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THE ROLE & THE TEAM

One of the main drivers for conversion in online retail is the delivery promise, informing fashion customers about when they can expect their shipment to arrive. Our team owns the forecasting of processing times for all the paths in the complex fulfillment network on which this delivery promise is based. Improving the precision of these predictions has a huge impact on customer satisfaction, allows better fulfillment planning, and enables the business to make better-informed tradeoff decisions.

Our team is composed of applied scientists and software engineers. As an applied scientist, you’ll design, train, extend, and continuously improve forecasting models based on features extracted from diverse datasets produced by high-throughput systems. You’ll do so in close collaboration with the software engineers in your team, who are responsible for building best in class services and infrastructure for experimentation and applying these models in production. A significant part of your role will be to research new opportunities and work closely with stakeholders to understand the underlying business processes and model them in the best possible way to feed into our models.

If you have a passion for creating forecasting models at scale and solving complex problems, we want to hear from you. This is a unique opportunity to make a real impact and help drive the success of our business.

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

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

Contribute to modeling, solving, and implementing forecasting models within our research-driven software framework to cater for the increasing scale and load and novel use cases. Constantly question the model and the algorithms we use and seek for a constant improvement.
Act as a technical lead and mentor for mid-level Applied Scientists, providing guidance on experimental design, code quality, and scientific excellence.
Design, implement, and maintain automated pipelines covering data ingestion, feature engineering, model training, and evaluation to ensure high reliability and scalability of our machine learning systems.
Involve yourself in our ongoing research roadmap to discover future opportunities.
Set the standard for the entire development cycle, including requirement engineering based on deep domain & business understanding, prototyping, implementing production software, as well as testing and operating the highly available production system.
Collaborate closely with our software engineers to mutually influence and understand system constraints and opportunities, and take part in shaping the future of our system.
Think abstractly and discover correlations between problems, methodologies, and solutions.
Contribute to the design, implementation and evaluation of A/B tests that help us measure impact, shape our roadmap and identify opportunities
Join the Zalando community of fellow researchers, exchange ideas, connect and provide your contributions
Promote and support an inclusive culture and diverse team, fostering a positive and productive work environment for all team members.

WE’D LOVE TO MEET YOU IF

You have an academic background in machine learning, statistics, operations research or related fields, and can apply the knowledge effectively
You have substantial experience (ideally 3+ years) discovering, building, evaluating and operating prediction models in production at scale.
You have experience with data processing frameworks such as PySpark or Pandas as well as Machine Learning libraries such as Scikit-Learn, XGBoost, LightGBM, PyTorch or Tensorflow. Previous experience with Databricks is not mandatory but appreciated.
You prefer simple solutions over complex ones but at the same time, you are aware that complex problems sometimes require advanced algorithms.

You’re excited about working in a setup that requires a deep domain understanding (e.g., how our fulfillment processes works).
You are a team player who thrives in an international, agile and cross-functional environment, and is passionate about fostering a positive and productive work environment.
You are fluent in English.

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.
Employee shares program
40% off fashion and beauty products sold and shipped by Zalando, 30% off Zalando Lounge, discounts from external partners
2 paid volunteering days a year
Hybrid working model with 60% (or more) remote per week, actual practice is up to each team to best support their collaboration
Work from abroad for up to 30 working days a year
27 days of vacation a year to start
Relocation assistance available (subject to prior agreement)
Family services, including counseling and support
Health and wellbeing options (including Gympass)
Mental health support and coaching available
Drive your development through our training platform and biannual peer-to-peer review. You'll also receive full access to an O'Reilly online learning subscription
Learn all about Zalando and our values here: https://jobs.zalando.com/en/?gh_src=22377bdd1us

