Senior Applied Scientist - Lounge Recommendation and Search (all genders)

Lounge by Zalando is the leading online outlet in Europe, offering limited-time exclusive discounts on premium fashion and lifestyle brands. The Personal Relevance team at Lounge leverages data and advanced machine learning techniques to tailor customer experiences and communication.

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 and customer communication. Your work will create more personalized and engaging experiences for millions of customers across Europe, boosting customer satisfaction and loyalty.

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://corporate.zalando.com/en/diversity-inclusion

Our employee resource groups: https://corporate.zalando.com/en/diversity-inclusion/our-employee-resource-groups

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

• Develop and improve machine learning applications, such as personalized recommendation systems, to enhance our customers' browsing experience and communication.

• Translate ambiguous business challenges into research questions, contribute to defining solutions, and lead the end-to-end applied science strategy, including model selection, problem formulation, and approaches for training and inference. Develop and implement effective evaluation frameworks to assess the impact of initiatives, analyze customer behavior, and evaluate business performance.

• Collaborate with product managers, engineers, and other scientists to craft efficient and inspiring customer experience, while also contributing to cross-functional initiatives beyond your immediate team to drive broader organizational impact.

• Leverage high-quality data, a mature experimentation framework, our advanced ML infrastructure, and access to world-class expertise in diverse fields such as generative AI, image processing, and NLP to quickly bring your ideas to production while rigorously measuring their impact.

• Contribute to our research efforts through internal peer reviews and external publications in top-tier journals and conferences.

WE'D LOVE TO MEET YOU IF:

• Strong expertise in recommendation systems, search, information retrieval (IR), or closely related fields, with at least 3 years of hands-on industry experience building and deploying scalable, high-performance recommendation or search solutions.

• At least 2 years of significant engineering experience in compiled languages such as Java, Scala, C++, Rust, Golang, C etc. (willingness to occasionally work in Java is required). 

• Excellent knowledge of machine learning and statistics with a strong track record in addressing real-world problems through empirical science, particularly online A/B testing.

• The ability to analyze business problems and partner with Product Managers and Engineers to turn customer needs into effective research and development plans as well as technical solutions.

• Extensive hands-on experience with key recommender system techniques like deep learning, gradient boosting trees, LLMs, vector search etc., preferably using libraries like PyTorch, TensorFlow, CatBoost, Lucene, FAISS etc. 

• Practical experience with large-scale data processing and deploying machine learning models to production, especially for real-time APIs (Databricks, Spark, Flink, Beam, Sagemaker, Kubernetes, REST APIs).

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

• Relocation assistance available (subject to prior agreement)

• 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.

Our values https://jobs.zalando.com/en/our-culture

do.More - our sustainability strategy https://corporate.zalando.com/en/sustainability

Follow us on Instagram instagram.com/insidezalando

Please note that all applications must be completed using the online form - we do not accept applications via email.