Senior Data Scientist – Logistics Algorithms (all genders)

 As a Senior Data Scientist, you will be part of an expert team of scientists 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 understanding intra-logistic processes and predicting their duration and throughput to improve both warehouse operations planning and execution, as well as delivery promise accuracy for customers.

In this role, you will face two significant challenges: 

• Build, productionize, and maintain accurate prediction models. This requires a deep understanding of warehouse operations, from picking and packing to sorting and dispatching. You’ll need to gain this operational knowledge and translate it into accurate and reliable predictions.

• Warehouses generate vast quantities of data. Your challenge will be to distill this data into actionable insights that allow data-driven / algorithmic decision-making.

If you are passionate about leveraging data science to solve real-world problems and enjoy deriving insights from complex datasets, we want to hear from you. This position offers the opportunity to create innovative, data-driven solutions and drive the success of our logistics operations.

INCLUSIVE BY DESIGN

At Zalando, our vision is to be inclusive by design. And this vision starts with our hiring - we do not discriminate on the basis of gender identity, sexual orientation, personal expression, ethnicity, religious belief, or disability status. You are welcome to leave out your picture, age, or marital status from your application. We only assess candidates on their qualifications and merit. 

We want to provide you with a great candidate experience. Feel free to inform us of any accommodations you may need, so we can best support you throughout the hiring process. 

do.BETTER - our diversity & inclusion strategy: https://corporate.zalando.com/en/our-impact/dobetter-our-diversity-and-inclusion-strategy 

Our employee resource groups: https://corporate.zalando.com/en/our-impact/our-employee-resource-groups 

WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)

• 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 and applied scientists 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. Proactively test and implement ideas, translating them into actionable improvements.

• 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, computer science, or a related field and are passionate about data analysis and predictive modeling, and owning machine learning pipelines end-to-end. You’re familiar with concepts such as regression, classification, clustering, time series analysis, and other relevant machine learning algorithms; and can apply these methods to uncover insights 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 working with data platforms and big data technologies, such as Apache Spark, and you are skilled in managing large-scale data pipelines and distributed computing principles. Ideally, you have worked with Databricks or are confident in quickly adapting to it.

• You have experience writing data-processing workflows in Python or Scala and are co