Senior/Principal Applied Scientist - Assortment Optimization | Senior/ Principal Applied Scientist - Assortment Optimization (all genders)

Zalando SE

Berlin, Berlin, Deutschland
Published Aug 29, 2025
Full-time
No information

Job Summary

This role offers a unique greenfield opportunity for a Senior/Principal Applied Scientist to architect and implement a world-class, intelligent assortment optimization system for Zalando, Europe's leading fashion e-commerce platform. You will be at the forefront of combining cutting-edge machine learning with operations research and economics to solve complex, large-scale problems. Day-to-day, you'll be responsible for the end-to-end scientific strategy, developing sophisticated demand and trend forecasting models, and applying advanced optimization techniques to select the optimal product assortment. You will also pioneer sequential decision-making models for inventory management and measure true impact using causal inference. This position is ideal for a scientific leader who thrives on ambiguity, has a strong entrepreneurial mindset, and is passionate about mentoring others while driving significant commercial success through innovative scientific solutions.

Required Skills

Education

Master's or PhD in a quantitative field like Computer Science, Operations Research, Machine Learning, Statistics, or Economics

Experience

  • 8+ years of industry experience solving large-scale problems in a quantitative field
  • Proven track record of designing and deploying high-impact scientific solutions in production (e.g., supply chain optimization, demand forecasting, algorithmic marketing, large-scale recommendation systems)
  • Deep, hands-on expertise in Machine Learning (advanced forecasting, Reinforcement Learning, Deep Learning with PyTorch/TensorFlow)
  • Deep, hands-on expertise in Operations Research (mathematical optimization, simulation, modeling of complex systems)
  • Deep, hands-on expertise in Causal Inference & Econometrics (experimental design, uplift modeling, causal impact from observational data)
  • Professional experience with an entrepreneurial and strategic mindset

Languages

Not specified

Additional

  • Not specified