Job Description

As a Senior 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?

What you'll do

• Together with other Operations Research scientists, Applied scientists and Analysts from Fulfillment Core, you will immerse yourself in the domain and develop complex mathematical models to ensure that the right product is available at the right location at the right time, all while adhering to our network constraints..
• You will collaborate with our skilled engineers to implement the mathematical models in production and assist in maintaining and adapting them.
• You will work closely with our stakeholders to understand the current goals and challenges within the fulfillment domain.
• You will help optimize a wide range of business processes (e.g. inventory distribution strategies, warehouse processes or order placement strategies) and configurations (e.g. warehouse network resilience, delivery connections) by leveraging various mathematical approaches, including Discrete Event Simulation, Mixed-Integer Linear Programming, and metaheuristics.  
• As a member of Fulfillment Core, you will also provide inputs to other research initiatives across the business unit.
• More generally, you will be part of our vibrant community of Applied Scientists at Zalando, participating for example in regular exchange meetings, reading groups and mentoring opportunities.

What we expect from you

• You have prior experience/interest in solving complex mathematical problems in Supply Chain in a retail/E-Commerce/Airlines/Logistics or similar domain. Previous experience in Network Simulation (Discrete Event Simulation) and/or Optimization is desirable but not mandatory.
• Your educational background is in Operations Research or another mathematical or statistical field.
• You have knowledge in mathematical programming (e.g., mixed-integer linear programming) and/or applied statistics.
• You are proficient in at least one programming language (e.g. Python or C/C++ or Java) suitable for a production-grade environment and are familiar with fundamental software development practices, including version control, data structures, and databases.
• You are highly self-motivated, with a strong sense of ownership and accountability.
• You have a customer-focused mindset and excel in teamwork: You like interacting with stakeholders and understanding their challenges, and you enjoy collaborating with your colleagues.
• You are comfortable with working in a diverse, inclusive and international environment where English is the working language.

What we 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 up to 60% 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
• Drive your development through our training platform and biannual peer-to-peer review