Senior/Lead Data Scientist
at Klarna
Posted 19 hours ago
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Join Klarna’s Model Risk and Model Validation team within Risk Control to independently validate a range of models including credit scoring, fraud detection and IFRS9 ECL models. You will develop and maintain model performance monitoring systems (SQL, PySpark, Lambda), review methodologies and assumptions, and provide actionable recommendations to improve model robustness. The role involves close collaboration with first-line teams, establishing model governance frameworks, and ensuring alignment with regulatory expectations. Requires an advanced quantitative degree and 3+ years' experience in model development, validation, or risk management.
What you will do
• Develop and work in Klarna’s Model Risk and Model Validation function, sitting within the second line of defense as part of Risk Control
• 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
• Develop and maintain internal model performance monitoring system (SQL, PySpark, Lambda and Wiki)
• 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
• Establish and maintain robust frameworks, policies, and procedures for model risk governance, in line with regulatory requirements and industry best practices
• Stay updated on evolving regulatory expectations and emerging trends in machine learning and AI model validation
Who you are
• Advanced degree (Master’s or PhD) in a quantitative discipline such as Data Science, Statistics, Mathematics, Computer Science, or equivalent experience
• Experience (3+ 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, SQL, Spark and AWS
• Knowledge of regulatory requirements and expectations for model governance and validation
• Excellent analytical, problem-solving, and decision-making abilities
• Strong 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
Please include a CV in English.
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