Senior Data Analyst / Credit Risk Modeler

About the role

Raiffeisen Bank International is looking for a Senior Data Analyst / Senior Credit Risk Modeler in Tirana, Albania. You will develop, redevelop and maintain retail credit risk models (scorecards, PD and LGD) and IFRS 9 models, keeping them predictive, compliant and fit for business and regulatory purposes. The role also covers data quality, data modelling and clear communication of findings. It is a full-time hybrid position with flexibility to work remotely.

Key responsibilities

• Perform statistical analysis on credit risk data to identify trends, risk drivers and portfolio behaviour.
• Prepare, clean and transform datasets for modelling; check data quality, accuracy and consistency through quality checks, reconciliation and regular controls.
• Develop applications, behaviours and transactional scorecards, and PD, LGD and CCF models, according to regulatory and group requirements and agreed timelines.
• Contribute to model development with the methodology team, including joint improvement of policies, methodology concepts and tools in Databricks.
• Take part in seminars, workshops and meetings related to the role, and prepare model documentation templates.
• Present redeveloped models to the Validation Committee, address validation findings promptly, and liaise with validation owners, auditors and model stakeholders.
• Implement approved models in production by coordinating testing and validating outputs, then run quarterly model monitoring and recommend improvements.
• Work with Risk, IT, Data Management and Product teams, and coordinate with the RBI methodology team to meet group standards and regulatory expectations.
• Support internal audits by preparing documentation and providing analytical evidence.

Required profile

• University degree in Mathematics, Statistics, Economics, Business Informatics, Information Technology or a related field.
• Strong analytical skills and excellent communication skills.
• Attention to detail, problem-solving ability and ability to work in a hybrid environment.
• Banking, financial services or credit risk modelling experience is an advantage.

Required skills

• Proficiency in statistics and statistical tools for quantitative analysis and model validation.
• Data modelling for credit risk assessment.
• SQL, Python, R or similar is highly desirable.

To apply, submit your CV to the bank's recruitment team, stating the role in the subject line.