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Zalando

Online fashion retail marketplace and logistics

Head of Applied Science Growth & Lifecycle

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeBerlin, GermanyIn-person

About the Job

Requirements

  • A strong track record of leading applied science or machine-learning teams, hiring and developing scientific talent, and delivering impact through others.
  • Deep expertise in machine learning, statistics, and experimentation, with strong experience in at least one of causal inference, marketing science, personalisation, or optimisation.
  • Experience critically assessing research and determining when sophisticated models are justified versus simpler solutions.
  • Experience leading development and deployment of models or algorithmic decision systems in a commercial environment, including data quality, reproducibility, offline-to-online evaluation, model drift, and operational trade-offs of machine learning at scale.
  • Ability to demonstrate how scientific work changed customer or business outcomes, design experiments, reason about confounding and uncertainty, and make investment decisions with incomplete evidence.
  • Ability to translate acquisition, activation, retention, and customer lifetime value challenges into scientific problems.
  • Ability to communicate complex scientific ideas clearly in English, influence senior stakeholders, and build partnerships across disciplines.
  • PhD or Master's degree in a relevant quantitative discipline, or equivalent applied research experience.

Responsibilities

  • Define and drive a coherent research and machine-learning strategy for Growth & Lifecycle, balancing longer-term scientific advances with near-term customer and commercial impact and prioritising problems where modelling, experimentation, or optimisation can outperform simpler approaches.
  • Hire, coach, and develop applied scientists and scientific leaders; set expectations for scientific craft and career progression; provide technical mentorship; and build a culture of rigorous peer review, reproducible research, and shared learning.
  • Guide problem formulation, method selection, and model design across lifetime value prediction, causal inference, uplift modelling, personalisation, and decision optimisation; challenge assumptions, review experimental designs and results, and help teams resolve scientific trade-offs.
  • Own the scientific lifecycle from hypothesis and baselines through offline evaluation, online experimentation, and ongoing model improvement; partner with Engineering on deployment, monitoring, and retraining, setting standards for model quality, latency, cost, and maintainability.
  • Establish how scientific advances affect acquisition efficiency, activation, retention, and customer lifetime value; use controlled experiments and causal methods to distinguish incremental value from correlation and make scale, iterate, or stop decisions based on evidence.
  • Identify where AI and machine learning, including agentic approaches, can improve marketing and lifecycle decisions; evaluate methods against baselines and establish safeguards for privacy, bias, customer experience, and human oversight before scaling.
  • Partner with Product, Engineering, Analytics, and Marketing to turn scientific opportunities into shared priorities; communicate uncertainty, evidence, and investment trade-offs to senior leaders; and connect the team's work with relevant scientific expertise across Zalando.

Desired Qualifications

  • Experience in consumer marketplaces, e-commerce, subscriptions, or another high-volume consumer setting.
  • Familiarity with customer relationship management and marketing platforms.
  • A record of impactful research, publications, patents, or open-source contributions.
  • Off-price or fashion domain knowledge.

About the Company

Zalando

Online fashion retail marketplace and logistics

Zalando operates as a European online marketplace for fashion and lifestyle items, selling clothing, shoes, and accessories directly to consumers and earning commissions from third-party sellers (plus Zalando Plus). Shoppers use its website or app to browse brands, and Zalando handles order processing and logistics, offering free delivery and free returns along with personalized recommendations and optional faster shipping for Plus members. It differentiates itself by combining direct sales with a large marketplace across 25 European markets, delivering a wide product range with strong logistics and a seamless shopping experience. Its goal is to remain a leading European online fashion retailer by connecting customers with many brands and improving convenience and services through technology and premium options.

Company size
10,001+
Company stage
IPO
Headquarters
Berlin, Germany
Founded
2008

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