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documenting and enhancing a range of predictive models across the entire credit life cycle. Responsibilities: in the development and application of predictive models across the entire credit life cycle. Conduct continuous research aimed at identifying predictors and enhancing model development practice and techniques. Monitor and Analysis, Data Science, Machine Learning, Predictive Modelling, Problem Solving & Analytical, Python Programming Understanding & knowledge of predictive modelling practices, performance standards & methodologies
focus on Prescriptive Analytics and Predictive Modelling. ● Engage with internal business clients with ● Create algorithms and build machine learning models to enhance product offerings and solve business systems to track model performance. ● Presentation of data science opportunities and model outcomes to a ● Experience or familiarity with data science model operationalization on-prem or in the cloud (GCP
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
statistical analysis, forecasting, predictive modelling, simulation and optimisation to discover trends statistical analysis, forecasting, predictive modelling, simulation and optimisation. to Identify, explore questions. o Design advanced analytics (quantitative) models that will answer key business questions or discover increased revenue or reduced costs. o Analyse model results, interpret findings and communicate these based on model results. o Run and automate regular reporting and operationalise successful models. o Establish
statistical analysis, forecasting, predictive modelling, simulation and optimisation to discover trends statistical analysis, forecasting, predictive modelling, simulation and optimisation. to Identify, explore questions. o Design advanced analytics (quantitative) models that will answer key business questions or discover increased revenue or reduced costs. o Analyse model results, interpret findings and communicate these based on model results. o Run and automate regular reporting and operationalise successful models. o Establish
BI (Including, but not limited to Ingestion, Modelling, Transformations and Cleansing, and DAX Expressions) and predictions. Aid in creating internal audit models and reports to identify risks and risk areas Identify Documentation up to date and the maintenance of semantic models Qualifications: Grade 12/Senior Certificate Tertiary BI (Including, but not limited to Ingestion, Modelling, Transformations and Cleansing, and DAX Expressions) and predictions. Aid in creating internal audit models and reports to identify risks and risk areas Identify
teams to understand business problems, develop models that drives automation, predictive analytics, advanced external data providers. Design and implement data modelling, data mining, and machine learning algorithms maintain predictive and prescriptive analytical models to support decision-making and drive business value and data transformation to prepare data for modelling and analysis. Utilize data visualization techniques audiences. Continuously evaluate and optimize existing models, algorithms, and data sources to improve accuracy
scorecards, frameworks and algorithm tuning Expose models and scorecards to other systems (API/Queue) Schedule (automation) Ability to identify the most relevant modelling approach based on the type of problem and available random forest, etc) Ability to train and maintain models Data cleaning and pre-processing (Size, data distribution including raw data) Experience in correctly applying model performance approaches in the context of the training training approaches taken (Classification Models, Confusion Metrix, etc) Qualifications & Experience: