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
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
WHY YOU SHOULD BE INTERESTED
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.
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
