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.
qualification Strong on Reporting and Financial Modelling Forecasting Hands-on person MS Excel advanced qualification Strong on Reporting and Financial Modelling, Forecasting Hands-on person, MS Excel advanced
Capital Models : Create and oversee regulatory and economic capital models. Actuarial Models : Develop Develop and sustain actuarial models to support business operations. Risk Management : Assist with ORSA and
Capital Models : Create and oversee regulatory and economic capital models. Actuarial Models : Develop Develop and sustain actuarial models to support business operations. Risk Management : Assist with ORSA and
seasoned Senior Business Analyst. Hybrid working model followed 2 days at office 3 days remotely per week seasoned Senior Business Analyst. Hybrid working model followed 2 days at office 3 days remotely per week that must be considered. Employ a variety of modelling techniques to analyze, confirm and communicate diagram, use cases, solution context, domain and data models, business process diagrams, activity diagrams, Product Requirements Specification (PRS) Analysis models Solution Proposal Technical Rule Configuration
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
cross-functional teams to assess risk, develop models, and drive innovative solutions.
Requirements:
Proficiency in actuarial modeling software (e.g., Prophet, AXIS) and programming