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
frameworks and algorithm tuning
Qualifications
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
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:
Based in Centurion with a generous hybrid working model. Description The Data Engineer will have a knack for data analysis, data manipulation and data modelling and will be responsible for understanding and Experience in data mining, large scale data modelling and business requirements gathering/analysis. Experience implementing data modelling methodologies like Dimensional Modeling and / or Data Vault. Working information to discover trends and patterns. Data Modelling (Relational and Star Schema). Database design
Based in Centurion with a generous hybrid working model. Description The Data Engineer will have a knack for data analysis, data manipulation and data modelling and will be responsible for understanding and Experience in data mining, large scale data modelling and business requirements gathering/analysis. Experience implementing data modelling methodologies like Dimensional Modeling and / or Data Vault. Working information to discover trends and patterns. Data Modelling (Relational and Star Schema). Database design
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
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
candidate will develop software tools and data models to improve interpretation of mineralogical data development to extract appropriate information and modeling, simulation and interpretation of mineral behaviour J, VG StudioMax, Aviso, etc.). Coding and/or modelling experience, preferably with mineralogical/metallurgical/chemical
candidate will develop software tools and data models to improve interpretation of mineralogical data development to extract appropriate information and modeling, simulation and interpretation of mineral behaviour J, VG StudioMax, Aviso, etc.). Coding and/or modelling experience, preferably with mineralogical/metallurgical/chemical