THE ROLE & THE TEAM
As a (Senior) Applied Scientist, you will be part of an expert team of researchers and engineers responsible for developing and operating algorithmic decision components that optimise order fulfilment in all of Zalando’s warehouses. Your focus will be on creating advanced batching algorithms that determine the most efficient way to group orders for fulfilment, thereby minimising the total walking distance required for picking items.
In this role, you will face three significant challenges: conducting cutting-edge research to enhance algorithmic performance, gaining a deep understanding of warehouse operations to identify and address optimization opportunities, and systematically analysing data to ensure that algorithms perform in production systems as anticipated from experimental results.
If you are passionate about applying scientific principles to solve real-world problems and have an interest in developing impactful algorithms, we want to hear from you. This position offers the chance to contribute to innovative solutions and drive the success of our logistics operations. For a glimpse into the type of work our team does, check out our recent preprint: https://arxiv.org/abs/2401.04563.
WHY YOU SHOULD BE INTERESTED…
Contribute to modeling, solving, implementing, and evaluating our research-driven software framework to cater for the increasing scale and load. Constantly question the model and the algorithms we use and seek for a constant improvement.
Deliver end-to-end solutions and set the standard for the entire development cycle, including requirement engineering based on deep domain & business understanding, prototyping, implementing production software, as well as testing and operating the highly available production system.
Collaborate closely with our software engineers to mutually influence and understand system constraints and opportunities, and take part in shaping the future of our system.
Think abstractly and discover correlations between problems, methodologies, and solutions.
Promote and support an inclusive culture and diverse team environment, fostering a positive and productive work environment for all team members.
WE’D LOVE TO MEET YOU IF…
You have a strong academic background in mathematics or computer science and are interested in combinatorial optimization. You know the basic concepts of discrete optimization such as min-cost flows, linear- and integer programming, the travelling salesperson problem, or the bin packing problem. And you are able to detect these concepts even if they are hidden in complex real-world problems.
You’re excited about working in a setup that requires a deep domain understanding, e.g. how our logistics order processing works.
You have hands-on experience in microservice architecture and patterns, REST, Kubernetes, architecture documentation, data and API specifications (e.g. OpenAPI), quality assurance and testing methods.
You have experience writing software on the JVM, and are familiar with Scala or you are open to learning and working with Scala in the future.
You’re a team player who thrives in an agile and cross-functional environment, and is passionate about fostering a positive and productive work environment.
OUR OFFER
Zalando provides a range of benefits, here’s an overview of what you can expect. Ask your Talent Acquisition Partner to learn more about what we offer.
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
Hybrid working model with 60% (or more) remote per week, actual practice is up to each team to best support their collaboration
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.
If you think this role fits you, we encourage you to apply even if you don't meet every single requirement.
