THE ROLE & THE TEAM
As a Senior Principal Applied Scientist, you will drive the scientific vision and execution for the Bidding and Allocation engines within Zalando Marketing Services (ZMS).
Every time a customer interacts with Zalando, our ad tech system must make high-stakes decisions in real-time. The system evaluates thousands of candidate ads, predicts performance metrics, and executes sophisticated auction logic to decide which ad to show and at what price. Every second, we process tens of thousands of requests where the intersection of market dynamics and machine learning creates unique challenges.
In this position, you will lead our optimization efforts at the frontier of high-load low-latency Engineering, Auction Theory, and Mechanism Design. The technical scope covers Large Scale Bayesian Inference, Value based Bidding, Incrementality-based Allocation, Reinforcement Learning, and Multi-Objective Optimization. You will be instrumental in evolving our auction mechanisms to balance advertiser ROI with a premium customer experience
WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)
•Lead the research and development of our real-time bidding and allocation algorithms, optimizing 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 Optimization in collaboration with Engineers and ML Scientists and foster a culture of technical excellence.
•Mentor and grow senior level members of the team, acting as a force multiplier for our scientific community.
WE’D LOVE TO MEET YOU IF
•You have a PhD in Machine learning with a track record of publications and industry experience
•A 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 10+ years of experience (commensurate with Principal level) in optimizing complex systems through automated algorithms, specifically within Ad Tech, Marketplaces, or related fields.
•Deep theoretical and technical expertise in optimization, control theory, or reinforcement learning applied to bidding and budget pacing.
•Expert knowledge of productionalizing 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.
OUR OFFER
•27 days of holiday a year to start for full-time employees (+1 day for every calendar year up to 30