INCLUSIVE BY DESIGN

At Zalando, our vision is to be inclusive by design. And this vision starts with our hiring - we do not discriminate on the basis of gender identity, sexual orientation, personal expression, ethnicity, religious belief, or disability status. You are welcome to leave out your picture, age, or marital status from your application. We only assess candidates on their qualifications and merit. ​
We want to provide you with a great candidate experience. Feel free to inform us of any accommodations you may need, so we can best support you throughout the hiring process.
do.BETTER - our diversity & inclusion strategy: https://corporate.zalando.com/en/our-impact/dobetter-our-diversity-and-inclusion-strategy
Our employee resource groups: https://corporate.zalando.com/en/our-impact/our-employee-resource-groups

ABOUT THE ROLE AND THE TEAM

Focused on measuring true business impact, this pivotal role leads the strategy and execution of causality-driven experimentation (primarily Brand/Conversion Lift studies and advanced A/B tests), employing advanced analytical and statistical methods to isolate the incremental effect of digital media.
This person will work closely with Digital Media, Marketing Analytics, and Measurement teams, applying scientific experimentation to inform budget allocation, optimization strategies, and creative performance. The ideal candidate will have a strong data science background, with expertise in marketing experiments, test-and-learn methodologies, and statistical analysis to validate the real business impact of media investments.
They will also ensure that insights from tests are accurate, statistically significant, and actionable, directly influencing our digital media planning and optimization.

WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)

1. Incrementality / Causal Experimentation
   Spearhead the strategy and execution of all digital media incrementality experiments (e.g., Brand and Conversion Lift studies, advanced A/B tests), ensuring they directly address critical questions on causal impact and efficiency.
   Define robust hypotheses, sophisticated experimental designs, precise KPIs, and the advanced statistical methodologies required to generate valid, actionable causal insights.
   Champion and embed best practices in causal inference, experimental design, and quantitative measurement, actively scouting and integrating cutting-edge data science innovations into our testing frameworks.
2. In-Depth Analysis & Strategic Insight
   Conduct rigorous statistical analysis of experiment outcomes to precisely quantify incremental lift in close collaboration with the media partners (e.g., on awareness, preference or consideration), determine statistical significance, and assess true business impact.
   Translate complex analytical findings into clear, compelling recommendations that differentiate causal impact from correlational observations, directly shaping media and targeting strategies and investment decisions.
   Develop and evolve testing frameworks for synthesizing learnings across multiple experiments, including meta-analysis and benchmarking, to build a cumulative knowledge base and drive continuous optimization.
3. Testing Roadmap & Governance
   Develop, prioritize, and manage a strategic roadmap for media experimentation, ensuring alignment with overarching business goals, learning agenda, and innovative testing opportunities.
   Establish and govern a comprehensive framework for the entire experimentation lifecycle, including test ideation, prioritization, rigorous design standards, execution oversight, and transparent knowledge sharing.
   Lead stakeholder education on the principles, methodologies, and strategic value of incrementality and causal measurement, fostering an evidence-based decision-making culture across the digital media team.