Key Responsibilities

• Develop and implement machine learning models to support claims management and decision-making.
• Apply statistical and predictive modelling techniques, including classification, regression, time-series analysis, clustering and anomaly detection.
• Analyse large, complex datasets to identify trends, emerging risks and opportunities for improved claims outcomes.
• Use Python, SQL and Azure Databricks to develop and deliver analytical solutions.
• Apply NLP and text analytics techniques to unstructured claims documentation.
• Evaluate, validate and monitor models to ensure reliability and performance in production.
• Work with business stakeholders and data professionals to translate business problems into practical analytical solutions.
• Support the delivery and ongoing optimisation of AI/ML solutions using CI/CD processes.
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About You

To be successful in this role, you will have:

• Demonstrated experience applying machine learning to large, complex datasets to solve business problems.
• Strong statistical analysis and predictive modelling skills.
• Experience with classification, regression, time-series analysis, clustering and anomaly detection.
• Practical experience with Python, SQL and Azure Databricks.
• Experience delivering AI/ML solutions using CI/CD processes.
• An understanding of monitoring and optimising production AI/ML solutions, including cost, latency and reliability.
• Strong analytical and problem-solving skills, with the ability to translate findings into meaningful business outcomes.
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Experience with NLP, text analytics and unstructured data is highly regarded, as is experience in government, insurance or another regulated environment.