Data Scientist in Financial Applications
Middle (2-5 ani), Entry (0-2 ani)
- 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 (. 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 (. 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
- Meal tickets
- Medical insurance
- Opportunities to grow and develop in a start-up environment
- Dynamic and multicultural working environment
- Great training opportunities
- Extra days off based on seniority
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- Do you have knowledge of R or Python?