Quantitative Analyst

You will be independently validate highâimpact models across credit risk, financial crime, and advanced analytics use cases. This is a handsâon technical role. What You'll Be Doing - Independent validation of machine learning models across: - Credit risk models - Propensity and behavioural models - Financial crime models (fraud and AML) - Applying advanced ML techniques, including: - Supervised learning (Random Forest, XGBoost, CatBoost, Neural Networks) - Unsupervised learning (clustering, isolation forests) - Managing model risk across the endâtoâend model lifecycle, including: - Feature engineering and data preparation - Model training, evaluation, and selection - Production deployment and monitoring - Building and reviewing models in Pythonâbased environments - Partnering closely with Risk, Technology, and Business stakeholders - Ensuring models meet governance, performance, and scalability standard What We Are Looking For - 58 years relevant experience - Strong handsâon experience building machine learning and data science models endâtoâend - Proven use of techniques such as: - Boosting algorithms (XGBoost, CatBoost) - Neural networks - Clustering and anomaly detection - Advanced proficiency in Python - Solid experience with SQL and working with large, complex datasets - Experience within credit risk, propensity modelling, or financial crime analytics - Experience with independent validation of models and/or detailed peer review - Proven experience researching machine learning model Qualifications - Honours or Masters degree in Mathematics, Statistics, Computer Science, Actuarial Science, or a related quantitative fiel Preferred/ Ideal - Experience deploying or supporting models in cloud environments - Exposure to credit risk modelling, scorecards, or IFRSârelated analytics - Financial crime (fraud or AML) modelling experience - Experience designing models with scalability and deployment in mind - Familiarity with model risk, governance, or validation standard What's in it for you? - Work on highâimpact, real-world models used across the industry. - Exposure to a wide variety of models, not just one product or portfolio - Learn from experienced quantitative leaders in a collaborative environment - Be part of a fast-growing organisation that values simplicity, transparency, and ownership - Competitive rewards, learning opportunities, and long-term career growt Conditions of Employment - Clear criminal and credit record Should you not receive a response from us within one week of your application, your application has unfortunately not been successful.