Senior Applied Scientist - Demand Forecast (all genders)

The Role & The Team

The Partner Tech Applied Science team acts as the engine behind Zalando's growth, partnering with Zalando Partners as well as internal stakeholders to achieve better business performance. We build products that provide better demand signals to partners. By leveraging cutting-edge technology, we ensure our assortment is relevant, engaging, and deeply respectful of customer privacy.

As a Senior Applied Scientist, you will collaborate closely with product managers, engineers, and analysts to refine our industry-leading article demand forecast engine. You will co-own the scientific roadmap for our forecast domain, working with Principal Scientists and leaders to maximize forecast performance by moving beyond simple metrics to true incrementally.

Inclusive by Design

If you think you have what it takes, we encourage you to apply even if you don't meet every single requirement. You may just be the right candidate for this or other roles! At Zalando, our vision is to be the leading pan-European ecosystem for fashion and lifestyle e-commerce – one that thrives on diversity and is truly inclusive by design. We believe that diverse teams fuel innovation and creativity, and we actively seek out talent from all backgrounds.

We actively seek to reduce bias in our hiring and employment processes, focusing on your qualifications, skills, and contributions. To support this, we kindly ask that you refrain from including personal details such as your photo, age, or marital status in your CV, ensuring a fair and equitable evaluation based solely on your abilities and potential.

We are committed to providing an exceptional and accessible candidate experience for everyone. If you require any accommodations to support you throughout the hiring process, please let us know – we are here to assist you.

Discover more about our commitment to creating a diverse and inclusive workplace: https://jobs.zalando.com/en/our-culture/diversity-and-inclusion

What We'd Love You to Do

• Conceptualize, prototype, and productionize state-of-the-art demand forecast solutions. You enjoy finding solutions to new complex problems and don't mind getting your hands dirty (with pen and paper or in your IDE of choice).
• Communicate technical problems and results effectively with other team members and also with (less technical) stakeholders. Educate them about your products and solutions.
• Be the owner of the whole development cycle of algorithms - from opportunity discovery to production. Iteratively improve models and explore the art of possibility (e.g. new data sources, new ways of structuring the problem)
• Build model pipelines and streamline analysis processes, using common programming tools (e.g. Python, R, Scala, SQL, PyTorch, Tensorflow etc.)
• Mentor junior scientists and foster a culture of continuous learning and knowledge sharing within the team.

Requirements

Required

• PhD in statistics, mathematics, physics, operation research or a related quantitative discipline with a strong theoretical foundation in statistics, time series analysis, and machine learning methodologies related to forecasting.
• At least 3 years of industry working experience in developing forecasting models, using both statistical methods and machine learning techniques. Understand the tradeoff of each method and their areas of applications. Have deep knowledge of the state of the art practices in forecasting, but also maintain a bias for simplicity
• Excellent verbal and written communication skills with a curious and self-starter mindset. Ability to unblock yourself, but also proactively request support when needed to remove roadblocks
• Deep proficiency in Python, SQL, and PySpark, with a commitment to high coding standards, including active participation in code reviews and elevating the team's engineering culture.

Preferred

• Demonstrated leadership experience in guiding less experienced colleagues in their work

Our Offer

• 27 days of holiday a year to start for full-time employees (+1 day for every calendar year up to 30 days)
• 2 paid volunteering days a year
• Employee shares programme
• 40% off fashion and beauty products sold and shipped by Zalando, 30% off Lounge by Zalando, discounts from external partners
• Relocation assistance available (subject to prior agreement)
• Family services, including counselling and support
• Health and wellbeing options (including Wellhub, formerly Gympass)
• Mental health support and coaching available
• Drive your development through our training platform and biannual peer-to-peer review