Model Risk Portfolio Analytics & Reporting Specialist

October 18, 2026

Senior

Warsaw, Poland

Description

A full-time model risk analytics and reporting position within a global banking risk function. The specialist reviews model risk topics, analyses model inventory and portfolio data, and builds dashboards, KPIs and automated reporting workflows using Python and Power BI. The role combines hands-on data work with AI-enabled reporting improvements, framework contributions and engagement with senior stakeholders.

Responsibilities

Perform reviews of model risk topics and provide expert advice, ensuring quality, consistency, and compliance with the MoRM framework
Analyze model inventory and portfolio data to identify emerging model risks, trends, concentrations, and areas requiring management attention
Design, develop, and maintain portfolio-level model risk dashboards, KPIs, and management reporting solutions
Build automated analytical processes and reporting workflows using Python and other data technologies to improve efficiency and reporting quality
Transform large and complex datasets into meaningful management information and actionable insights
Develop advanced visualizations and interactive reporting solutions in Power BI or similar platforms to support risk oversight and decision-making
Support the continuous enhancement of model inventory data quality controls, monitoring capabilities, and reporting frameworks
Leverage AI and new technologies to improve reporting deliverables, insight generation, stakeholder engagement, and operational efficiency
Participate in strategic initiatives and remediation activities, collaborating with global stakeholders across Risk, Data, Technology, and Business teams
Influence strategic change in stakeholder behaviour by promoting data-driven decision making and portfolio-based management of model risks
Draft business requirements and partner with technology teams to implement reporting, analytics, and automation enhancements in iModel and related tooling
Deliver analytical insights, presentations, and training sessions to senior stakeholders and model risk communities

Requirements

Master's degree in a quantitative field such as Mathematics, Statistics, Econometrics, Data Science, Computer Science, Engineering, Physics, or a related discipline
Strong understanding of model risk management concepts, modelling techniques, their applications, and associated risks
Proven experience in data analytics, reporting, and portfolio-level risk monitoring
Hands-on experience with Python programming, including data manipulation, automation, and analytical workflows
Advanced knowledge of data structuring, data modelling, and working with complex datasets from multiple sources
Experience with data visualization and dashboard development using Power BI, Tableau, or similar analytical platforms
Knowledge of SQL and database concepts; experience with large-scale data processing is considered a plus
Experience in designing and implementing automated reporting solutions and process improvements
Interest in Artificial Intelligence and emerging technologies, with practical experience applying AI-enabled solutions to reporting, analytics, or operational processes
Strong analytical and problem-solving skills, with the ability to translate data into actionable insights for senior stakeholders
Knowledge of relevant regulatory requirements and ethical guidelines applicable to model risk management
Strong communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences
Experience in model risk management, risk reporting, governance, framework implementation, or portfolio monitoring will be considered an advantage
Experience with Power BI semantic models, DAX, Power Query, or advanced dashboard design
Experience with AI-assisted analytics, GenAI, Copilot, or machine learning applications
Experience in data quality monitoring, data governance, and BCBS239-related initiatives
Experience working in Agile environments and cross-functional international teams