2 of 2 Model Validation Jobs in Northern Ireland

inform business strategies. Statistical Modeling : The ability to applying statistical techniques to extract insights, build predictive models, interpret data, and support data driven decision making. Machine Learning and AI Model End to End Management : The ability to build and manage the full lifecycle of ML models including development, validation, deployment, and monitoring in production environments. Collaboration : The ability … develop, test, and deploy advanced machine learning models, ensuring alignment with business objectives and seamless integration into client operations. Communication : The skill to effectively communicate complex analytical findings and model results to stakeholders, translating data-driven insights into business language that informs decision-making. Continuous Learning : The ability to stay informed of the latest advancements in data science, including … AI principles and programming is essential for success in this role. Ideally, you will also have Problem-Solving: Ability to translate business assumptions and rules into feature engineering and model explainability, addressing business problems with data-driven solutions. Collaborative Development: Work under the guidance of senior data scientists and solution architects to build models that align with strategic visions More ❯

inform business strategies. Statistical Modeling : The ability to applying statistical techniques to extract insights, build predictive models, interpret data, and support data driven decision making. Machine Learning and AI Model End to End Management : The ability to build and manage the full lifecycle of ML models including development, validation, deployment, and monitoring in production environments. Collaboration : The ability … develop, test, and deploy advanced machine learning models, ensuring alignment with business objectives and seamless integration into client operations. Communication : The skill to effectively communicate complex analytical findings and model results to stakeholders, translating data-driven insights into business language that informs decision-making. Continuous Learning : The ability to stay informed of the latest advancements in data science, including … statistics, mathematics, AI principles and programming is essential for success in this role. Nice-to-have Problem-Solving: Ability to translate business assumptions and rules into feature engineering and model explainability, addressing business problems with data-driven solutions. Collaborative Development: Work under the guidance of senior data scientists and solution architects to build models that align with strategic visions More ❯