Development Life Cycle models (Waterfall, Rapid Application Development, Spiral Model, Agile, etc.) required
and Datawarehouse Architecture development Data modelling including solid ETL, designing and building packages Warehousing / BI Development Experience with data modeling, data anlaysis, data profiling, data mapping and
warehousing projects. Strong understanding of data modelling concepts and techniques. Proficiency in SQL and for improvement. Data Modelling Assist in the design and development of data models that support business data engineers to create logical and physical data models for the data warehouse. Data Profiling and Analysis documentation for data warehouse requirements, data models, and processes. Ensure documentation is kept up-to-date
warehousing projects. Strong understanding of data modelling concepts and techniques. Proficiency in SQL and for improvement. Data Modelling Assist in the design and development of data models that support business data engineers to create logical and physical data models for the data warehouse. Data Profiling and Analysis documentation for data warehouse requirements, data models, and processes. Ensure documentation is kept up-to-date
responsibilities assigned in the Agile Working Model (AWM) Charter ADVANTAGEOUS SKILLS REQUIREMENTS: experience Architecture: Cloud, On-prem, hybrid, data modelling, SW-Architecture QUALIFICATIONS / EXPERIENCE NEEDED:
performance full stack applications; integrating AI models and solutions into existing and new platforms and Github Actions / Jenkins Any experience in data modelling / manipulation R100k to R120k pm
KPAs: Analytical Modeling: Translate business requirements into suitable analytical models, extracting trends to address short-term insurance metrics. Present model functionality to relevant stakeholders upon request oversee user-acceptance testing of Data Visualisation models. Administer the business intelligence management analytics reports, extracting insights from BI models for stakeholders. Stakeholder Engagement: Build
Job Purpose To develop and maintain best practice models and assessment strategies in line with regulations expectations by liaising with stakeholders through the model build process as well as the systems and strategy interacting with external bodies. The challenge model builds from around the cluster through peer review Seek opportunities to improve business processes; models and systems by identifying and recommending effective action where risk is identified in any processes; models or reporting; through analysis and formal communication
cases. 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 variety (must). Experience or familiarity with data science model operationalization on-prem or in the cloud (GCP and Skills Strong data exploration, analytical, modeling, and reporting skills Strong communication and
role in designing, developing, and implementing AI models and algorithms to solve complex business challenges Responsibilities: Create, build, and deploy AI models and algorithms to meet business requirements. Employ techniques. Prepare and sustain documentation for AI models, processes, and tools. Offer technical expertise