Senior Applied Scientist- Risk Management (all genders)

Zalando
Berlin
THE ROLE & THE TEAM

Zalando Payments is looking for a Senior Applied Scientist to join our team and help us advance our risk models. In this role, you'll be responsible for the full machine learning lifecycle, including deep data exploration, model development, deployment, and monitoring. While this position has a strong research component, we need someone with a production mindset who can also translate new findings into robust, real-time systems. Most importantly, you must have a passion for data. As fraud patterns are diverse and constantly changing, you'll be the one to find, understand, and leverage these patterns to protect our systems.

This position is located in the Risk Management Department, which is responsible for managing credit and fraud risk for Zalando's payments.

INCLUSIVE BY DESIGN

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!

At Zalando, our vision is to be the leading pan-European ecosystem for fashion and lifestyle e-commerce - one that thrives on diversity and is truly inclusive by design. We believe that diverse teams fuel innovation and creativity, and we actively seek out talent from all backgrounds.

We actively seek to reduce bias in our hiring and employment processes, focusing on your qualifications, skills, and contributions. To support this, we kindly ask that you refrain from including personal details such as your photo, age, or marital status in your CV, ensuring a fair and equitable evaluation based solely on your abilities and potential.

We are committed to providing an exceptional and accessible candidate experience for everyone. If you require any accommodations to support you throughout the hiring process, please let us know - we are here to assist you.

Discover more about our commitment to creating a diverse and inclusive workplace:

WHAT WE'D LOVE YOU TO DO (AND LOVE DOING)
  • You will be working in an interesting ML space, balancing the importance of blocking bad customers without hindering the experience for the good ones.
  • You will be working with diverse and interesting data sets (networks, financial data, customer history).
  • You will drive innovation and improve models through research, design and development of new ML features to create measurable business impact
  • You will develop and maintain scalable ML pipelines.
  • Make a substantial financial impact on Zalando's business.
  • Engage with the wider applied science community at Zalando
WE'D LOVE TO MEET YOU IF
  • You have a passion for researching and exploring new machine learning methods and data sources to improve model performance.
  • You have hands-on experience in productionizing ML algorithms, from data collection and model development to deployment and monitoring.
  • You are a collaborative team player who thrives in a cross-functional environment, working with applied scientists, software engineers, and product managers to deliver business results.
  • You deal well with ambiguity and have a pragmatic approach to problem-solving.
  • You are proficient in Python and have experience processing large-scale datasets using frameworks like Apache Spark.
  • Experience in payments, risk, or fraud is a plus. We are looking for an applied scientist who recognizes that domain knowledge and business acumen are just as critical as technical skills for building effective and impactful solutions.
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!

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.
  • 27 days of holiday a year to start for full-time employees
  • 2 paid volunteering days a year
  • Hybrid working model with up to 60% 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
  • Employee shares program
  • 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 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
Veröffentlicht am 2025-12-24

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