management, pricing, segmentation, reinsurance models, capital modeling, and reserving. Your duties will include: on data Conducting experienced investigations Modeling reinsurance, reserving, and assessing capital capital requirements Implementing predictive modeling and client segmentation Enhancing automation and integration
analyzing vast datasets, developing predictive models, and optimizing collection strategies to enhance historical collection data. Develop predictive models to forecast debtor behavior, default rates, and analysis and modeling. Solid understanding of machine learning algorithms and statistical modeling techniques
sector. • Enhance and maintain advanced commission models • Perform in-depth sensitivity analysis to refine practices • Collaborate with IT to leverage data for model accuracy and automation • Uphold strict confidentiality related field • Proven experience in financial modeling, pricing analysis and data analysis • Advanced
Create financial models. Management Information analysis Business Information models Analysing data trends Adviceworx Operating Model & business processes. Building data models Automating data models Update dashboards
currently looking for a Structural Draughtsman/BIM Modeller to join their team in Cape Town. Responsibilities: specifications and industry standards. Generate accurate BIM models to facilitate project coordination and collaboration Provide support and guidance to junior drafters and modelers as needed. Qualifications: Minimum 5 years of drafting or BIM modeling capacity. Proficiency in producing detailed drawings and models for structural
Locations: Centurion l Johannesburg l Cape Town Working model: Hybrid Specification: The Data Engineer will have for data analysis, data manipulation, and data modelling. The candidate will be responsible for understanding Experience in data mining, large scale data modelling and business requirements gathering/analysis. Experience implementing data modelling methodologies like Dimensional Modelling and / or Data Vault. Working information to discover trends and patterns. Data Modelling (Relational and Star Schema). Database design
Locations: Centurion l Johannesburg l Cape Town Working model: Hybrid Specification: The Data Engineer will have for data analysis, data manipulation, and data modelling. The candidate will be responsible for understanding Experience in data mining, large scale data modelling and business requirements gathering/analysis. Experience implementing data modelling methodologies like Dimensional Modelling and / or Data Vault. Working information to discover trends and patterns. Data Modelling (Relational and Star Schema). Database design
responsibilities is to own and run complex project finance models for transactions in various stages of development Responsibilities: Build and run complex project finance models for greenfield project and acquisition opportunities and external stakeholders (including financial model sensitivities and scenarios) to facilitate effective respect of updating operating project financial models. Support operating project optimisation exercises competitor analysis. Skills needed: Project Finance modelling, including VBA and application of industry best
responsibilities is to own and run complex project finance models for transactions in various stages of development Responsibilities: Build and run complex project finance models for greenfield project and acquisition opportunities and external stakeholders (including financial model sensitivities and scenarios) to facilitate effective respect of updating operating project financial models. Support operating project optimisation exercises competitor analysis. Skills needed: Project Finance modelling, including VBA and application of industry best
medium term forecast via the internal forecasting model to ensure that the forecast is accurate and reflective evaluate possible risks and opportunities for new model introductions. Prepare volume studies for FBU and Excel to ensure that risks and opportunities of model introductions are highlighted. Prepare input MPL them to continue with their leg of the process. Model mix analysis to evaluate financial impact versus forecasting model, without it impacting on demand. Run-in and run-out planning of model types and model derivatives