
Data Engineer to Non-Retail Credit Risk | SEB, Stockholm
- Stockholm
- Permanent
- Heltid
- Structured data management and analysis, working with large datasets
- Supporting the team as well as business, credit analysis and other teams, with data driven insights and recommendations to stakeholders
- Designing, implementing, and maintaining modern, scalable data pipelines to support credit risk modelling and reporting
- Building and maintaining ETL frameworks that ensure transparency, reproducibility, and regulatory compliance
- Upholding and improving data quality control framework, representing credit risk quantification in group functions involved in data quality
- Identifying data deficiencies and contributing to designing solutions to address such deficiencies (from input to IT development requirements to design of regular controls for ensuring adequate data quality)
- Interaction with control functions and IT development, specification of IT development requirements
- Documentation and regulatory interaction
- Responsibilities and tasks within the role of a data steward
- Have a true interest in building modern, scalable data infrastructure and driving automation through CI/CD
- Like to get things done and can translate challenges into concrete options on what to do next
- Show quantitative analytical capability, proactivity and problem-solving skills. You are comfortable working with large datasets and enjoy finding solutions to loosely defined problems
- Are a team player and can work closely and collaborate with external stakeholders from different parts of the bank
- Can prioritize and are committed to deliver high quality on time - also under time pressure
- Are honest and reliable, willing to speak up even when it is difficult
- A Master's degree within a quantitative field, including but not limited to statistics, mathematics, finance, economics or engineering
- Experience in working with data and business intelligence, knowledge of statistical models
- Version control and CI/CD (e.g. Git, GitLab/GitHub pipelines)
- ETL pipeline development (ELT is an advantage)
- Hands-on experience with extraction and visualization of insights from large datasets and long timeseries
- Knowledge of SAS, SQL and Python
- Knowledge in credit risk modelling (e.g., PD, LGD and EAD) is an advantage
- Knowledge in credit risk related legislation and supervisory guidelines (e.g., CRR and CRD) is an advantage
- Cloud platforms (e.g. Azure, AWS, GCP) is an advantage
- Strong communication skills in English, both spoken and written; knowledge of Swedish is an advantage
- Friendly and welcoming culture
- Challenging and interesting projects at the forefront of credit risk modelling
- A supportive environment for learning, development and career progression
- Attractive compensation and benefits.
Uptrail