(Junior) Data Scientist - Focus on Recommender Systems and Ranking | (Junior) Data Scientist (m/w/d) – Fokus auf Recommender Systems und Ranking-Probleme Mietwagen

CHECK24 Services Personal GmbH

Augsburg, Bayern, Bayern, Deutschland

Published Apr 2, 2026

Full-time

Permanent

Job Summary

As a (Junior) Data Scientist at CHECK24's car rental division in Augsburg, you will play a pivotal role in enhancing the user experience for over 20 million customers. Your day-to-day responsibilities involve developing, operating, and optimizing productive ranking and recommendation models that directly influence how search results are personalized for users. You will work within an agile environment, conducting A/B tests and integrating models into the existing system landscape via APIs and microservices. This role is ideal for someone passionate about Machine Learning who wants to see their work have an immediate, measurable impact on a market-leading product. CHECK24 offers a highly attractive package including a central location, flexible working hours, extensive professional development budgets, and a strong team culture with perks like free daily lunches and modern AI tools like Cursor and GPT to support your development process.

Required Skills

Education

Degree in Data Science, Computer Science, Mathematics, or a related quantitative field is implied; however, specific degree levels are not specified.

Experience

Professional experience in the development and operation of Machine Learning applications, from data preparation to production.
Experience in building stable data and training pipelines.
Practical experience with common ML frameworks such as Scikit-learn, TensorFlow, or Keras.
Experience in software engineering practices including version control (Git) and containerization (Docker).
Experience in ranking or recommender systems (e.g., Learn-to-Rank, Matrix Factorization) is highly preferred.

Languages

German (Fluent)

Additional

The position is based at a central location in Augsburg (HELIO). Candidates must be willing to work in a hybrid model with a focus on office culture and Friday remote options. Work involves interdisciplinary collaboration between IT and Product Management.