prompts to enable models to achieve business goals Developing custom machine learning models to enhance existing tasks Building and testing bespoke machine learning models to solve specialised problems in the clinical and healthcare. Developing and deploying machine learning models to enhance existing products or enable new product
use existing tools and models for this reporting, as well as to optimise models where required and perform ) Maintaining and optimising existing tools and models Research and investigations into client-relevant warehousing, cleaning, ETL and building scalable models and data pipelines Skilled at reporting, data visualisation
responsible for special model introduction project management to keep the models relevant as per customer the project changes post milestone PF as well as Model Year. Ensuring that the approval request is agreed divisional inputs are plausible. Represent the Group in model year meetings ensuring both the HUT and Platform
including Business Continuity, Third- Party, Data, Model, Fraud, and Technology (cyber or information security) engagements. Implement robust data governance and model risk management practices to ensure the accuracy completeness, and reliability of bank data and modelling processes. Lead the fraud risk management program managing Business Continuity, Third-Party, Data, Model, Fraud, and Technology risks. Deep knowledge of
including Business Continuity, Third- Party, Data, Model, Fraud, and Technology (cyber or information security) engagements. Implement robust data governance and model risk management practices to ensure the accuracy completeness, and reliability of bank data and modelling processes. Lead the fraud risk management program managing Business Continuity, Third-Party, Data, Model, Fraud, and Technology risks. Deep knowledge of
satisfaction. Finetune and optimise predictive models: Apply state-of-the-art techniques and frameworks learning as well as open-source LLM foundation models Build RAG and Agentic pipelines: Develop and implement solutions or proof of concepts with Large Language Models, including familiarity with frameworks such as lifecycle management of machine learning and language model operations. Front-End Development Skills: Proficiency
satisfaction. Finetune and optimise predictive models: Apply state-of-the-art techniques and frameworks learning as well as open-source LLM foundation models Build RAG and Agentic pipelines: Develop and implement solutions or proof of concepts with Large Language Models, including familiarity with frameworks such as lifecycle management of machine learning and language model operations. Front-End Development Skills: Proficiency
and initiatives. 3. Perform data analysis, data modelling, and data mapping to support business decision-making methodologies, tools, and best practices, such as process modelling, requirements elicitation, and solution evaluation analysis techniques and tools, including data modelling, SQL, and data visualization. 5. Strong project meet deadlines. 6. Knowledge of business process modelling techniques and tools, such as BPMN or UML, to
experience in a product owner/manager role Actuarial modelling, Product pricing and Statistical analysis techniques
experience in a product owner/manager role Actuarial modelling, Product pricing and Statistical analysis techniques