One of the main drivers for conversion in online retail is the delivery promise, informing fashion customers about when they can expect their shipment to arrive. Our team owns the forecasting of processing times for all the paths in the complex fulfillment network on which this delivery promise is based. Improving the precision of these predictions has a huge impact on customer satisfaction, allows better fulfillment planning, and enables the business to make better-informed tradeoff decisions.
Our team is composed of applied scientists and software engineers. As an applied scientist, you’ll design, train, extend, and continuously improve forecasting models based on features extracted from diverse datasets produced by high-throughput systems. You’ll do so in close collaboration with the software engineers in your team, who are responsible for building best in class services and infrastructure for experimentation and applying these models in production. A significant part of your role will be to research new opportunities and work closely with stakeholders to understand the underlying business processes and model them in the best possible way to feed into our models.
If you have a passion for creating forecasting models at scale and solving complex problems, we want to hear from you. This is a unique opportunity to make a real impact and help drive the success of our business.
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, and implementing forecasting models within our research-driven software framework to cater for the increasing scale and load and novel use cases. Constantly question the model and the algorithms we use and seek for a constant improvement.
Act as a technical lead and mentor for mid-level Applied Scientists, providing guidance on experimental design, code quality, and scientific excellence.
Design, implement, and maintain automated pipelines covering data ingestion, feature engineering, model training, and evaluation to ensure high reliability and scalability of our machine learning systems.
Involve yourself in our ongoing research roadmap to discover future opportunities.
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.
Contribute to the design, implementation and evaluation of A/B tests that help us measure impact, shape our roadmap and identify opportunities
Join the Zalando community of fellow researchers, exchange ideas, connect and provide your contributions
Promote and support an inclusive culture and diverse team, fostering a positive and productive work environment for all team members.
WE’D LOVE TO MEET YOU IF
You have an academic background in machine learning, statistics, operations research or related fields, and can apply the knowledge effectively
You have substantial experience (ideally 3+ years) discovering, building, evaluating and operating prediction models in production at scale.
You have experience with data processing frameworks such as PySpark or Pandas as well as Machine Learning libraries such as Scikit-Learn, XGBoost, LightGBM, PyTorch or Tensorflow. Previous experience with Databricks is not mandatory but appreciated.
You prefer simple solutions over complex ones but at the same time, you are aware that complex problems sometimes require advanced algorithms.
You’re excited about working in a setup that requires a deep domain understanding (e.g., how our fulfillment processes works).
You are a team player who thrives in an international, agile and cross-functional environment, and is passionate about fostering a positive and productive work environment.
You are fluent in English.
OUR 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 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
Drive your development through our training platform and biannual peer-to-peer review. You'll also receive full access to an O'Reilly online learning subscription
Nach der Prüfung werden unsere Recruiter*innen über eine offizielle Zalando E-Mail-Adresse (@zalando.de) Kontakt aufnehmen.
In einigen Fällen arbeiten wir auch mit einer Auswahl von Headhunter*innen und Agenturen zusammen, um bestimmte Positionen zu besetzen. Bitte beachte, dass weder Zalando noch unsere Rekrutierungspartner*innen irgendeine Art von Bezahlung verlangen, um sich für eine Stelle zu bewerben oder an einem Vorstellungsgespräch teilzunehmen.
