creating data flow diagrams (DFDs), defining data models, ensuring data lineage, and implementing data governance development with a focus on data lineage, data modeling, and data flow design. Proven experience with in creating data flow diagrams (DFDs) and data models.
the development and implementation of actuarial models, and collaborating with cross-functional teams regulatory requirements. Modelling and Coding: Develop and maintain actuarial models to analyse and forecast skills to enhance efficiency and accuracy in modelling processes. IFRS17 Reporting: Assist in the implementation consistency and accuracy of data used in actuarial models and financial reporting. Identify and resolve discrepancies opportunities for automation in data processing, modelling and reporting. Requirements: Bachelor's degree
the development and implementation of actuarial models, and collaborating with cross-functional teams regulatory requirements. Modelling and Coding: Develop and maintain actuarial models to analyse and forecast skills to enhance efficiency and accuracy in modelling processes. IFRS17 Reporting: Assist in the implementation consistency and accuracy of data used in actuarial models and financial reporting. Identify and resolve discrepancies opportunities for automation in data processing, modelling and reporting. Requirements: Bachelor's degree
seasoned Senior Business Analyst. Hybrid working model followed 2 days at office 3 days remotely per week must be considered.
vulnerabilities. Develop and maintain fraud detection models that are both accurate and minimize disruptions Optimizing Detection Models: Continuously review, analyze, and improve core models used to detect fraud legitimate transactions. This involves adjusting models and thresholds based on factors like desired alert Integrate new data sources when needed to improve model effectiveness. Assist data engineering efforts to data analysis. Experience applying statistical modelling techniques to solve complex problems. Familiarity
vulnerabilities. Develop and maintain fraud detection models that are both accurate and minimize disruptions Optimizing Detection Models: Continuously review, analyze, and improve core models used to detect fraud legitimate transactions. This involves adjusting models and thresholds based on factors like desired alert Integrate new data sources when needed to improve model effectiveness. Assist data engineering efforts to data analysis. Experience applying statistical modelling techniques to solve complex problems. Familiarity
in developing, implementing, and optimizing AI models and algorithms that support our business objectives
Responsibilities:
in developing, implementing, and optimizing AI models and algorithms that support our business objectives
Responsibilities:
in developing, implementing, and optimizing AI models and algorithms that support our business objectives effectively. Key Responsibilities: Develop and deploy AI models and algorithms to address business challenges. solutions. Monitor and evaluate the performance of AI models, making improvements as needed. Stay current with statistical analysis, data mining, and predictive modeling. Excellent problem-solving skills and attention