Job Description
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.
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
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.
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 comfortable with Spark for building efficient and scalable solutions.
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.
If you think this role fits you, we encourage you to apply even if you don't meet every single requirement.
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
Learn all about Zalando and our values here: https://jobs.zalando.com/en/?gh_src=22377bdd1us
Zalando is a European online fashion platform- offering a broad assortment of fashion for men, women and children. It carries over 1.500 brands and over 150.000 product choices for over 17 million customers in 15 countries. By constantly optimising its processes and platform offerings, using its e-commerce expertise and lots of can-do spirit, Zalando have become Europe's leading online fashion retailer in only a few years. Its goal is to create the world’s best online fashion experience. The cores of its business are what the company focuses on, always striving to be cutting-edge in fashion, technology, marketing, and logistics. Zalando SE in Berlin is the group’s centrepiece which focuses on the development of its core product: the online shopping experience. Zalando SE operates the international business and takes care of their business development. Zalando SE comprises functions like the management, marketing, administration, and technology.
