Found Description
Key Responsibilities
- Lead the independent validation of machine learning and predictive models across credit risk, financial crime, fraud, AML, and behavioural analytics.
- Review and validate the end-to-end model lifecycle, including feature engineering, model development, training, evaluation, deployment, and monitoring.
- Assess and challenge advanced machine learning methodologies, including boosting algorithms, neural networks, clustering techniques, and anomaly detection models.
- Build, review, and test quantitative models within Python-based environments.
- Monitor and manage model risk, ensuring compliance with governance and validation standards.
Experience
- 6-8+ years’ experience within Quantitative Analytics, Machine Learning, Data Science, Model Validation, or Risk Analytics.
- Proven experience developing and validating machine learning models end-to-end.
- Experience with...