for the impairment and capital models (such as PD, LGD and EAD models) and using IFRS9 standards. You make a difference by providing input to the credit models. Education: Honours Degree in a Statistical, Mathematical risk model development or validating models. Model development experience in impairment models including including PD, LGD, EAD and IFRS9 model building experience. Economic capital model development. Experience with
using sophisticated analytics and machine learning models to address difficult business challenges and generate departments to design data strategies, build models, and embed those models into software-driven business processes Analysis and Modelling: - Develop and deploy machine learning and artificial intelligence models and algorithms for modelling. - Work with data engineering teams to ensure data availability and quality. Model Evaluation - Evaluate model performance and fine-tune models for improved accuracy. - Deploy models in production
providing analytical inputs into financial and risk models. We are primarily looking for Quantitative Analysts his quantitative skills to develop and implement models and analytical solutions for our clients. The bulk of credit and operational risk models (Basel II regulatory capital models, impairments) Development and and implementation of various quantitative models for clients in the banking and insurance industries Credit qualitative and quantitative approaches, as well as modelling, analytics, and forecasting Data mining, scrubbing
providing analytical inputs into financial and risk models. We are primarily looking for Quantitative Analysts his quantitative skills to develop and implement models and analytical solutions for our clients. The bulk of credit and operational risk models (Basel II regulatory capital models, impairments) Development and and implementation of various quantitative models for clients in the banking and insurance industries Credit qualitative and quantitative approaches, as well as modelling, analytics, and forecasting Data mining, scrubbing
clients in form of solution conceptualisation, modelling, design, and implementation of client focused coordination, project management, commercial modelling, solution implementation, solution stabilisation financial decision-making through advanced analytical modelling, using large sets of data. • The secondary focus solutions using appropriate fleet and network design modelling. • Driving “cost to serve” optimisation by principals or supply chain environment • Advanced Excel modelling and analytical skills • Advanced skills in Power
machine learning, statistical and mathematical models to solve business problems and enable the effective data by utilising cutting-edge technologies and model data preparation.
Responsibilities:
coordinate analytics and business intelligence models, creating visual data representations, and implement align with business goals. Business Intelligence Models : Establish and coordinate analytics and business descriptive models, including but not limited to Propensity to Pay, discount and settlement models, and commission commission rate models. Finance and Legal Collections: Work with finance and legal collections teams on on fair value, amortized cost modeling, and other financial models. Qualifications BSc in Business Data
coordinate analytics and business intelligence models, creating visual data representations, and implement align with business goals. Business Intelligence Models : Establish and coordinate analytics and business descriptive models, including but not limited to Propensity to Pay, discount and settlement models, and commission commission rate models. Finance and Legal Collections: Work with finance and legal collections teams on on fair value, amortized cost modeling, and other financial models. Qualifications BSc in Business Data
Personal Lines Pricing team through predictive modelling exercises and in-depth analytical investigations business objectives. Create and refine actuarial models to monitor business performance and support development initiatives. Taking ownership of lifetime value models and renewal strategies to maximize customer value value and retention. Utilize predictive modeling techniques to segment the client base and identify pricing pricing opportunities. Ensure models are accurate and fit for purpose, regularly monitoring their performance
Analysis and Modelling: Develop and deploy machine learning and artificial intelligence models and algorithms data for modelling Work with data engineering teams to ensure data availability and quality Model Evaluation Deployment: Evaluate model performance and fine-tune models for improved accuracy Deploy models in production Implement best practices for model version control and management Ensure proven models are integrated into business requirement for human intervention to implement the model within their respective businesses Cross-Functional