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Data Scientist Professional
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Yubi Group is seeking a highly skilled Data Scientist Professional to develop and implement cutting-edge credit risk modeling solutions. To succeed in this role, you will need in-depth knowledge of machine learning algorithms, statistical analysis, and Python programming. This position requires strong collaboration and communication skills, as you will work closely with cross-functional teams to design, develop, and deliver end-to-end data products and solutions.
Key Responsibilities
• Design, develop, and deploy credit risk models to ensure high accuracy and regulatory compliance.
• Lead the development of a machine learning platform that empowers clients to build and customize their own credit risk models.
• Align data solutions with business objectives and technical constraints, adapting to evolving market dynamics, regulatory landscapes, and client requirements.
• Monitor model performance, maintain risk management protocols, and retrain models as needed to ensure ongoing accuracy and regulatory compliance.
• Stay up-to-date on industry trends, regulations, and emerging technologies to continuously improve the models and platform.
• Provide mentorship and guidance to junior data scientists and engineers within the team.
Requirements
• In-depth understanding of machine learning algorithms (supervised, unsupervised, ensemble methods) and their application to credit risk.
• Expertise in statistical analysis, including hypothesis testing, regression analysis, probability theory, and data modeling techniques to extract insights and validate machine learning models.
• Experience in designing, developing, and delivering end-to-end data products and solutions.
• Expertise in model explainability techniques (e.g., SHAP, LIME) and regulatory compliance for risk models.
• Strong proficiency in Python and working knowledge of PySpark.
• Proficiency in building and deploying models on cloud platforms (AWS).
• Familiarity with key financial instruments, regulatory frameworks (e.g., Basel III, IFRS 9), and their impact on risk assessment models.
• Bachelor's/Advanced degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 3-5 years of experience in the data science and machine learning domain.
• Experience in the financial sector or credit risk management is a bonus.
