Head of Applied Science & Engineering - Ranking

Head of Applied Science & Engineering – Ranking About the Role

We are looking for a Head of Applied Science to lead the scientific strategy and execution for Ranking across Europe’s largest fashion & lifestyle platform. This leader will define the long-term vision for Ranking relevance and visibility, leveraging machine learning, AI, and experimentation to help millions of customers find the right products quickly and confidently. You will lead a team of applied scientists driving the core ranking platform across Zalando’s discovery surfaces.

Partnering with Product, Engineering, Analytics, and Design, you will shape cross-surface experiences by balancing customer relevance, commercial steering governance, and marketplace health in line with Zalando's Platform-First strategy.

At Zalando, our vision is to be the leading pan-European ecosystem for fashion and lifestyle e-commerce – one that thrives on diversity and is truly inclusive by design. We believe that diverse teams fuel innovation and creativity, and we actively seek out talent from all backgrounds. We actively seek to reduce bias in our hiring and employment processes, focusing on your qualifications, skills, and contributions.

To support this, we kindly ask that you refrain from including personal details such as your photo, age, or marital status in your CV, ensuring a fair and equitable evaluation based solely on your abilities and potential. We are committed to providing an exceptional and accessible candidate experience for everyone. If you require any accommodations to support you throughout the hiring process, please let us know – we are here to assist you.

Discover more about our commitment to creating a diverse and inclusive workplace:

• Define and drive the long-term Applied Science strategy, aligning roadmap investments with customer needs and business priorities.
• Lead the development of advanced ML models for retrieval, ranking, and personalization to improve product ranking and discovery.
• Build and inspire a high-performing team of Applied Scientists, fostering a culture of scientific rigor, mentorship, and continuous learning.
• Optimize for business outcomes by balancing relevance, diversity, monetization, and operational efficiency.
• Accelerate innovation by investing in scalable machine learning platforms, data infrastructure, and experimentation frameworks.
• Establish best practices for model governance, offline evaluation, online experimentation, and standardized scientific methods across teams.
• Drive adoption of emerging AI/ML techniques, ensuring the organization stays at the forefront of technological advancements.
• Collaborate cross-functionally with Product, Engineering, UX, and leadership to define priorities and influence the broader organizational strategy.

• Proven experience leading high-performing Applied Science or Machine Learning organizations.
• Track record of defining technical vision and delivering business impact through AI and machine learning.
• Ability to attract, develop, and retain exceptional scientific talent.
• Deep expertise in machine learning for ranking and recommender systems, particularly learning-to-rank and personalization.
• Strong understanding of experimentation, causal inference, statistical modeling, and evaluation methodologies.
• Experience deploying and operating large-scale ranking systems in production.
• Demonstrated ability to translate customer problems into scientific solutions that deliver measurable business impact.
• Experience balancing customer experience, operational considerations, and commercial objectives.
• Strong strategic thinking with the ability to prioritize long-term investments alongside near-term…