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Data Analysis and Modelling:
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
extensive experience in IT/software development, data modelling, and data visualization. Qualifications: National cloud-based and on-premises Experience in data modelling, data partitioning, and implementing data security and analyze requirements Design and develop data models and data integration solutions Implement data security
Knowledge of Python and R Understanding of predictive modelling techniques and machine learning algorithms DUTIES: outcomes Identify risks associated with predictive modelling and mitigation thereof Integrate various datasets
Understanding and implementation of generative AI models and prompt engineering. Experience in creating management. AI Implementation Implement generative AI models for data analysis and prediction. Leverage AI for decision-making processes. Develop effective prompts for AI models to generate useful and relevant outputs. Continuously
cloud-based and on-premises.
cloud-based and on-premises
background Experience with physics and reality modelling, 3D graphics, hardware control, motion feedback
Demonstrated projects involving the use of generative AI models in data analysis, forecasting, or other relevant