Junior Applied Scientist (all genders) - B2B Data Science and Algorithms
The ZEOS department is responsible for all partner-facing Zalando Logistics Solutions. We provide a holistic approach to delivering the fulfillment solutions that meet our partner’s needs by unifying these services under a single umbrella. We aim to provide our partners with a profitable fulfillment experience, and we see that to do this, Machine Learning, Operations Research, and data-driven solutions will play a pivotal role.
We are seeking a highly motivated Junior Applied Scientist who is fueled by the desire to kickstart their career by building innovative and impactful ML/Optimization systems for our B2B logistics partners. You will join an established team of Senior Applied Scientists and Machine Learning Engineers, working in a cross-functional setup with Product Managers, Data Engineers, and Software Engineers.
The team’s focus is helping our B2B partners improve inventory health and order fulfillment efficiency. With guidance and mentorship from senior team members, you will contribute to building various ML/DL forecasting models (demand, returns, lead-times), stochastic inventory optimization solutions, recommendation services, and emerging Agentic AI systems. You will play a key role in a cross-functional team where your eagerness to learn and grow will directly translate into value for our partners!
WHY YOU SHOULD BE INTERESTED…
Learn and Impact from Day One: You won't be stuck doing busywork. You will be an active scientific partner, working alongside experienced scientists and product teams to define problems and build solutions. Your fresh perspective will help identify new opportunities to create value for our partners.
Tackle Complex Scientific Problems with Expert Guidance: This is your chance to bridge the gap between academia and industry. You'll tackle cutting-edge challenges in stochastic inventory optimization, multi-echelon demand forecasting, and recommender systems while receiving the mentorship needed to succeed.
Explore Emerging Tech like Agentic AI: As we explore opening up MCP servers to our partners, you will assist in defining how we measure their performance. You will contribute to implementing evaluation frameworks (e.g., LLM-as-a-judge, safety guardrails) to ensure autonomous systems act reliably.
Grow into End-to-End Ownership: You will have the opportunity to follow ideas from initial research and prototyping to production. You will learn how to define success metrics, collaborate with engineers to deploy scalable services, and monitor real-world impact on partner KPIs.
Drive Impact at a Multi-Merchant Scale: Your contributions will help build platform-level services that scale across hundreds of diverse partners, shaping the future of a more sustainable and efficient e-commerce logistics network.
WE’D LOVE TO MEET YOU IF…
Educational background in a quantitative field; Masters degree or higher preferred.
Up to 2 years of hands-on experience (including internships, working student roles, or significant academic/thesis projects) applying scientific methods to solve complex problems.
A solid theoretical foundation and practical exposure in at least one of the following areas:
Machine Learning or Deep Learning for time-series forecasting (e.g., LGBM, ARIMA, Prophet, Transformers).
Operations Research and Optimization (e.g., stochastic inventory models, linear/integer programming, Monte Carlo simulations).
Machine Learning Engineering basics (e.g., understanding of git, batch processing, basic software testing).
Agentic AI & MCP evaluation frameworks
Proficiency in SQL and Python, with some exposure to working with datasets.
Strong communication skills with the ability to explain scientific concepts clearly and a desire to learn how to communicate effectively with business stakeholders.
A collaborative, growth-oriented mindset. You have a passion for learning by doing and are not afraid to ask questions.
You thrive in our team's core value: “High Challenge, High Support”! We cherish an open, direct feedback culture and are here to help you develop into a world-class scientist.
INCLUSIVE BY DESIGN
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
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 Lounge by Zalando, discounts from external partners
2 paid volunteering days per year
27 days of vacation a year to start for full-time employees
Family services, including counseling 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.
