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Principal Applied Scientist - Network Optimization

Location

Berlin

JobType

Full time

About the role

Zalando fulfills more than a hundred million customer orders every year and volumes are increasing. Fulfillment Core within Zalando builds and operates systems that are at the core of Zalando's platform strategy and ensure timely, efficient, and correct delivery of every one of our customers' 185+ million orders every year. Enabling the fulfillment of orders is a complex process, involving the choice of physical locations of our warehouses and the placement of stock, the planning of inner warehouse processes and capacity management, the management of a diverse range of fulfillment and delivery configurations, all while optimizing towards various competing targets. As a Principal Applied Scientist, you will play a pivotal role in transforming Zalando's supply chain by enhancing customer experience, and addressing complex and critical challenges. You will develop financially viable self-serve products utilizing Optimization or Simulation techniques. Collaborating with a team of highly talented colleagues in Fulfillment Core, you will drive innovation and resilience within our supply chain operations. You'll find our Berlin campus and HQ in the vibrant area of Friedrichshain. With amazing views of the Spree river and East Side Gallery, it's a campus designed to inspire. Berlin is the city that has shaped our business. Are you up for a new experience in one of the most vibrant, diverse, and green cities in Europe?

About the company

It's the perfect time to join Zalando on our journey, from being a pioneer in the world of e commerce, to the Starting Point for Fashion in Europe. We connect customers, brands, and partners across 23 markets. Help us drive digital and sustainable solutions for fashion, logistics, advertising and research, bringing head-to-toe fashion to more than 49 million active customers through a team of diverse skill-sets, cultural backgrounds, and interests.

Skills

optimization
simulation
mathematical programming
mixed-integer linear programming
metaheuristics
constraint programming
python
c++
java