Senior Applied Scientist (all genders)

Role: Senior Applied Scientist Team: Content Personalization & Governance team at Zalando. The team provides personalized content selection and ranking for Zalando's discovery surfaces, driving the evolution into an inspiring ecosystem that integrates shopping, storytelling, and style inspiration through the Home Feed. The team sits at the intersection of algorithmic relevancy and business value, using state-of-the-art deep learning and reinforcement learning models to build intelligent content discovery systems. Responsibilities: - Develop and deploy state-of-the-art Deep Learning and Reinforcement Learning models to power real-time content delivery algorithms across high-traffic surfaces. - Formulate and solve multi-objective ranking and allocation problems at scale, optimizing dynamic trade-offs between short-term conversion, long-term customer engagement, and business monetization. - Contribute to long-term research roadmaps for personalized content discovery and ranking, translating strategic business objectives and governance goals into concrete scientific problems. - Partner closely with Principal Scientists, Data/ML Engineers, and Product Managers to deliver state-of-the-art machine learning solutions to production, navigating high technical uncertainty and aligning across stakeholders. - Act as a mentor and technical sparring partner to scientists across the team, advocating for rigorous experimental methodologies and contributing to Zalando's broader science community. Qualifications: - Advanced degree (M.Sc., Ph.D.) or equivalent industry experience in Machine Learning, Applied Economics, Econometrics, Computer Science, Statistics, or a related quantitative field. - 6+ years of applied science experience leading end-to-end AI/ML solutions from ideation and research to large-scale production, ideally with a strong publication record. - Deep hands-on expertise in Deep Learning, Recommender Systems, Reinforcement Learning/Bandits, Multi-Objective Optimization, and Causal ML, with extensive experience designing and evaluating complex A/B experiments. - Proven leadership in shaping scientific roadmaps and collaborating across Product, Science, Engineering, and senior leadership. - Strong technical proficiency in Python and Deep Learning frameworks (e.g., TensorFlow, PyTorch) for RL, and modern AI coding assistants and agents, along with hands-on experience building and scaling production recommender and ranking engines on cloud platforms (AWS). What We Offer: - Employee shares program - 40% off fashion and beauty products sold and shipped by Zalando, 30% off Zalando Lounge, discounts from external partners - 2 paid volunteering days a year - 27 days of vacation a year to start - Relocation assistance available (subject to prior agreement) - Family services, including counseling and support - Health and wellbeing options (including Gympass) - Mental health support and coaching available - Drive your development through our training platform and biannual peer-to-peer review - Opportunity to work from abroad for 30 (working) days per calendar year