Quantitative Analyst

SUMMARY:
We are partnering with a fast-growing, data-driven financial institution that is redefining how analytics, machine learning, and risk modelling shape smarter and fairer credit and banking decisions.
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.

POSITION INFO:

What You’ll 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, 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 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

• 6–8+ 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, 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 Master’s 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