London, South East, England, United Kingdom Hybrid / WFH Options
L&Q Group
aligned with strategic goals. Hands-on experience in change management, with a focus on embedding data-driven decision-making throughout the organisation. Strong analytical capabilities, including the application of statistical and mathematical models to support business insights. Exceptional communication and influencing skills, with the ability to engage and inspire stakeholders at all levels. A proactive and solutions-focused approach More ❯
23. The ideal candidate will have a strong quantitative background, hands-on programming experience in Python, and a track record of developing or validating AI/machine learning or statistical models in surveillance or conduct risk contexts. Key Responsibilities Independently validate and periodically review trade surveillance models for robustness and regulatory compliance Evaluate data quality, feature engineering, and model … performance across surveillance systems Review model documentation for conceptual soundness, implementation quality, and governance controls Conduct benchmarking, backtesting, and stress testing using Python to challenge model design Assess statistical and machine learning-based surveillance systems for transparency and effective alert thresholds Provide quantitative and qualitative assessments of model accuracy, stability, and business suitability Collaborate with model developers, compliance, and More ❯
23. The ideal candidate will have a strong quantitative background, hands-on programming experience in Python, and a track record of developing or validating AI/machine learning or statistical models in surveillance or conduct risk contexts. Key Responsibilities Independently validate and periodically review trade surveillance models for robustness and regulatory compliance Evaluate data quality, feature engineering, and model … performance across surveillance systems Review model documentation for conceptual soundness, implementation quality, and governance controls Conduct benchmarking, backtesting, and stress testing using Python to challenge model design Assess statistical and machine learning-based surveillance systems for transparency and effective alert thresholds Provide quantitative and qualitative assessments of model accuracy, stability, and business suitability Collaborate with model developers, compliance, and More ❯