Senior Principal Applied Scientist - ZMS (all genders)
8.0/10
Growth Content Creator
$140,000 – $210,000 USD
Remote
mid
about 2 hours ago
aitechMachine LearningOptimizationControl TheoryReinforcement LearningPython
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The vacancy is well-structured with clear responsibilities and requirements, though some details on compensation and company profile could improve clarity.
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Description
Responsibilities
- •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.
Conditions
- •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.
- •Hybrid working model with up to 60% remote per week.
- •Work from abroad for up to 30 working 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 counseling 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.
Requirements
Requirements
- •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.
- •At least 10+ years of experience 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.
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