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Senior Applied Scientist - Partner Tech

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Zalando Lounge

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Location:
Germany , Berlin

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

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
  • 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
  • Design and implement advanced experimentation frameworks to measure the causal impact of CRM campaigns
  • Build sophisticated models to identify which customers should receive specific promotions, minimizing waste and maximizing relevance
  • Directly influence how Zalando allocates marketing investment, ensuring we attribute value correctly and optimize for long-term growth

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
  • Command of causal inference is a big plus
  • At least 5 years of industry experience (3 years with PhD degree) 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
  • Demonstrated experience in guiding less experienced colleagues and organizing team educational initiatives
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

Additional Information:

Job Posted:
February 20, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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