Senior Applied Scientist
vor 4 Wochen
Location
Berlin
Contract
Full time
Job Category
**THE ROLE AND THE TEAM**:
Lounge by Zalando is the leading online outlet in Europe, offering limited-time exclusive discounts on premium fashion and lifestyle brands. The Scalability team is optimising the assortment lifecycle with advanced machine learning and operations research techniques starting from the buying decisions until the moment when articles go online.
As a Senior Applied Scientist, you will drive our scientific roadmap, deliver cross-department projects, and work closely with Product Managers, Engineers and other Applied Scientists across Zalando to enhance Lounge's product discovery, research and development. Your contributions will drive more effective decision-making across the entire assortment management lifecycle, enhancing the scalability and accelerating the growth of the Lounge business.
**INCLUSIVE BY DESIGN**
**WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)**
- Conduct state-of-the-art research using machine learning and data science techniques to develop innovative solutions. Prototype and validate ML solutions using advanced algorithms and techniques, tailoring them to Zalando Lounge’s unique requirements.
- Build, train, and optimize machine learning models, focusing on interpretability, accuracy and scalability. Perform rigorous offline and online evaluation using appropriate metrics to validate performance and reliability.
- Partner with engineers to integrate ML models into production systems, ensuring seamless performance and monitoring.
- Work closely with cross-functional teams, including software engineers and business stakeholders, to ensure alignment and deliver impactful solutions.
**WE’D LOVE TO MEET YOU IF**:
- 3+ years of experience in applied machine learning, including end-to-end ML lifecycle ownership.
- You have strong programming skills in Python and are proficient with software engineering practices
- You have strong problem-solving skills, with the ability to simplify complex business challenges into actionable ML-based solutions.
- You have excellent understanding of data science concepts (regression, classification forecasting) and have used some libraries like scikit-learn, XGBoost, CatBoost, Facebook Prophet, statsmodels.tsa, Pytorch, Tensorflow. Strong track record in addressing real-world problems through empirical science, particularly online A/B testing is a plus.
- You have expertise in demand forecasting
- Expertise in statistical analysis, feature engineering, and handling large datasets using tools like Pandas, Polars, or Spark, SQL.
- Expertise in Casual Econometrics or Operations Research is a plus
**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 flexible hours and up to 60% remote
- Work from abroad for up to 30 working days a year
- 27 days of vacation a year to start
- Family services, including counselling and support
- Health and wellbeing options (including Gympass)
- Mental health support and coaching available
**ABOUT ZALANDO**
It’s the perfect time to join Zalando on our journey, from being a pioneer in the world of e-commerce, to the starting point for fashion in Europe. We connect customers, brands, and partners across 23 markets.
Help us drive digital and sustainable solutions for fashion, logistics, advertising and research, bringing head-to-toe fashion to more than 48 million active customers through a team of diverse skill-sets, cultural backgrounds, and interests.
**Recruiter**
Karolina Miernik
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.
Wenn du Fragen zu unserem Rekrutierungsprozess hast, wirf bitte einen Blick auf unsere FAQ-Seite.
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