The role requires very strong technical and communication skills. You will manage risk data including data capturing, organizing, storing, and analyzing for the development, validation, and implementation of Risk Rating Models and Scorecards. Key responsibilities include conducting risk analytics and generating comprehensive risk reports, providing advanced quantitative analytics support to the overall Risk Management function, and formulating management techniques for quality data collection to ensure adequacy, accuracy, and legitimacy of data. You will engage in Risk Architecture projects which involve the implementation of various risk IT applications, data analytics, data flows, standards, and processes.
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Possessing strong knowledge of Information Technology systems, Risk Management systems, tools, applications, and relational database management systems is essential. You will develop and implement AI analytics to analyze risk data using machine learning techniques to identify patterns, trends, and potential risks, as well as design data tracking and monitoring tools to analyze and validate data, ensuring data security.
Requirements
- Minimum 3 years of total experience in handling data management projects, data science, machine learning, and model development within the banking and finance sector, preferably in the Credit Risk domain (e.g., Basel II and IFRS 9).
- Bachelor’s degree in computer science, Engineering, Information Systems, or a related field.
- Master’s degree is preferred.
- Experience working with large and complex data sets, including alternative data for credit models.
- Experience in Credit Risk modeling and Risk analytics preferred.
- Strong quantitative skills and solid experience in developing, validating, and monitoring risk models.
- Advanced user of statistical software (such as SAS, R, Python, and SQL).
- Excellent oral and written communication skills in English.
- Flexible team player and able to work and deliver under pressure.
