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
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
structured and unstructured data sets. Responsibilities: Model complex business problems, discovering insights intelligent automation and predictive modelling. Build machine learning models from and utilises distributed Kafka. Provide input into Data management and modelling infrastructure requirements and adhere to the Ensure business integration through integrating model outputs into end-point production systems, are understood Measure proficiency in using the diagramming and modelling techniques vital for requirements analyses. Qualifications
of procurement and development efforts. Create models for new database development and/or changes to maintain and support, including SQL code optimization. Hands-on database tuning and troubleshooting experience
development efforts. Operational Management Create models for new database development and/or changes to maintain and support, including SQL code optimization Hands-on database tuning and troubleshooting experience
out for and on behalf of the organisation. Proven hands-on experience owning/managing a CRM system is a or Oracle. Experience with data cleansing, data modeling, and data restructuring within CRM systems. Strong
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
Development Life Cycle models (Waterfall, Rapid Application Development, Spiral Model, Agile, etc.) required
CSS, C#, TypeScript, etc. Comfortable with data modelling, Qlik NPrinting, data mapping, back and front-end existing Qlikview models. Data Clean up from source. Developing new Qlikview models. Maintaining automation