Data Scientist in Financial Applications

Ideal candidate:

  • University degree in fields of computer science, business administration with a strong focus on information technology or a quantitative degree in mathematics, statistics, engineering with an additional focus on informatics and business administration
  • Excellent understanding of data-driven statistical methods, data mining, time-series analysis and machine learning algorithms
  • Proven knowledge in software engineering and architectural design
  • Ability to lead a complex data science project
  • Good scripting, programming and database skills (e.g. relational databases, R, Python, TensorFlow, Apache software stack: Hadoop, Spark)
  • Languages: Fluent written and spoken English, German skills beneficial
  • Knowledge of SAP products (especially SAP BW, SAP Hana, SAP Predictive Analytics) is a strong plus


  • Exploring and developing new use cases for data science methods within different domains of financial applications (e.g. prognosis of cash flow)
  • Detailing business requirements and set up of project according to CRISP-DM standards
  • Selecting features, building and optimizing classifiers using machine learning techniques
  • Data mining using state-of-the-art methods
  • Processing, cleansing, and verifying the integrity of data used for analysis
  • Doing ad-hoc analysis and presenting results to management
  • Creating automated anomaly detection systems
  • Constant tracking and optimization of model performance
  • Coordination and communication with our internal IT service department


  • Motivational financial package
  • Meal tickets
  • Medical insurance
  • Opportunities to grow and develop in a start-up environment
  • Dynamic and multicultural working environment
  • Great training opportunities
  • Transportation