Senior Applied Scientist (all genders)
THE ROLE & THE TEAM
Partner Tech builds the products, tools, and insights that help Zalando partners grow with confidence. Within Assortment, Steering & Data Insights (ASDI), we develop data products and decision systems that improve assortment composition, in-season steering, demand understanding, partner performance insights, and commercial automation across our wholesale and Partner Platform businesses.
As a Senior Applied Scientist, you will focus primarily on measuring the impact of ASDI products while also supporting selected strategic Partner Tech-wide initiatives where rigorous evaluation is critical. You will design experiments where possible and robust observational studies where they are not, helping us understand the incremental effect of product, algorithmic, and policy changes on outcomes such as GMV, profitability, and operational efficiency. Working closely with Product, Engineering, Analytics, Applied Science and business stakeholders, you will turn ambiguous questions into clear evaluation strategies, reliable evidence, and better product decisions.
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. We only want to know why you’re great for this role, so please avoid including your picture, age, and marital status in your CV as well.
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
Lead impact measurement for ASDI products and strategic Partner Tech initiatives. You will own the experimentation charter and work with cross-functional teams to define hypotheses, estimands, guardrails, and success metrics for initiatives in ASDI and broader high-priority Partner Tech topics.
Develop state-of-the-art machine learning and econometric models. You will design and develop models for observational studies to estimate the incremental effect of products, algorithmic, and recommendations across the product area thereby optimizing our recommendations and products.
Choose the right causal design for the question. You will use randomized experiments where feasible and quasi-experimental methods when they are not, balancing scientific rigor with practical constraints.
Translate evidence into decisions. You will communicate findings, uncertainty, and trade-offs clearly to technical and non-technical audiences, helping shape rollouts, prioritization, and investment choices.
Build trusted, extensible KPI frameworks : You will design and develop robust and extensible KPI frameworks to enable evaluation and prioritization of multiple products in the domain
Raise the bar for measurement in ASDI. You will empower the team to stay up-to-date with the latest research in relevant fields like causal machine learning, econometrics, and optimization. You will help define best practices for experimentation and observational causal inference, support peer reviews, and mentor colleagues.
You hold a PhD in Economics, Econometrics, Statistics,Causal Inference or Causal Machine Learning
You have at least 2 years of industry experience in data science with a focus on experimentation and causal inference, and have used these methods to evaluate products, algorithms, recommendations, or interventions in complex, data-rich environments.
You bring deep expertise in experimentation and causal inference, including panel data methods, causal inference under unconfoundedness, doubly robust methods
You can independently drive a scientific workstream by developing an applied research agenda, and translate research into actionable insights at scale
You code fluently in Python and SQL and are comfortable working with large datasets and modern analytical platforms such as Spark or Databricks.
You communicate clearly to diverse audiences, connect scientific insights to business impact, and help others do stronger work through mentoring, peer review, or knowledge sharing.
If you think you have what it takes, we encourage you to apply even if you don't meet every single requirement. You may just be the right candidate for this or other roles!
OUR OFFER
Zalando provides a range of benefits, here’s an overview of what you can expect. Ask your Talent Acquisition Partner to learn more about what we offer.
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
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 (subject to prior agreement)
Family services, including counselling 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
Nach der Prüfung werden unsere Recruiter*innen über eine offizielle Zalando E-Mail-Adresse (@zalando.de) Kontakt aufnehmen.
In einigen Fällen arbeiten wir auch mit einer Auswahl von Headhunter*innen und Agenturen zusammen, um bestimmte Positionen zu besetzen. Bitte beachte, dass weder Zalando noch unsere Rekrutierungspartner*innen irgendeine Art von Bezahlung verlangen, um sich für eine Stelle zu bewerben oder an einem Vorstellungsgespräch teilzunehmen.
