Senior Applied Scientist – Logistics Algorithms (all genders) at Zalando SE
Berlin, Berlin, Germany -
Full Time


Start Date

Immediate

Expiry Date

09 Jul, 25

Salary

0.0

Posted On

06 Jun, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

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 optimize order fulfillment 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 fulfillment, thereby minimizing 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 analyzing 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.

Responsibilities

Contribute to modeling, solving, implementing, and evaluating our research-driven software framework to cater to the increasing scale and load. Constantly question the model and the algorithms we use and seek 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.

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