Location Berlin Contract Full time Job Category Applied Science & Research

THE ROLE & THE TEAM

Do you feel happy when shopping online and your order arrives the very next day, all articles in a single box? And do you get frustrated when every article arrives separately, some even late? We do as well! And our team - Fulfillment Planning - is tackling exactly this challenge. We build the software that decides how fashion items are moving inside Zalando's Europe-wide logistics network and how they reach your home.

As a Senior Applied Scientist in the Fulfillment Planning team in Berlin, you will work on the core system and algorithms that control the flow of fashion items through our Europe-wide logistics network. By applying operational research and machine learning techniques, you will explore new ways to speed up deliveries, increase sustainability and reduce logistic costs. Within a multidisciplinary team of research and engineering, you will work on highly critical systems to the business.

WHAT WE'D LOVE YOU TO DO (AND LOVE DOING)

• Drive innovation in algorithm development to optimise the balance between delivery speed and cost-efficiency across our logistics network. Collaborate with cross-functional teams to incorporate cutting-edge scientific methodologies into live business operations, ensuring a continuous flow of improvements.

• You and your team will work like a startup and take ownership for the whole research and development cycle - from data collection and architecture design to testing, implementation and maintenance.

• Design and implement advanced, data-driven algorithms to optimise resource allocation and order fulfilment. Build and refine allocation models that mimic the intricate behaviour of our logistics network. These algorithms will factor in macro-level constraints such as warehouse configurations, transportation capacity, inventory distribution, and order routing strategies to improve the accuracy of promises and planning.

• Work closely with product managers, data analysts, and engineers, translating business requirements into scientific problems and delivering innovative solutions.

• Lead data-driven analyses aimed at improving key performance indicators (KPIs) and operational efficiency. Oversee the end-to-end experimentation process to propose and validate enhancements to our planning algorithms, continuously improving their accuracy and effectiveness.

WE'D LOVE TO MEET YOU IF

• You bring solid experience in operations research, combinatorial optimization (exact and heuristic methods) and working knowledge of graph theory and probability theory. You have experience in machine learning, including practical applications as well as a good understanding of the underlying mathematical concepts.

• Strong skills in Python and/or a Java-based language Kotlin (e.g., Kotlin) & SQL, hands-on experience with Git, working with cloud services (e.g. S3, dynamodb, k8s etc.).

• You are eager to collaborate and pursue new concepts and are willing to push them all the way to production. Ideally, you already have experience building production systems at scale (experience in Java/Kotlin and Python is recommended).

• You excel at analysing large datasets to uncover meaningful insights. Your background in statistics and quantitative methods allows you to create hypotheses, run statistical tests, and draw data-driven conclusions.

• You have hands-on experience in microservice architecture and patterns, REST, Kubernetes, architecture documentation, data and API specifications, quality assurance and testing methods.

• You have a degree in computer science, mathematics, statistics or another similar quantitative field and are eager to keep learning and