Data Scientist – Fraud Analytics / Risk Modelling

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Data Scientist – Fraud Analytics / Risk Modelling Role Overview We are seeking an experienced Mid to Senior Level Data Scientist to enhance and maintain fraud detection and risk analytics models. The role involves model validation, threshold optimisation, performance monitoring and developing analytical solutions to identify potential fraud risks across public training grant schemes. Key Responsibilities Review, validate and optimise fraud detection models, including methodology assessments, backtesting, threshold calibration and performance evaluation. Develop and enhance fraud-risk indicators, scoring models, analytical rules and features based on business and operational requirements. Build and maintain technical dashboards to monitor model performance, including precision, recall, data drift, concept drift and alert thresholds . Analyse new grant schemes, eligibility criteria and claims processes to identify potential fraud risks and recommend appropriate detection approaches. Perform exploratory data analysis, data validation, anomaly investigation and impact assessments using large-scale datasets. Collaborate with business stakeholders, data engineers and management to translate requirements into analytical solutions. Maintain reproducible analytical workflows, model documentation, validation reports and knowledge transfer materials. Requirements Degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics or a related quantitative disciplin

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