Principal Applied Scientist - Zalando Marketing Services | Principal Applied Scientist - ZMS (all genders)
Zalando SE
Job Summary
As a Principal Applied Scientist at Zalando Marketing Services (ZMS), you will lead the scientific vision and execution for real-time bidding and allocation engines. This high-impact role involves developing sophisticated auction logic and machine learning models that process tens of thousands of requests per second with ultra-low latency. You will collaborate with cross-functional teams to translate complex business constraints into mathematical objective functions, advancing mechanisms in auction theory and mechanism design. The position is ideal for a scientific leader who enjoys balancing advertiser ROI with premium customer experiences through large-scale Bayesian inference and reinforcement learning. Beyond technical execution, you will act as a force multiplier by mentoring senior team members and driving the long-term scientific roadmap. This role offers a unique opportunity to work at the intersection of market dynamics and high-load engineering within one of Europe's leading e-commerce ecosystems, featuring a hybrid work model and a strong focus on diversity and inclusion.
Required Skills
Education
Not specified
Experience
- 7+ years of experience in optimizing complex systems through automated algorithms, specifically in Ad Tech or Marketplaces
- Proven track record of research excellence evidenced by peer-reviewed publications or equivalent industry impact
- Extensive experience productionalizing ML models within ultra-low latency constraints
- Professional experience in leading research and development for real-time bidding and allocation algorithms
- Leadership experience in mentoring and growing senior-level technical team members
Languages
Additional
- Candidates are requested to include peer-reviewed publications in relevant fields such as Computational Advertising or Game Theory in their application. Role requires expertise in high-load, low-latency environments and large-scale distributed systems.
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