(Senior) Data Scientist - Online Shop Area
Role details
Job location
Tech stack
Job description
As a Data Scientist, you are part of the Analytics & Data Science team in our online shop. You work closely with product teams to improve real-time homepage recommendations and build models for editorial content, shaping how customers discover and engage with content across the platform., Deliver robust machine learning solutions by collaborating closely with product teams to bring them into production and maintaining them on our platform. Kernaufgabe
Drive user engagement by optimizing existing and building new recommender systems for different content types, such as editorial content, community, etc. Kernaufgabe
Ensure continuous improvement of our recommender systems by generating and clearly communicating insights from the analysis of interaction data of millions of users. Kernaufgabe
Validate the impact of improvements by defining success criteria and analytical frameworks together with product and analytics teams. Kernaufgabe
Shape impactful machine learning strategies by aligning product goals with data science solutions in close collaboration with the product team
Requirements
Do you have experience in SQL?, Higher education in data science or a related field, with at least 3 years of experience, including hands-on work on recommender systems. Zwingend
Advanced Python proficiency, with experience using machine learning libraries such as PyTorch, TensorFlow, and scikit-learn. Zwingend
Ability to work with large-scale datasets, including advanced knowledge of SQL and database systems (e.g. BigQuery) to analyze user interactions and derive insights. Zwingend
Experience with MLOps, including deploying and operating machine learning models in production, using orchestration tools such as Airflow. Zwingend
Solid understanding of statistics and experimentation, including defining success criteria and analytical frameworks. Zwingend
Strong communication skills and a proactive, ownership-driven mindset, enabling effective collaboration with product and cross-functional teams.