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 presentation of results and implications of Data Analytics projects.
• Manage contact with internal and external customers on data analytics topics at the work and specialist level and with middle management in the context of current and future analytics projects.
• Support in onboarding and coaching junior data science and engineering colleagues as part of the project.
• Actively contribute to team responsibilities and support business development activities on request.
• Produce accurate outcomes of analytics tasks and communicate as such (accurate does not imply success).
• Manage contact with internal and external customers on data analytics topics at the work and specialist level.
• Manage contact with middle management in the context of current and future analytics projects.
• Relationship management with business departments about relevant analytics topics, as well as internal and external expert networks in the data analytics field. Do you have what it takes?
• University degree in Mathematics, Statistics, Physics, Computer Science or related natural sciences / technical degree, or comparable qualification.
• More than 4 years of experience working in data science, mathematics, statistics, research, and/or IT.
• Knowledge of machine learning, statistics, data visualization, and cleansing techniques, as well as data pipelining and big data technologies.
• Experienced in analyzing complex datasets and building mathematical models, also in a practical context.
• Having programming skills and/or experience in scripting languages (Python, R, or Java) and good experience in working with databases (relational, big data) and data pipelines.
• Ability to produce creative and analytical solutions based on clear and thorough analyses of complex processes and business relationships.
• Comfortable explaining complex analytical and technical content to various audiences.
• Energetic and success-oriented problem solver.
• Independent work ethic, integrity, and loyalty, positive “can-do” attitude"
• Fluent in English, written & spoken. (Other languages are a benefit) Become a part of our team If you are looking to further your career at the global market leader in Express logistics and are keen to be part of an organization whose focus is to connect people and improve lives, we are interested to hear from you. Please submit your application along with your CV and a copy of your highest educational degree (e.g., Bachelor’s, Master’s, or MBA certificate). DHL is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic. Recruitment Fraud Alert: DHL Express will never request payment or personal/financial information from applicants or employees at any stage of the recruitment process. Any such request should be treated as fraudulent. All email correspondence will be sent from the official DHL domain e.g. xxx@dhl.com. Protect yourself by verifying job offers and communications. Your safety is important to us. Recruitment Team