What you will be doing: Collaborate with cross-functional teams to analyse and document non-linear trading functionality Analyse the financial costs of risk and uncertainty Lead solutioning of trading integration requirements via APIs and backend systems Act as a liaison between technical teams and business stakeholders to ensure seamless delivery Provide expert support and training to internal teams and platform users Conduct product reviews and recommend enhancements aligned to market needs What we are looking for: BSc in Mathematical Sciences (Computational Science) / BSc Financial Engineering / BSc Actuarial Science and Financial Mathematics / B.Eng Engineering CQF Certificate in Quantitative Finance / CFA Chartered Financial Analyst / FRM Financial Risk Manager Experience in Cross Asset Trading and Risk (CATR) Quantitative Analysis Experience in Derivatives Trading (Volatility) Experience in X Valuations and Analytics Proficiency in trading platforms such as Front Arena, Murex, or Calypso Strong programming skills (Python, C++, C#, SQL, VBA, R, Matlab, Java) Strong analytical and problem-solving skills Excellent communication and stakeholder engagement abilities Proven project management experience with end-to-end delivery Understanding of financial modelling and technical environments Knowledge of risk management practices and regulatory requirements Leadership capability and experience managing cross-functional teams Strong adaptability in dynamic market environments Strong client relationship management skills Strategic thinking aligned to business objectives Please note if you do not hear from us within 3 weeks, please consider your application unsuccessful. Follow for the Latest Vacancies Join Psybergate Careers Channel here:

This is an opportunity for a highly skilled Senior Quantitative Analyst / Machine Learning Specialist to take ownership of complex, high-impact models across credit risk, financial crime, and advanced behavioural analytics. What Youll Be Doing: In this role, you will be at the centre of advanced analytics and model risk management: Independently validate and assess machine learning models across: Credit risk modelling Customer behaviour and propensity models Fraud detection and AML (financial crime) models Work hands-on with advanced ML techniques, including: Ensemble methods (XGBoost, CatBoost, and Random Forest) Neural networks Clustering and anomaly detection models Manage the full model lifecycle: Data preparation and feature engineering Model development, evaluation, and optimisation Deployment support and performance monitoring Build and review models in Python-based environments using large, complex datasets Partner with Risk, Technology, and Business teams to ensure that models are robust, scalable, and production-ready Provide technical leadership and mentorship to junior analysts and data scientists Ensure compliance with model governance, validation standards, and risk frameworks What You Bring: 68 years experience in quantitative analytics, data science, or machine learning Strong end-to-end model development experience in Python Advanced knowledge of SQL and large-scale data handling Proven experience with: Boosting algorithms (XGBoost and CatBoost) Neural networks Clustering and anomaly detection Exposure to credit risk, behavioural analytics, or financial crime modelling Experience in model validation, peer review, or model risk management Strong ability to balance technical depth with stakeholder engagement Qualifications: Honours or Masters degree in Mathematics, Statistics, Computer Science, Actuarial Science, or a related quantitative field Bonus Experience (Highly Valued): Experience leading or mentoring ML teams Exposure to regulated financial environments Cloud-based model deployment experience Credit scoring, IFRS-related analytics, or scorecard modelling Familiarity with model governance frameworks Why This Opportunity?: Work on real-world, high-impact models used across the business Exposure to a wide range of modelling applications (not siloed work) Strong mentorship from senior quantitative leaders A culture that values ownership, simplicity, and innovation Long-term career growth in a rapidly scaling analytics environment Requirements: Clear credit and criminal record Apply now! For more exciting Actuarial & Analytics vacancies, please visit:

This is an opportunity for a highly skilled Senior Quantitative Analyst / Machine Learning Specialist to take ownership of complex, high-impact models across credit risk, financial crime, and advanced behavioural analytics. What Youll Be Doing: In this role, you will be at the centre of advanced analytics and model risk management: Independently validate and assess machine learning models across: Credit risk modelling Customer behaviour and propensity models Fraud detection and AML (financial crime) models Work hands-on with advanced ML techniques, including: Ensemble methods (XGBoost, CatBoost, and Random Forest) Neural networks Clustering and anomaly detection models Manage the full model lifecycle: Data preparation and feature engineering Model development, evaluation, and optimisation Deployment support and performance monitoring Build and review models in Python-based environments using large, complex datasets Partner with Risk, Technology, and Business teams to ensure that models are robust, scalable, and production-ready Provide technical leadership and mentorship to junior analysts and data scientists Ensure compliance with model governance, validation standards, and risk frameworks What You Bring: 68 years experience in quantitative analytics, data science, or machine learning Strong end-to-end model development experience in Python Advanced knowledge of SQL and large-scale data handling Proven experience with: Boosting algorithms (XGBoost and CatBoost) Neural networks Clustering and anomaly detection Exposure to credit risk, behavioural analytics, or financial crime modelling Experience in model validation, peer review, or model risk management Strong ability to balance technical depth with stakeholder engagement Qualifications: Honours or Masters degree in Mathematics, Statistics, Computer Science, Actuarial Science, or a related quantitative field Bonus Experience (Highly Valued): Experience leading or mentoring ML teams Exposure to regulated financial environments Cloud-based model deployment experience Credit scoring, IFRS-related analytics, or scorecard modelling Familiarity with model governance frameworks Why This Opportunity?: Work on real-world, high-impact models used across the business Exposure to a wide range of modelling applications (not siloed work) Strong mentorship from senior quantitative leaders A culture that values ownership, simplicity, and innovation Long-term career growth in a rapidly scaling analytics environment Requirements: Clear credit and criminal record Apply now! For more exciting Actuarial & Analytics vacancies, please visit: