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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.
Job Responsibility:
Conceptualize, prototype, and productionize state-of-the-art demand forecast solutions
Communicate technical problems and results effectively with other team members and also with (less technical) stakeholders
Be the owner of the whole development cycle of algorithms - from opportunity discovery to production
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:
Master degree or above (PhD) in quantitative economics, statistics, mathematics, physics, operation research or a related quantitative discipline with a strong theoretical foundation in statistics, econometrics, time series analysis, and machine learning methodologies
At least 5 years of industry experience (3 years with PhD degree) in developing forecasting models, using both statistical methods and machine learning techniques
Excellent verbal and written communication skills with a curious and self-starter mindset
Deep proficiency in Python, SQL, and PySpark, with a commitment to high coding standards
Demonstrated experience in guiding less experienced colleagues and organizing team educational initiatives
Nice to have:
Command of causal inference is a big plus
What we offer:
27 days of holiday a year to start for full-time employees
2 paid volunteering days a year
Hybrid working model with up to 60% remote per week
Work from abroad for up to 30 working days a year
Employee shares program
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 counseling 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