Senior/Lead Data Scientist

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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