Data Scientist - ETL


- Data gathering and extraction from different sources, ETL transformation of the data;
- Research on the potential methodologies to meet business expectations;
- Prototype the code to implement model logic
- Productionize the developed prototypes including design and development of data storage layer, APIs, visualizations and model monitoring
- Maintenance of the developed solution
- Participate in projects leading to end-to-end risk model deployments
- Work closely with the business stakeholders to understand model requirements and understand the scope of work required
- Develop methodologies and best practices for model implementation, validation, ongoing monitoring and issues remediation
- Ensure the documentation of the models meets highest standards
- Collaborate with team during the model review phase and on remediation of findings
- Education and training of end-users of the tools


- Higher education in a quantitative field (Physics/Mathematics/Computer Science/ Quantitative Finance or related is a must)
- At least 2-3 years of experience
- Strong intellectual/analytical potential and willingness to the goal of extending the existing risk models and to perform original applied research in the field;
- Strong programming skills in Python/R and experience with numpy, scipy, pandas, matplotlib, scikit-learn
- Hadoop
- Experience in building complex numerical simulations
- Practical working knowledge of some ML algorithms, working knowledge of at least one ML framework
- Experience in building complex ETL pipelines and in building end-to-end Machine Learning or analytical solutions with special emphasis on version control of the data (not code)
- Fluency in using Git and GitHub, Confluence, JIRA, understanding of agile methodologies
- Motivation to develop in the emerging field of enterprise risk modelling

The offer:

- Life insurance
- Interesting path of career in an international organization
- Private medical and dental care