Everybody knows our yellow vans, trucks and planes around the world. But do you know how data drives our business and how we leverage algorithms and technology in our core operations? We will share some “behind the scenes” insights on Deutsche Post DHL Group’s journey towards a Data-Driven Company. • Large-Scale Use Cases: Challenging and high impact Use Cases in all major areas of logistics, including Computer Vision and NLP • Fancy Algorithms: Deep-Neural Networks, TSP Solvers and the standard toolkit of a Data Scientist • Modern Tooling: Cloud Platforms, Kubernetes , Kubeflow, Auto ML • No rusty working mode: small, self-organized, agile project teams, combining state of the art Machine Learning with MLOps best practices • A young, motivated and international team – German skills are only “nice to have” But we have more to offer than slides filled with buzzwords. We will demonstrate our passion for our work, deep dive into our largest use cases that impact your everyday life and share our approach for a timeseries forecasting library - combining data science, software engineering and technology for efficient and easy to maintain machine learning projects..

Severin Schmitt

Affiliation: Deutsche Post DHL Group

Severin is a Senior Data Scientist at Deutsche Post DHL Group, leading the forecasting tech team, main developer of DPDHL’s forecasting library and holds a PhD in mechanical engineering. He is passionate about combining Data Science and Software Engineering for long lasting and maintainable machine learning projects; he loves guiding the scoping of new projects as well as the change management processes necessary to bring small and big solutions to life; he is curious about timeseries forecasting and constantly looking for interesting discussions.

Leona Ruedt von Collenberg

Starting out as a Strategy Consultant & Analyst for DPDHL, Leona discovered the power of applying Data Science in Logistics. She holds a MSc in Business & Logistics and is now heading one of our Analytics teams. Therefore she can combine what she enjoys most: Work with & develop a group of talented Machine Learning Experts and Analytics Strategy enthusiasts, steer projects to embed data (science)- driven decision making deeply into our business processes and shape Analytics Governance for our company.

Thorsten Kranz

With a background in Physics and Neuroscience Research Thorsten has been working as a Data Scientist for many industries. He is driving DPDHL’s efforts of increasing the efficiency for building productionquality, large scale Data Science solutions for the business together with his team. While working as a Manager for many years now he has remained a nerd at heart – with a passion for data, algorithms and Software Development in Python.