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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 dev…
Skills: Causal Inference, Experimentation, Machine Learning, Econometrics, Python
Berlin, Germany · On-site
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Berlin, Germany · On-site
Chat Bewerbung » Ort: 12459 Berlin / Oberschöneweide, Rummelsburger Str. 16 | Vertragsart: Teilzeit, 20 Std./Woche, unbefristet | Job-ID: 966022 Du begeisterst dich für den Einzelhandel und suchst nach einem abwechslungs…
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Berlin, Germany · On-site
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Berlin, Germany · On-site
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Berlin, Germany · On-site
$80k–$120k/yr
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Berlin, Germany · On-site
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Berlin, Germany · On-site
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Berlin, Germany · On-site
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Lead impact measurement for ASDI products by designing experiments and observational studies to evaluate the effect of algorithmic and policy changes. Develop machine learning and econometric models to optimize recommendations and communicate findings to stakeholders to shape product decisions.
Requires a PhD in Economics, Statistics, or a related field with at least 2 years of industry experience in causal inference and experimentation. Proficiency in Python, SQL, and big data platforms like Spark or Databricks is essential.
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!
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
Welcome to Zalando. Here’s some key info about us: Our position and vision: - We’re Europe’s leading online platform for fashion and lifestyle. - Founded in Berlin in 2008, we bring head-to-toe fashion to more than 50 million active customers in 25 markets; offering clothes, footwear, accessories, and beauty. - We're building the ecosystem for fashion and lifestyle ecommerce. Our offering: - Our assortment of international brands ranges from world-famous names to local labels - Our platform is a one-stop fashion destination for inspiration, innovation, and interaction - As Europe’s most fashionable tech company, we work hard to find digital solutions for every aspect of the fashion journey: for our customers, partners, and friends of our brand. - Our logistics network with 12 centrally located fulfillment centers allows us to efficiently serve our customers throughout Europe, supported by warehouses in Italy, France, Poland, and Sweden with a focus on local customer needs. Our beliefs: - Our ambition is to combine our passion for self-expression through fashion with our unwavering commitments to sustainability and D&I - We promote an inclusive corporate culture that welcomes different perspectives and brings together people from diverse backgrounds. We want to ensure a non-discriminatory and supportive working environment for each of our employees to thrive. It’s a journey that all teams are on together, centered around the values we uphold. - We believe that our integration of fashion, operations, and online technology gives us the capability to deliver a compelling value proposition to both our customers and fashion brand partners.
Offices: Valeska-Gert-Straße 5, Berlin, Berlin 10243, DE · Tamara-Danz-Str. 1, Berlin, Berlin 10243, DE · Vorsetzen 35, Hamburg, 20459, DE · 3 Grand Canal Quay, Grand Canal Dock, Dublin, Dublin D02 WC65, IE · Runeberginkatu 5 B, Helsinki, Uusimaa 00100, FI
