Senior Applied Scientist- Network Behavior (all genders)

Overview

The Role and The Team

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 predictions 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 prediction 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 prediction 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.

WED LOVE TO MEET YOU IF

• You have a strong academic background in machine learning, statistics, operations research, or related fields
• You have experience operating prediction models in production in a microservice environment, ideally with end-to-end MLOps frameworks such as SageMaker
• You have experience with data processing frameworks such as PySpark or Pandas, as well as Machine Learning libraries such as Scikit-Learn, XGBoost, PyTorch, or TensorFlow
• You prefer simple solutions over complex ones but understand that some problems require advanced algorithms
• You are excited about working in a setup that requires a deep domain understanding (e.g. how our fulfillment processes work)
• You are a team player who thrives in an international agile and cross-functional environment and are passionate about fostering a positive and productive work environment
• You are fluent in English

Responsibilities

• Contribute to modeling, solving, and implementing forecast models within our research-driven software framework to cater for increasing scale and load and novel use cases.
• Constantly question the model and the algorithms we use and seek constant improvement.
• Involve yourself in our ongoing research roadmap to discover future opportunities.
• Deliver end-to-end solutions and set the standard for the development cycle, including requirement engineering based on deep domain & business understanding, prototyping, implementing production software, testing, and operating the highly available production system.
• Collaborate closely with our software and data 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 measure impact, shape our roadmap, and identify opportunities.
• Join the Zalando community of fellow researchers, exchange ideas, connect, and provide contributions.
• Promote and support an inclusive culture and diverse team fostering a positive and productive work environment for all team members.

Our 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

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