Principal Applied Scientist

Role: Principal Applied Scientist As a Principal Applied Scientist, you will serve as a technical authority and strategic leader for the Bidding and Allocation engines within Zalando Marketing Services (ZMS), driving scientific vision and high-impact innovation across our ad tech platforms. Every time a customer interacts with Zalando, our ad tech systems make real-time decisions at immense scale. The platform evaluates thousands of candidate ads, predicts complex performance metrics, and executes sophisticated auction mechanics in tens of thousands of requests per second. At the intersection of market dynamics, machine learning, and high-throughput engineering, you will define how we solve these high-stakes algorithmic challenges. In this role, you will spearhead our optimization strategy, operating at the intersection of high-load, low-latency Engineering, Auction Theory, and Mechanism Design. Your technical domain will span Reinforcement Learning, Multi-Objective Optimization, Value-based Bidding, Incrementality-driven Allocation, and Large-Scale Bayesian Inference. Furthermore, you will play a key role in advancing our auction mechanisms to harmonize advertiser ROI with an exceptional user experience. Responsibilities: - Lead the research and development of our real-time bidding and allocation algorithms, optimising for long-term platform health, advertiser performance, and user relevance. - Advance our Auction and Mechanism Design capabilities to ensure a fair, efficient, and transparent marketplace. - Collaborate with Product Managers, Engineers, and Analysts to translate complex business constraints into mathematical objective functions. - Drive the long-term scientific and execution roadmap for ZMS Ad Tech Bidding Optimisation in collaboration with Engineers and ML Scientists and foster a culture of technical excellence. - Coach/support other members of the team, acting as a force multiplier for our scientific community. Qualifications: - PhD in Machine learning with a track record of publications and industry experience. - Proven track record of research excellence, evidenced by peer-reviewed publications in relevant fields such as Computational Advertising, Auction Theory, Mechanism Design, or Game Theory (please include these in your application) and/or equivalent applied industry impact track. - At least 5+ years of experience (commensurate with Principal level) in optimising complex systems through automated algorithms, specifically within Ad Tech, Marketplaces, or related fields. - Deep theoretical and technical expertise in optimisation, control theory, or reinforcement learning applied to bidding and budget pacing. - Expert knowledge of productionalising ML models within ultra-low latency constraints and experience with large-scale distributed systems. - Strong proficiency in Python and related stack, with a solid understanding of how to architect scalable data pipelines for sparse, high-dimensional advertising data. What We Offer: - 27 days of holiday a year to start for full-time employees (+1 day for every calendar year up to 30 days) - 2 paid volunteering 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 counselling 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