At Zalando, our vision is to be the Starting Point for Fashion. We want to offer a shopping experience that is characterized by trust, for our more than 50 million customers in 25 markets across Europe, and also for our +6,500 partner brands. To maintain this trust, it is vital for us to manage transactional risks that originate from abusive behaviors on our fashion platform. With 3.3 million shopping items, resulting in hundreds of thousands of orders every single day, we use big data and advanced methods from machine learning to predict and mitigate such risks and ensure trustful relationships with our customers and partners.
As a full-stack applied scientist in our Transactions Risk Management department you will have the opportunity to join a dynamic and diverse group of 15-20 scientists and engineers. As an analytics team, we are responsible for several predictive services running in Java, Python, AWS, and Kubernetes to safeguard other teams in the checkout domain at Zalando. As part of our team, you will have the chance to work on cutting edge projects, raise the technical bar, improve our operational excellence, and shape our ways of working.
What you build and put in production is impacting not only every single Zalando customer on the spot, but also the performance of Zalando and its partners.
WHERE YOUR EXPERTISE IS NEEDED
Lead the applied science work across two teams in the Transactions Risk Management department, involving the research strategy, roadmap, and projects
Take end-to-end ownership for developing, deploying, and operating machine learning solutions on our centralized abuse protection platform for detecting and managing transactional risks
Raise the analytical and technical bar within the applied science domain by improving processes and documentation
Quick prototyping and spiking of machine learning models to assess their applicability for solving research, customer, and business problems
Tackle challenges for developing algorithms and running them efficiently on resource constrained platforms
Rigorous approach in solving, conducting, and documenting research projects
Work in a cross functional team consisting of software applied scientists, engineers, product managers, and product analysts
Be an influential and empathetic leader and mentor for our applied scientist to help growing their expertise and curiosity in science and risk management topics
Contribute to our growing science community and encourage knowledge sharing in an agile work environment
WHAT WE’RE LOOKING FOR
Solid hands-on experience as an applied scientist, developing and productionizing machine / deep learning models in cloud environments (preferably AWS)
Good proficiency in Python and related machine / deep learning frameworks, such as Pytorch, Tensorflow, Keras, etc.
Expertise in machine learning infrastructure and tooling, such as Databricks, Spark, Flink, relational databases, AWS SageMaker, S3, EC2, Step Functions, Git
Experience with data storage, ingestion, and transformation, also including machine learning workflow orchestration
Passion for developing clean, well maintainable, and testable code
Motivation for continued personal development in discovering new technologies and software services
Curiosity and eagerness to understand the business context where the team operates and the customer problems being solved
Very good communication skills to translate (even complex) analytical / engineering decisions and outcomes to broader, non-technical audience
Preferred
Previous knowledge in working with un-/weak-labeled data (self-supervised models, synthetic label generation, anomaly detection)
Experience in designing, developing, and operating highly-scalable microservices on a distributed system
Knowledge in automated deployment and monitoring through CI/CD pipeline (Docker, Kubernetes, or similar)
Work experience with a high level of test automation (unit, component, integration)
Running and evaluating experimental machine learning deployments (canary, blue-green)
PERKS AT WORK
Culture of trust, empowerment and constructive feedback, open source commitment, meetups, game nights, 70+ internal technical and fun guilds, knowledge sharing through tech talks, internal tech academy and blogs, product demos, parties & events
Competitive salary, employee share shop, 40% Zalando shopping discount, discounts from external partners, centrally located offices, public transport discounts, municipality services, great IT equipment, flexible working times, additional holidays and volunteering time off, free beverages and fruits, diverse sports and health offerings
Extensive on-boarding, mentoring and personal development opportunities and an international team of experts
Relocation assistance for internationals, PME family service and parent & child rooms* (*available only in selected locations)
We celebrate diversity and are committed to building teams that represent a variety of backgrounds, perspectives and skills. All employment is decided on the basis of qualifications, merit and business need.
ABOUT ZALANDO
Zalando is Europe’s leading online platform for fashion and lifestyle, connecting customers, brands and partners across 28 markets. We drive digital solutions for fashion, logistics, advertising and research, bringing head-to-toe fashion to about 45 million active customers through diverse skill-sets, interests and languages our teams choose to use.
Please note that all applications must be completed using the online form - we do not accept applications via email.
