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About the Role
As a Senior Applied Scientist within Assortment, Steering & Data Insights (ASDI), you will focus on measuring the impact of ASDI products and supporting strategic Partner Tech initiatives. You will design experiments and observational studies to understand the incremental effect of product, algorithmic, and policy changes on key business outcomes. Collaborating with various stakeholders, you will translate ambiguous questions into clear evaluation strategies, reliable evidence, and improved product decisions.
Responsibilities
- Lead impact measurement for ASDI products and strategic Partner Tech initiatives.
- Own the experimentation charter and collaborate with cross-functional teams to define hypotheses, estimands, guardrails, and success metrics.
- Design and develop state-of-the-art machine learning and econometric models for observational studies.
- Estimate the incremental effect of products, algorithms, and recommendations to optimize them.
- Utilize randomized experiments and quasi-experimental methods, balancing scientific rigor with practical constraints.
- Communicate findings, uncertainty, and trade-offs clearly to technical and non-technical audiences.
- Shape rollouts, prioritization, and investment choices based on evidence.
- Design and develop robust and extensible KPI frameworks for product evaluation and prioritization.
- Empower the team by staying updated on the latest research in causal machine learning, econometrics, and optimization.
- Define best practices for experimentation and observational causal inference.
- Support peer reviews and mentor colleagues.
Requirements
- PhD in Economics, Econometrics, Statistics, Causal Inference, or Causal Machine Learning.
- At least 2 years of industry experience in data science with a focus on experimentation and causal inference.
- Experience evaluating products, algorithms, recommendations, or interventions in complex, data-rich environments using experimentation and causal inference methods.
- Deep expertise in experimentation and causal inference, including panel data methods, causal inference under unconfoundedness, and doubly robust methods.
- Ability to independently drive a scientific workstream by developing an applied research agenda.
- Ability to translate research into actionable insights at scale.
- Fluent coding skills in Python and SQL.
- Comfort working with large datasets and modern analytical platforms such as Spark or Databricks.
- Clear communication skills for diverse audiences.
- Ability to connect scientific insights to business impact.
- Experience helping others do stronger work through mentoring, peer review, or knowledge sharing.
Skills
- Experimentation
- Causal Inference
- Machine Learning
- Econometrics
- Python
- SQL
- Spark
- Databricks
- Mentoring
- Peer Review
- Knowledge Sharing
Location
- Europe
Work Type
- Full-time
Experience Level
- Senior
Education Level
- PhD
Benefits
- 27 days of holiday a year (+1 day for every calendar year up to 30 days)
- 2 paid volunteering days a year
- Employee shares programme
- 40% off fashion and beauty products sold and shipped by Zalando
- 30% off Lounge by Zalando
- Discounts from external partners
- Relocation assistance available
- Family services, including counselling and support
- Health and wellbeing options (including Wellhub, formerly Gympass)
- Mental health support and coaching
- Training platform access
- Biannual peer-to-peer review
About the Company
- Zalando's vision is to be the leading pan-European ecosystem for fashion and lifestyle e-commerce.
- Partner Tech builds the products, tools, and insights that help Zalando partners grow with confidence.
- Assortment, Steering & Data Insights (ASDI) develops data products and decision systems that improve assortment composition, in-season steering, demand understanding, partner performance insights, and commercial automation across wholesale and Partner Platform businesses.
Equal Opportunity
- At Zalando, our vision is to be the leading pan-European ecosystem for fashion and lifestyle e-commerce - one that is inclusive by design.
- We only assess candidates based on qualifications, merit, and business needs.
- We welcome applications from people of all gender identities, sexual orientations, personal expressions, racial identities, ethnicities, religious beliefs, and disability statuses.
- Please avoid including your picture, age, and marital status in your CV.
- We want to provide you with a great candidate experience. Please feel free to inform us of any accommodations you may need, so we can best support and assist you throughout the hiring process.
- do.BETTER - our diversity & inclusion strategy: https://jobs.zalando.com/en/our-culture/diversity-and-inclusion