Applied Scientist (all genders) - B2B Data Science and Algorithms

Role --- Applied Scientist (all genders) – B2B Data Science and Algorithms. Join the ZEOS department, responsible for partner‑facing Zalando Logistics Solutions, to build innovative ML and optimization systems that improve inventory health and order‑fulfilment efficiency for B2B logistics partners. Responsibilities --- - Develop ML/DL forecasting models for demand, returns, and lead‑times. - Design stochastic inventory optimization solutions and recommendation services. - Create and evaluate emerging Agentic AI systems for partner decision‑making. - Define success metrics, collaborate with engineers to deploy models as scalable services, and monitor real‑world impact. - Build rigorous Agentic AI evaluation frameworks and safety guardrails. - Own end‑to‑end research, prototyping, production, and performance monitoring. - Work cross‑functionally with product managers, data engineers, and software engineers. Qualifications --- - Master's degree or higher in a quantitative field (preferred). - 3+ years of industry experience as an Applied Scientist, Data Scientist, or Research Scientist. - Expertise in at least one area: time‑series forecasting (ML/DL), ML engineering, operations research & optimization, or Agentic AI evaluation. - Proficiency in SQL and handling large‑scale datasets. - Strong communication skills to explain complex scientific concepts to product and business stakeholders. - Collaborative, product‑oriented mindset with an entrepreneurial attitude. - Commitment to inclusive, high‑challenge, high‑support team culture. What We Offer --- - Employee shares program. - 40% discount on Zalando fashion & beauty products, 30% off Lounge, plus external partner discounts. - 2 paid volunteering days per year. - Ability to work from abroad up to 30 days per year. - 27 days of vacation (starting). - Family services, counseling, and support. - Health and wellbeing options (Wellhub/Gympass) and mental‑health coaching. - Continuous development through training platforms and bi‑annual peer reviews.