empowers every team member to make the greatest possible impact on our business. Our corporate culture is about personal commitment – to our business, to each other and to our global communities. DHL is dedicated to being a great place to work. DHL Express is looking for a **Road & Capacity Scientist** in Diegem. Road & Capacity Scientist is responsible for designing, analyzing, and optimizing DHL’s road network using advanced modeling, optimization tools, and data science techniques. This role translates operational data into actionable network decisions that improve cost, service, asset utilization, and customer experience across linehaul, hubs, and first/last mile operations. As DHL’s processes are increasingly underpinned by data, this role is a key contributor to business process optimization and network transformation. They will extract meaningful insights, identify predictive opportunities, and develop automation possibilities that support better decision-making across the European ground network. The role will identify, develop, and implement analytical models, prototypes, and best-practice methods for business users, ensuring that modeling outputs are practical, implementable, and aligned with business objectives. They will serve as the bridge between network design, operations, technology, and data science, helping optimize processes, systems, and methods using relevant operational data. **How will you contribute to the success of DHL?** ================================================== * Execution of data analytics projects with very limited or no guidance from a supervisor/project lead. * Analysis of the business processes as well as the derivation of problem areas and analytical requirements. * Sourcing initial cleansing and preparation of large amounts of data. Identification and collection of required data, as well as data cleansing. * Develop statistical/mathematical models (e.g., time series analyses, operations research methods, machine learning). * Develop implementation data pipelines. Modify data analysts' code to prepare for deployment. * Clarify data needs and take action with the IT organization. * Support the identification of more efficient ways to store, source, query, and activate data. * Deploy best practices to optimize processes, systems, and methods using relevant data. * Support the definition of project contents, deliverables, and timelines of data analytics projects in terms of data needs. * Source, prepare, pre-analyze, and cleanse data as per business needs. * Largely independent preparation and presentati