","datePosted":"2026-07-29T00:00:00.000Z","validThrough":"2026-08-28T00:00:00.000Z","employmentType":"FULL_TIME","hiringOrganization":{"@type":"Organization","name":"Zalando"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dortmund","addressCountry":"DE"}},"identifier":{"@type":"PropertyValue","name":"Zalando","value":"workday_zalando_2724018"},"directApply":false,"url":"https://zalando.wd3.myworkdayjobs.com/ZalandoSiteWD/job/Dortmund/Senior-Applied-Scientist---Network-Behaviour--all-genders-_2724018-1"},{"@context":"https://schema.org","@type":"JobPosting","title":"PhD candidate (f/m/d)","description":"The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early diagnosis, and therapy of diseases like cardiovascular diseases or cancer. Overall, the institute strives to advance precision medicine by combining knowledge from different fields such as biology, chemistry, computer science, medicine, pharmacology, and physics. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states.\n\nWe invite applications for the Research Group Biofluorescence: **PhD candidate (f/m/d)**\n\nThis project, funded by the DFG as part of CRC 1752, \"DYNAMO: Immediate Tumor Dynamics in Melanoma Therapy“ (https://www.uni-due.de/crc1752/) seeks to combine high-resolution multi-omics profiling, advanced computational modeling, and clinically aligned biomarker stratification, in order to generate actionable, patient-specific predictions and resistance-targeting interventions in melanoma therapy. You will be responsible for finding out the role of neutrophils for the early development of therapy resistance in human melanoma. The project is being carried out in collaboration with University Hospital Essen and the University of Duisburg-Essen.\n\n### You will be responsible for\n\n- Experimental setup and execution of neutrophil functional profiling in the context of melanoma immune regulation and immune checkpoint inhibitor (ICI) response\n- Functional assays of neutrophils including migration, phagocytosis, and ROS production\n- Optimization and standardization of neutrophil functional assays for primary human samples\n- Few-cell proteomics for deep molecular characterization of neutrophil subsets\n- Multicolor flow cytometry of PBMCs and immune cell populations\n- Live-cell imaging and advanced microscopy for dynamic immune cell behavior analysis\n- Planning and execution of stimulation and inhibition experiments to dissect signaling pathways regulating neutrophil function in the melanoma context\n- Data processing, analysis, interpretation, and visualization of experimental results in collaboration with computational partners\n\n### Your profile\n\n- Completed diploma or master’s degree in molecular biology, cancer biology, immunology, cell biology, bioinformatics, translational medicine or related disciplines\n- Experience in molecular and cellular biology techniques, ideally with hands-on experience with functional immune cell assays (preferably with neutrophils or myeloid cells) is an advantage\n- Strong interest in melanoma biology, tumor immunology, immune checkpoint therapy, translational cancer research, and tumor–immune interactions\n- Experience with cell culture, flow cytometry, microscopy, proteomics workflows or high-dimensional immune profiling approaches is desirable\n- Experience with bioinformatics or biostatistics is beneficial but not required\n- Ability to work independently and in interdisciplinary teams, with strong organizational skills and analytical thinking\n- High level of self-motivation, scientific curiosity, reliability, creativity, and team-oriented personality with enthusiasm to work in a collaborative research environment\n- Fluent in spoken and written English\n\n### We offer\n\n- A clear research topic as well as multifold training and support for PhD students in framework of ISAS and the Leibniz association\n- Opportunities for scientific training and development in an international environment and an excellent working atmosphere in a very dynamic and professional team\n- Access to state-of-the-art technologies including few-cell proteomics, high-dimensional flow cytometry, and advanced microscopy platforms\n- Integration into an interdisciplinary, internationally visible, translation-oriented cancer immunology research network\n- The opportunity to present your data on international conferences and participate in workshops\n- A wide range of opportunities for further training and qualifications\n- Flexible working times, mobile working and attractive social benefits\n- Family-friendly infrastructure and support from a family service\n\nNon-residents who apply for this job will receive help from the institute to find accommodation and to handle authorities. Applications from disabled applicants are welcome. ISAS supports the principle of equal opportunity for all employees and therefore particularly encourages women to apply.\n\nThe part-time position (65%) starts on October 1, 2026, and is offered until June 30, 2030. The salary will be according to the German TV-L and falls within the pay group 13. The time limitation of the contract is based on the Wissenschaftszeitvertragsgesetz (WissZeitVG).\n\nISAS collects and processes the personal data of its applicants in accordance with European and German legal regulations. Further information on data protection and the processing of personal data can be found at: https://www.isas.de/en/datenschutz.\n\nThe closing date for applications is** August 14, 2026**. Please apply via our [applicant portal](https://bewerbermanagement.net/en/jobposting/4e342c0b4ebdda805ec07aefc033c1e6bce0d9010/apply?ref=Agentur+f%C3%BCr+Arbeit+Dortmund). If you have any questions (**reference number 411\\_2026**), feel free to contact the Human Resources team (bewerbungen@isas.de). Further information about the institute can be found at: https://www.isas.de/en.","datePosted":"2026-07-15T00:00:00.000Z","validThrough":"2026-08-14T00:00:00.000Z","employmentType":"FULL_TIME","hiringOrganization":{"@type":"Organization","name":"Leibniz-Institut f.Analytische Wissenschaften -ISAS- e.V."},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dortmund","addressCountry":"DE"}},"identifier":{"@type":"PropertyValue","name":"Leibniz-Institut f.Analytische Wissenschaften -ISAS- e.V.","value":"ba_10000-1207198193-S"},"directApply":false,"url":"https://www.arbeitsagentur.de/jobsuche/jobdetail/10000-1207198193-S"}]

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Senior Applied Scientist - Network Behaviour

PhD candidate