About Us
We are seeking an exceptional leader to join Klarna’s Risk Control, leading Model Risk and Model Validation team. This role is crucial to ensuring the integrity, accuracy, and compliance of our models while supporting sustainable business growth. Reporting directly to the Chief Risk Officer, the role offers a strategic opportunity to shape and oversee model risk management across Klarna’s global operations.
What you will do
Lead Klarna’s Model Risk and Model Validation function, sitting within the second line of defense as part of Risk Control.
Establish and maintain robust frameworks, policies, and procedures for model risk governance, in line with regulatory requirements and industry best practices.
- Manage the independent validation of a wide range of models, including but not limited to:
- Credit scoring models
- Fraud detection models
- IFRS9 Expected Credit Loss ( ECL) provisioning models
- Review and challenge model development methodologies, assumptions, and implementation processes to ensure their appropriateness, robustness, and transparency.
Conduct detailed assessments of model performance, accuracy, and limitations, providing actionable recommendations for improvements.
Collaborate closely with first-line teams, such as data scientists, model developers, and business units, to ensure alignment and effective communication of model-related risks.
Stay updated on evolving regulatory expectations (e.g., IFRS9, Basel III/IV) and emerging trends in machine learning and AI model validation.
Build and mentor a high-performing team of model validation professionals, fostering a culture of excellence, collaboration, and continuous learning.
Present findings, insights, and reports to senior management, audit committees, and regulators.
Who You Are
Proven leadership skills, with experience building and managing high-performing teams.
Experience interacting in with regulators and senior management
Advanced degree (Master’s or PhD) in a quantitative discipline such as Data Science, Statistics, Mathematics, Computer Science, or a related field.
Extensive experience (7+ years) in model development, validation, or risk management within the financial services sector.
Strong technical expertise in statistical and machine learning models, with a deep understanding of credit scoring, fraud detection, and IFRS9 ECL models.
Hands-on experience with programming languages and tools commonly used in data science, such as Python and SQL.
In-depth knowledge of regulatory requirements and expectations for model governance and validation.
Exceptional analytical, problem-solving, and decision-making abilities.
Excellent communication and stakeholder management skills, with the ability to convey complex technical information to non-technical audiences.
A passion for innovation and staying at the forefront of data science and risk management advancements.
Closing
Please include a CV in English.
