Senior Machine Learning Scientist / Data Engineer - Logistics Algorithms (all genders)

About the Team

As a Senior ML Scientist / Data Engineer, you will drive algorithmic research-driven software development in a logistics team. Our systems make critical scheduling, planning, and routing decisions within warehouses, processing millions of customer orders every week. Predictive warehousing allows us to preemptively take actions that improve warehouse efficiency by solving a stochastic optimization problem at the crossroads of combinatorial optimization and data science. Our research pipeline enables fast incremental improvements that directly impact the productivity of our warehouses.

Responsibilities

• Drive the research, design, and implementation of algorithms and predictive models.
• Deliver end-to-end solutions and set the bar for the entire development cycle, including research, prototyping, implementation of production software, testing, and operation of highly available production systems.
• Influence research and development methodologies to foster a scalable, data‑driven architecture.
• Support and coach other Applied Scientists by sharing knowledge and expertise in applied research.

Qualifications

• Hold a Master’s or PhD in Mathematics, Computer Science, or another quantitative field, together with industry experience in algorithm‑related software development in Java, Kotlin, Python, or similar.
• Hands‑on experience with state‑of‑the‑art methods in software engineering, particularly microservice architecture and distributed systems for data processing (e.g., Spark, Databricks).
• Practical understanding of advanced algorithmic techniques (e.g., combinatorics, graph theory), mathematical modeling (operation research, statistics, experimentation), and machine learning approaches (forecasting, Bayesian networks).
• High degree of autonomy to translate real‑world business cases into mathematical problems, with a proven record of at least 6 years of applied research experience.
• Strong collaboration skills within an agile and cross‑functional team environment, engaging with engineers, product owners, and fellow applied scientists.

Benefits

• Employee shares program
• 40% off fashion and beauty products sold and shipped by Zalando
• 30% off Zalando Lounge
• Discounts from external partners
• 2 paid volunteering days a year
• Work from abroad for up to 30 working days a year
• 27 days of vacation a year to start
• Relocation assistance available (subject to prior agreement)
• Family services, including counseling and support
• Health and wellbeing options (including Gympass)
• Mental health support and coaching available